Regional Vulnerability to Food Insecurity: The Case of Indonesia

Abstract

Regional vulnerability manifests in various ways, one of which is food insecurity. Food insecurity is a global challenge and a key focus of Sustainable Development Goal 2, which aims to achieve zero hunger. This study aims to assess the level of regional vulnerability to food insecurity for 34 provinces in Indonesia. The components of vulnerability are defined by exposure, sensitivity, and adaptive capacity, while the dimensions of food insecurity are assessed through availability and access-utility. This study employed the composite index method to assess regional vulnerability to food insecurity in Indonesia for the year 2021. The analysis involved three calculation steps and utilized a subjective direct technique for indicator weighting. The findings emphasize the significant role of exposure in a region’s susceptibility to food insecurity. Mapping the conditions of exposure, sensitivity, and adaptive capacity indicates that 11.7% of Indonesian provinces are extremely vulnerable, with high exposure and sensitivity, and low adaptive capacity. To address these issues, these provinces should focus on diversifying food sources, improving market access for farmers, investing in essential agricultural infrastructure, and enhancing the agricultural sector through human resource development.

1. Introduction

Research in vulnerability is crucial as it helps determine the risk and impact a system, community, or individual may face during a threat or disaster. Vulnerability studies assess how well a society can withstand natural disasters or threats, whether social, economic, or physical. By analyzing vulnerability, we can identify which populations or regions are at greater risk, prioritizing them for targeted mitigation and adaptation efforts. Vulnerability is dynamic, influenced by factors such as human behavior, urbanization, and climate change, and research in this area allows us to adapt our strategies accordingly.

This study specifically examines the vulnerability of regions to food insecurity, offering valuable insights for broader research on vulnerability. As demonstrated, vulnerability manifests in various forms, including social, economic, and environmental aspects, and this study enhances our understanding of the need for comprehensive assessments [1]. This topic is crucial because it diversifies the cases in vulnerability studies, particularly in the context of food security, which significantly impacts people’s well-being. The research highlights how food vulnerability levels differ across regions, enabling the identification of areas most susceptible to food insecurity [2].

Food insecurity is a condition in which individuals, households, or regions are unable to meet their food needs adequately, in terms of food availability, access, and utilization. Food insecurity contributes directly to hunger and becomes one component of socioeconomic risk [3]. It contributes to an increase in cases of stunting, malnutrition, and infant mortality in many countries. The prevalence of undernourishment in Indonesia is increasing from 8.23% in the year 2017 to 10.21% in the year 2022. In the year 2021, stunting cases were recorded at 31.8%, malnutrition at 18%, and under-five deaths at 22.17 deaths per 1000 live births [4]. Indonesia’s 2021 Global Hunger Index (GHI) score of 18 positions it as the third highest in ASEAN countries, surpassing the global concern threshold of 9. Indonesia has been classified as severe by the World Health Organization (WHO), highlighting the prevalence of food insecurity among many individuals [5]. Food insecurity has placed Indonesia among the top five ASEAN countries for these health challenges [6]. Therefore, addressing food insecurity is an essential priority at both national and local levels, as it can help eliminate hunger and support the achievement of the Sustainable Development Goals (SDGs) related to zero hunger.

In Indonesia, several provinces have faced repeated famines over the past few decades, resulting in substantial fatalities. For instance, in 1997, 421 people perished in Jayawijaya; in 2005, 55 people died in Yahukimo; and in 2018, 71 children in Asmat succumbed to malnutrition and measles [7]. Approximately 68 districts or cities, which account for about 13% of Indonesia’s area, remain vulnerable to food insecurity, particularly in Eastern Indonesia and the 3T (underdeveloped, frontier, outermost) regions. This food insecurity is closely connected to poverty, low educational levels, and limited access to nutritional services such as stunting prevention programs [8].

Climate change is among the most urgent environmental challenges faced globally [9]. It is a significant shock that contributes to food insecurity, as it exacerbates the vulnerability of countries or regions to hunger and increases the risk of food scarcity. Addressing these challenges, it is crucial for regions to enhance their food provisioning capabilities to withstand the disruptions caused by climate change [10]. According to the European Commission [11], climate change substantially impacts food production by causing droughts and floods that affect agricultural land.

Indonesia experienced a decline in rice production by 10 million tons from 2018 to 2022 due to floods and drought [12]. In 2021, there was a 21% decrease in agricultural production with 70,076 hectares of agricultural land affected by flooding and 101,549 hectares affected by drought [13]. In addition to floods and droughts, the decline in production was also contributed to by the lack of irrigation facilities on agricultural land in Indonesia. As much as 45% of the 2.3 million hectares of total rice area in Indonesia does not have adequate irrigation facilities, and 10% of the existing irrigation systems were damaged [14].

The region vulnerability to food insecurity is further exacerbated by its dependence on food imports [15], as a high reliance on imports exposes the region to food insecurity. Food imports may be driven by growing demand for food. But, we must be aware, some countries that export food, such as India and Russia, place restrictions on the export quota, because they have concerns about potential food shortages resulting from extreme climate change [16].High food prices can also trigger vulnerabilities in food insecurity. The Global Food Price Index rose from 108.8 in 2021 to 121.2 in 2022 [12]. The rise in global food prices disproportionately affects impoverished individuals’ ability to consume the food [17].

There are several reasons why any region can avoid vulnerability to food insecurity. Firstly, regions can economically reduce dependence on food imports by creating food self-sufficiency and increasing employment opportunities for farmers. Second, regions can address the regional problems of poverty and income inequality. Third, the region can develop the ability to maintain nutritional quality [18].

This research enables us to comprehend the specific weaknesses of each region, facilitating the development of targeted solutions. This ensures that resources are efficiently utilized to address crucial issues. By prioritizing research on regional vulnerabilities to food insecurity, we can develop strategies for resilience and guarantee food accessibility for all, establishing a secure and stable food supply, which could enhance the future for the coming generations.

Regional susceptibility to food insecurity can be mitigated by delivering tailored information and alerts based on the food vulnerability assessments conducted across different areas. This approach is instrumental in shaping regional policies and creating effective interventions to tackle vulnerability.

This research gap addresses the lack of studies on regional vulnerability to food insecurity, particularly the absence of connections between the components of regional vulnerability and food insecurity. Additionally, the components used to create the composite index of food insecurity have not been correlated with each aspect of regional vulnerability. This research aims to evaluate regional susceptibility to food insecurity in Indonesia. This study aims to gain insights into the reasons and mechanisms behind the regions’ susceptibility to food insecurity by constructing a composite index that captures the intricate factors associated with food insecurity and regional vulnerability.

2. Literature Review

Most prior research has not thoroughly examined the relationship between regional vulnerability and food insecurity. Typically, studies focus independently on either vulnerability or food insecurity. The link between the elements of regional vulnerability and the dimensions of food insecurity remains inadequately addressed in earlier investigations.

2.1. Food Insecurity

Regional vulnerability refers to the weakened resilience of an area to both external and internal factors. Meanwhile, food insecurity is characterized by a chronic lack of access to sufficient food, either because of the inability to acquire or to produce food [19]. Some previous research from Nebie et al. [15], Shear et al. [20], Singh et al. [21] and Hoque et al. [22] explain that regional vulnerability to food insecurity signifies that the ability to meet food needs in a region is easily compromised. Regional susceptibility to food insecurity is influenced by three primary factors: food availability, access, and utility. Fan et al. [23] said that the availability of food is contingent on production levels, while access and utility pertain to a region’s ability to distribute food effectively and ensure that its benefits reach the population.

Fauzi [24] proposed a comprehensive approach to development that encompasses economic, social, and environmental dimensions. Fauzi [25] also highlighted that vulnerability extends beyond economic factors, being significantly shaped by the social and cultural contexts of a community. Issues such as poverty, inequality, and unemployment can exacerbate regional vulnerability to food insecurity, making it increasingly difficult for individuals to meet their food needs due to these constraints. A region is particularly susceptible to food insecurity when it experiences high levels of poverty, as poor communities are more likely to face food-related challenges and other disruptions beyond the economic domain [17].

Measuring regional vulnerability to food insecurity involves assessing how each area can provide, access, and utilize food. Food availability is achieved when sufficient quantities are consistently accessible to all individuals within a country [26]. This availability can be ensured through household production, domestic output, commercial imports, and food assistance. It relies on the interaction of domestic food reserves, commercial imports, food assistance, and local production, along with the key factors that influence these components [27]. The term “availability” can be confusing, as it may refer to food supplies at both household and broader levels, though it is most commonly used concerning regional or national supplies. Food access is influenced by the general availability of food, which affects market supply and prices [28].

Access to food is impacted by the physical, social, and policy environments that determine how effectively households can utilize their resources. Significant changes like droughts or social conflicts can seriously disrupt production strategies and threaten food access for affected households [29]. Access depends on household income, income distribution within the household, and food prices [30].

Food utility is fulfilled when all citizens receive adequate nutrition, which is reflected in health indicators such as the number of live births, and instances of malnutrition and stunting. Regions with high levels of adequate food utility typically have lower rates of infant mortality, malnutrition, and stunting [26].

2.2. Regional Vulnerability

Vulnerability refers to a reduced capacity for resilience due to external factors that threaten life, livelihoods, natural resources, infrastructure, economic productivity, and overall well-being [31]. Vulnerability theory serves as a framework for understanding and analyzing the circumstances under which individuals or groups encounter threats from various disasters, both natural and social. It encompasses multiple dimensions that impact a community’s ability to survive and adapt to present risks. In this context, vulnerability can be defined as a state that hinders a person or group’s ability to confront and manage threats [32].

The concept of vulnerability has been present since the 1970s, initially addressing susceptibility to hazards [25,33]. It gained prominence in the 1980s and 1990s by connecting disasters with developmental shortcomings. Vulnerability holds importance across numerous fields, such as ecology, public health, poverty and development, food security and hunger, land use changes, and the impacts and adaptation of climate. It also extends to interdisciplinary areas like sustainability science, global environmental change, and risk and resilience [31].

A key contributor to the advancement of vulnerability theory is Awotona [34], who identifies several critical elements of vulnerability, including social, institutional, systemic, environmental, and economic factors. These vulnerabilities can be categorized into three primary types: physical vulnerability, social vulnerability, and economic vulnerability. Physical vulnerability pertains to the susceptibility of infrastructure and buildings to disasters, while social vulnerability encompasses demographic and public health considerations [30].

In various studies, vulnerability is characterized by the dimensions of exposure and sensitivity of a system. In another field, the concept specifically incorporates the role of adaptive capacity in assessing vulnerability. Across different contexts and over time, the dimensions of vulnerability can reflect exposure, sensitivity, and adaptive capacity. Exposure and sensitivity relate to how systems react to stressors, while adaptive capacity refers to the ability to effectively adjust to or leverage the effects of these stressors. These dimensions are explained in detail as follows [25,35]:

• Exposure (E) refers to the presence of individuals, livelihoods, species or ecosystems, environmental functions and services, resources, and infrastructure, as well as economic, social, or cultural assets in regions that are susceptible to the negative impacts of climate change. There is a close relationship between exposure and vulnerability; as exposure in an area increases, so does its vulnerability. This correlation arises because greater exposure raises the likelihood of a region experiencing disasters or threats, thereby heightening its overall vulnerability. Areas with high exposure are more prone to natural disasters such as floods, earthquakes, and storms, which can result in damage to infrastructure, agriculture, and natural resources. Additionally, high exposure can impair essential infrastructure such as roads, bridges, and buildings, disrupting access to markets, healthcare facilities, and other critical services. Damage to infrastructure and the effects of natural disasters can hamper food supply to the affected regions, potentially leading to food scarcity and volatile prices. The combined effects of elevated regional exposure and vulnerability can contribute to food insecurity in impacted areas as disruptions from external factors exacerbate the situation.
• Sensitivity (S) pertains to the degree to which a system is affected by or responds to climate change drivers, including factors such as water supply sources, population mobility, and the overall quality of life for families. Sensitivity can be measured based on how much change or disturbance is required to cause a significant effect on a system or component. Sensitivity and vulnerability have a close relationship. A system or component that has a high sensitivity to changes or disturbances also has a high vulnerability to threats or disturbances. High sensitivity means that a system or component can be affected by relatively small changes or disturbances, thus making it more vulnerable to threats or disturbances.
• Adaptive capacity (AC) indicates the ability to avoid, anticipate, resolve, or manage impacts, or the ability to recover. Adaptive capacity refers to the ability of a system or community to adapt and adjust to changes or disturbances. Adaptive capacity and vulnerability have a negative relationship. This means that the higher the adaptive capacity of a system or community, the lower its vulnerability. This is because adaptive capacity can help a system or community to recognize and understand threats or disturbances.

From Figure 1, exposure and sensitivity are components that cause the region to be more vulnerable, while adaptive capacity is a component that can strengthen the region in dealing with problems that cause vulnerability [35,36].

Regions lacking food support capacity will make their vulnerability even more critical. Logistics infrastructure is critical for supporting the region’s strength against food insecurity. Infrastructure plays a crucial role in facilitating human needs in the food supply and accommodates the accessibility of upstream and downstream food needs [37]. Food insecurity can be avoided if the availability of food and access to food are met [5]. Abay [16] states that it is important to emphasize that areas susceptible to food insecurity are also influenced by insufficient food supply and limited access to food. Infrastructure and socioeconomic problems of the region affect the level of vulnerability on food insecurity. The level of welfare dramatically influences a person’s ability to fulfill the needs and quality of food. It is also challenging to increase the economic growth rate when the region is vulable to food insecurity. In terms of investors, countries that are vulnerable to problems will be reluctant to invest in the country [38].

Indonesia benefits from its abundance of natural resources. However, challenges persist in ensuring universal access to essential food. First, inadequate infrastructure is a significant issue in certain regions. While food production may be concentrated in specific areas, others face difficulties in accessing food because of deficient transportation infrastructure, particularly in remote locations [39]. Second, insufficient storage facilities and processing inefficiencies can result in food spoilage and waste, thereby diminishing the availability of food. Furthermore, various socioeconomic factors impact food accessibility, including income levels and price volatility. Limited income hampers individuals’ ability to purchase nutritious food, even when it is available. Meanwhile, fluctuations in food prices, particularly for staples such as rice, can pose challenges for low-income households in consistently obtaining food.

Korir et al. [26] and Sileshi et al. [31] explained that regional support significantly affects food availability and access. Infrastructure support and regional demographics can reduce vulnerability severity. For instance, studies in Zimbabwe show that irrigated households are significantly more likely to be food secure than those relying on rain. Vulnerable regions do not have adequate infrastructure to cope with food problems, and their demographic structures are sensitive to shocks. In addition, government policies illustrate how much the government cares about vulnerability. Regions facing a food crisis with poor management of food stocks and limited dietary variation are extremely vulnerable to food insecurity [40].

2.3. Climate Change on Regional Vulnerability to Food Insecurity

Climate change has affected various sociocultural, economic, and environmental facets of life. As global warming is projected to intensify, the frequency of extreme climate events is likely to rise, increasing the vulnerability of human populations and regional economies [41]. Insufficient adaptation to climate change may lead to significant short and long-term challenges, potentially undermining regional development [42]. When climate change impacts specific economic sectors within a regional economy, those sectors may struggle to operate normally and to recover swiftly on their own. This disruption can have a cascading effect, preventing other sectors from achieving their objectives and jeopardizing the overall stability of the regional economic system. Climate vulnerability compels the regional economic system to adapt to climate-induced changes, as the region seeks to bolster its capacity to prevent or mitigate related challenges [14].

Climate change has affected food security on a global scale. Increased temperatures, changes in rainfall patterns, and extreme weather events can interfere with agricultural production and reduce yields. In the agricultural sector, floods and droughts reduce production and impact food prices, availability, and accessibility [43]. Climate change poses a threat to regional capability. To overcome this challenge, we need to take regional actions. As the impact of climate change continues to affect agricultural production, many people face food insecurity. Regions that are unable to deal with the impact of climate change will experience food insecurity in the food sector. Food insecurity and vulnerability are closely linked because regions that are more vulnerable are often more likely to experience food insecurity [16,43].

3. Materials and Methods

This study employs a composite index as its methodology. A composite index, also referred to as a multi-column index, is a database indexing technique that creates an index across multiple columns of a table. To assess regional vulnerability to food insecurity, composite indices can integrate complex and multidimensional indicators into a single, straightforward metric. This approach enhances analysis and decision-making compared to relying on individual indicators separately. By utilizing a composite index, relevant weights can be assigned to each indicator according to their significance and data characteristics, thereby making the index results more representative and valid.

The vulnerability dimensions considered were exposure, sensitivity, and adaptive capacity. The analysis of food insecurity components was based on availability, access, and utility. Secondary data from 2021 obtained from the Ministry of Agriculture, Ministry of Health, and the National Food Agency were utilized. The process of constructing a composite index is illustrated in Figure 2.

As for the selection of variables based on previous research, Nebie et al. [15] and Hoque et al. [22] reveal that climate change impacts agricultural land through droughts and floods, disrupting agricultural production. Sileshi et al. [31] explain that nutritional quality is highly determined by the types of food consumed. This affects early childhood development, and maintaining adequate food consumption can reduce stunting, malnutrition, and early mortality rates. Abay et al. [16] explain that food imports lead to dependency in meeting food needs; regions with high import rates are more vulnerable. Phoung et al. [37] highlight the importance of irrigation in agricultural land as a strength for regions facing vulnerability issues, and the diversity of available food in an area can save it during a crisis of one food commodity.

In their research, Abay et al. [16] explain that large food expenditures, if not accompanied by the ability to meet them, make a region more vulnerable to food insecurity. Continuously increasing food prices makes it difficult for people to access food. Korir et al. [26] and Sileshi et al. [31] emphasize the importance of having young farmers, which becomes a source of strength for the agricultural sector in that region. Other factors can enhance a region’s adaptability against vulnerability to food insecurity. Korir et al. [26] explain further about income levels and market access. High income levels can fulfill people’s access to food, and markets, as providers of the food distributed in each region, can help with food procurement for the community. The details of the components of vulnerability, the dimension of food insecurity, and the indicators used are shown in

Table 1. Vulnerability dimensions, food insecurity components, and Forming Indicator Regional Vulnerability to Food Insecurity Index (RVFII).

Vulnerability Dimensions	Food Insecurity Component	Indicators	Unit	Code	Reference to RFVII	Source of Data
Exposure (Exp)	Availability (AV)	Percentage of villages that experienced flooding	%	E1	+	Statistics of Indonesia, 2021
		Percentage of villages that experienced drought	%	E2	+
	Access and Utility (AU)	Proportion of malnutrition in the population	%	E3	+	Ministry of Health, 2021
		Prevalence of stunting	%	E4	+
		Proportion of infant mortality	Lives per 1000 births	E5	+
		Prevalence of undernourishment	%	E6	+
Sensitivity (Sens)	Availability (AV)	Percentage of food supply from other regions to total food consumption	%	S1	+	Ministry of Agriculture, 2021
		Paddy fields without irrigation	%	S2	+
	Access and Utility (AU)	Consumer Price Index (CPI)	Index	S3	+	Statistics of Indonesia, 2021
		Proportion of household expenditure on food	%	S4	+
Adaptive Capacity (ACap)	Availability (AV)	Area of rice fields	(ha/cap)	AC 1	-	Statistics of Indonesia, 2021
		Share of agricultural sector	%	AC 2	-	Ministry of Agriculture, 2021 Ministry of Agriculture, 2021
		Proportion of young farmers (less than 45 years)	%	AC 3	-
		Number of farmers per extension workers	ratio	AC 4	-
		Farmers’ terms of trade	-	AC 5	-
	Access and Utility (AU)	Percentage of food diversity of staple foods (corn, sago, potato, cassava, and sweet potato) to total food production	%	AC 6	-	Statistics Indonesia, 2021
		Number of traditional markets per area	(units/km2/cap)	AC 7	-	Ministry of Agriculture, 2021

.

Data normalization was performed using the following formula [44]:

$$X_{ij}^{\ast }={\displaystyle \frac{\left(X_{ij}-X_{i}min\right)}{\left(X_{i}max-X_{i}min\right)}}\times \left(100\right)$$

(1)

where X*_ij is the normalized value of indicator I for province j. The maximum (X_imax) and minimum (X_imin) values for each indicator represent the highest and lowest values achieved by all provinces during 2017–2021, respectively. The normalized values fell within the range of 0–100.

The weight for each dimension was determined using the subjective direct method. Eight experts, including researchers, practitioners, and policy makers from various organizations, such as the Logistics Affairs Agency (Bulog), National Food Agency (Bapanas), Ministry of National Development Planning (Bappenas), Institute for Development of Economics and Finance (Indef), and Greenpeace, were asked to rank each indicator, component, and dimension. Weighting is applied for the vulnerability dimension, the food insecurity component, and each indicator. The rankings provided were analyzed using the ROC technique to calculate the weights, which was previously used by [44]. The formula used for this calculation is as follows:

$$W_j={\displaystyle \frac{1}{K}} {\sum }_{i=j}^K\left({\displaystyle \frac{1}{j}}\right)$$

(2)

where $W_j$ is the weight of the criteria with the jth rank; K is the number of indicators, components, and dimensions; and i is the priority order value of the criteria (indicators, components, and dimensions). The weighted values obtained are presented in parentheses in Table 2.

Table 2. Weights for dimensions, components, and indicators.

Vulnerability Dimensions	Food Insecurity Component	Indicators
Exposure (0.3)	Availability	Percentage of villages that experienced flooding (0.55)
	(0.65)	Percentage of villages that experienced drought (0.45)
	Access and Utility	Proportion of malnutrition in the population (0.46)
	(0.35)	Prevalence of stunting (0.27)
		Proportion of infant mortality (0.12)
		Prevalence of undernourishment (0.15)
Sensitivity (0.28)	Availability (0.65)	Percentage of food supply from others region to total food consumption (0.45)
		Paddy fields without irrigation (0.55)
	Access and Utility	Consumer Price Index (0.45)
	(0.35)	Proportion of household expenditure on food (0.55)
Adaptive Capacity (0.42)	Availability (0.65)	Area of rice fields per capita (ha/cap) (0.45)
		Share in the agricultural sector (0.08)
		Proportion of young farmers (less than 45 years) (0.15)
		Number of farmers to extension workers (0.17)
		Farmers’ terms of trade (0.15)
	Access and Utility (0.35)	Percentage of food diversity of staple foods (corn, sago, potato, cassava, and sweet potato) to total food production (0.41)
		Number of traditional markets per area (units/km2/Cap) (0.59)

Table 2. Weights for dimensions, components, and indicators.

Vulnerability Dimensions	Food Insecurity Component	Indicators
Exposure (0.3)	Availability	Percentage of villages that experienced flooding (0.55)
	(0.65)	Percentage of villages that experienced drought (0.45)
	Access and Utility	Proportion of malnutrition in the population (0.46)
	(0.35)	Prevalence of stunting (0.27)
		Proportion of infant mortality (0.12)
		Prevalence of undernourishment (0.15)
Sensitivity (0.28)	Availability (0.65)	Percentage of food supply from others region to total food consumption (0.45)
		Paddy fields without irrigation (0.55)
	Access and Utility	Consumer Price Index (0.45)
	(0.35)	Proportion of household expenditure on food (0.55)
Adaptive Capacity (0.42)	Availability (0.65)	Area of rice fields per capita (ha/cap) (0.45)
		Share in the agricultural sector (0.08)
		Proportion of young farmers (less than 45 years) (0.15)
		Number of farmers to extension workers (0.17)
		Farmers’ terms of trade (0.15)
	Access and Utility (0.35)	Percentage of food diversity of staple foods (corn, sago, potato, cassava, and sweet potato) to total food production (0.41)
		Number of traditional markets per area (units/km2/Cap) (0.59)

$${AV}_J^E=\sum _{i=1}^2{EAv}_{ij}{\times W}_{iEAv}$$

(3)

$${AU}_J^E=\sum _{i=3}^6{EAu}_{ij} {\times W}_{iEAu}$$

(4)

where the following applies:

• ${AV}_J^E$ is the sub-index of availability in the exposure dimension for the jth province.
• ${AU}_J^E$ is the sub-index of access and utility in the exposure dimension for the jth province.
• EAv_ij is the normalized value of each indicator of the availability component in the exposure dimension for the jth province.
• EAu_ij is the normalized value of each indicator of the access–utility component in the exposure dimension for the jth province.
• $W_{iEAv}$ is the weight of each indicator of the availability component in the exposure dimension.
• $W_{iEAu}$ is the weight of each indicator of the access–utility component in the exposure dimension.

$${AV}_J^S=\sum _{i=1}^2{SAv}_{ij}\times W_{iSAv}$$

(5)

$${AU}_J^S=\sum _{i=3}^4{SAu}_{ij}\times W_{iSAu}$$

(6)

where the following applies:

• ${AV}_J^S$ is the sub-index of availability in the sensitivity dimension for the jth province.
• ${AU}_J^S$ is the sub-index of access and utility in the sensitivity dimension for the jth province.
• SAv_ij is the normalized value of each indicator of the availability component in the sensitivity dimension for the jth province.
• SAu_ij is the normalized value of each indicator of the access–utility component in the sensitivity dimension for the jth province.
• $W_{iSAv}$ is the weight of each indicator of the availability component in the sensitivity dimension.
• $W_{iSAu}$ is the weight of each indicator of the access–utility component in the sensitivity dimension.

$${AV}_J^{Ac}=\sum _{i=1}^5{AcAv}_{ij}\times W_{iAcAv}$$

(7)

$${AU}_J^{Ac}=\sum _{i=6}^7{AcAu}_{ij}\times W_{iAcAu}$$

(8)

where the following applies:

• ${AV}_J^{Ac}$ is the sub-index of availability in the adaptive capacity dimension for the jth province.
• ${AU}_J^{Ac}$ is the sub-index of access and utility in the adaptive capacity dimension for the jth province.
• AcAv_ij is the normalized value of each indicator of the availability component in the adaptive capacity dimension for the jth province.
• AcAu_ij is the normalized value of each indicator of the access–utility component in the adaptive capacity dimension for the jth province.
• $W_{iAcAv}$ is the weight of each indicator of the availability component in the adaptive capacity dimension.
• $W_{iAcAu}$ is the weight of each indicator of the access–utility component in the adaptive capacity dimension.

The RVFII (Regional Vulnerability to Food Insecurity Index) is calculated in 3 steps. First is to calculate the exposure, sensitivity, and adaptive capacity dimension indexes for each province. Equations (3) and (4) are used to calculate each availability sub-index and access–utility sub-index for the exposure dimension, and both are aggregated to obtain the EI value using Equation (9). In the second step, Equations (5) and (6) are used to produce the availability sub-index and the access–utility sub-index for the sensitivity dimension, and both are aggregated to obtain the SI value in Equation (10). In the third step, Equations (7) and (8) are used to produce the availability sub-index and access–utility sub-index for the adaptive capacity dimension, and both are aggregated to obtain the ACI value in Equation (11).

$${\mathrm{EI}}_{\mathrm{j}}=({AV}_J^E\times W_{AV})+({AU}_J^E\times W_{Au})$$

(9)

$${\mathrm{SI}}_{\mathrm{j}}=({AV}_J^S\times W_{AV})+({AU}_J^S\times W_{Au})$$

(10)

$${\mathrm{ACI}}_{\mathrm{j}}=({AV}_J^A\times W_{AV})+({AU}_J^A\times W_{Au})$$

(11)

where the following applies:

• EI_j is the index of the exposure dimension on food insecurity for the jth province.
• SI_j is the index of the sensitivity dimension on food insecurity for the jth province.
• ACI_j is the index of the adaptive capacity dimension on food insecurity for the jth province.
• W_Av is the weight of the availability component of food insecurity.
• W_Au is the weight of the access–utility component of food insecurity.

Because ACIj give the negative sign as explained in Figure 1, an adjustment is needed to make ACI_j having positive sign to the vulnerability, using the Equation (12).

RevACI_j = 100 − ACI_j

(12)

The three sub-indices above, EI_j, SI_j and ACI_j, are then be agregated to derive the Regional Vulnerability to Food Insecurity Index (RVFII) by using the Equation (13).

RVFII_j = (EI_j.W_E) + (SI_j.W_S) + (RevACIj.W_AC)

(13)

where the following applies:

• W_E is the weight for the exposure dimension.
• W_S is the weight for the sensitivity dimension.
• W_AC is the weight for the adaptive capacity dimension.

4. Results

The regional vulnerability index to food insecurity offers a thorough evaluation of how prone a specific area is to difficulties in fulfilling its food needs. It measures the degree to which a region is at risk of experiencing obstacles in obtaining enough food supply. A higher index value suggests an increased level of vulnerability, indicating a greater chance of food insecurity impacting the residents.

According to

Table 3. Regional vulnerability to food insecurity index in Indonesia.

Provinces	Exposure Index (EI)	Sensitivity Index (SI)	Adaptive Capacity Index (ACI)	Reversed Adaptive Capacity (RevACI)	RVFII	Rank
East Nusa Tenggara	65.98	24.87	44.47	55.53	50.08	1
East Kalimantan	37.40	35.17	36.39	63.61	47.78	2
Papua	30.86	42.53	39.63	60.37	46.52	3
Bangka Belitung	27.73	41.74	37.94	62.06	46.07	4
Riau	28.68	40.75	38.16	61.84	45.99	5
North Kalimantan	32.61	36.55	40.35	59.65	45.07	6
East Java	23.83	45.79	41.04	58.96	44.73	7
North Maluku	37.59	23.41	36.87	63.13	44.35	8
DKI Jakarta	41.19	13.31	32.78	67.22	44.32	9
Riau Islands	24.88	23.38	28.17	71.83	44.18	10
West Kalimantan	46.22	37.84	55.98	44.02	42.95	11
Aceh	31.06	23.41	36.75	63.25	42.44	12
Banten	31.47	27.92	40.41	59.59	42.28	13
Jambi	28.15	32.40	42.98	57.02	41.47	14
Central Sulawesi	32.86	36.18	49.67	50.33	41.13	15
West Java	29.75	15.44	35.28	64.72	40.43	16
Maluku	31.43	11.36	34.82	65.18	39.98	17
DI. Yogyakarta	28.54	9.35	33.74	66.26	39.01	18
Central Java	26.61	22.32	41.33	58.67	38.88	19
Gorontalo	46.95	7.87	46.71	53.29	38.67	20
South Kalimantan	29.40	42.73	59.26	40.74	37.90	21
West Sulawesi	31.77	21.38	48.91	51.09	36.97	22
West Sumatra	32.48	15.65	46.35	53.65	36.66	23
North Sumatra	17.99	25.66	43.54	56.46	36.29	24
Central Kalimantan	44.59	43.74	74.62	25.38	36.29	25
West Nusa Tenggara	34.17	22.02	53.43	46.57	35.98	26
North Sulawesi	18.42	16.46	38.69	61.31	35.89	27
Lampung	18.41	33.38	50.54	49.46	35.64	28
South Sumatra	19.73	41.22	56.88	43.12	35.57	29
Bengkulu	19.17	16.67	47.24	52.76	32.58	30
Southeast Sulawesi	20.89	13.00	46.54	53.46	32.36	31
West Papua	26.14	24.18	59.87	40.13	31.47	32
South Sulawesi	24.93	23.36	64.32	35.68	29.00	33
Bali	12.53	2.28	49.03	50.97	25.81	34

and Figure 3, Bali Province had the lowest level of vulnerability. Bali is one of the provinces with significant development prospects, particularly regarding agricultural infrastructure (e.g., irrigation). Bali has a high proportion of young farmers. Bali’s exposure to drought and flooding is low, which makes it less vulnerable [45]. Bali’s geographical conditions also support efforts toward food self-sufficiency. An agricultural system closely linked to local wisdom and the community’s high level of agrarian culture also means that Bali can maintain guaranteed food availability. Bali is unique for agricultural systems. The Subak system, a traditional irrigation farming method that has existed since the ninth century, is an example of the local culture’s prowess in managing water resources sustainably [46]. With farmers collaborating to regulate water flow and collectively managing land, this system ensures that crops receive sufficient water, reducing the risk of food shortages. In addition, Bali Island has a very large local food potential. There are sweet potatoes, cassava, taro, suweg, corn, and other crops. Utilization of these alternative food sources can reduce the need for rice.

East Nusa Tenggara is identified as the most food-insecure province, registering an index value of 50.08. This region is particularly vulnerable to food insecurity challenges. Catastrophic climate change has intensified issues such as extreme drought, which annually impacts numerous districts, particularly during the dry season from September to November. A key factor contributing to the drought in NTT is the dry easterly monsoon winds that blow from Australia to Asia between April and October, resulting in reduced rainfall and a shortened rainy season. In some areas like Kupang, East Sumba, Rote Ndao, and Ende regencies, periods without rain can extend over 60 consecutive days. These prolonged dry spells diminish both water availability and quality, put stress on agricultural crops, heighten susceptibility to pests and diseases, lower crop yields, increase production costs, and jeopardize the economic sustainability of agriculture in the region [47,48].

The drought experienced in East Nusa Tenggara is attributed to climate change, which poses significant challenges to food production in the region [49]. Consequently, East Nusa Tenggara faces heightened vulnerability to food insecurity, leading to alarming stunting and malnutrition rates. The prevalence of malnutrition in East Nusa Tenggara is categorized as high; therefore, this province is very vulnerable to food consumption. In Raihat District, Asumanu Village witnessed 31.02 hectares of rice fields affected by drought, alongside Tohe Village with 6 hectares and Manumutin Village with 12.1 hectares [50].

The large number of rain-fed rice fields in East Nusa Tenggara exacerbates its regional vulnerability to food insecurity because these rice fields rely solely on rainfall. Furthermore, projections indicate a significant decrease in water availability for rain-fed rice fields by 2023, discouraging farmers from crop cultivation. Approximately 42.18% of the rice fields lack irrigation. The region’s limited agricultural infrastructure, particularly the absence of irrigation, makes East Nusa Tenggara susceptible to food insecurity due to water availability issues. In 2022, 2.5 hectares of rice land under the food estate program in Fatuketi Village, Kakuluk Mesak District, suffered damage due to flooding from the Rotiklot Dam. Another reason is that limited accessibility to markets and to storage and distribution facilities hinders effective food distribution, thereby increasing food insecurity. Many farmers also rely on one or two crops, such as maize and rice. This dependence makes them vulnerable to crop failure due to pests, diseases, or climate change. Economic problems such as high poverty rates and lack of access to education and modern agricultural technology make it difficult for communities to adapt to more productive agricultural practices [51].

Although East Java is one of the national rice barns and the number one rice-producing province in Indonesia, this does not make the province free from vulnerability to climate change. The assessment of sensitivity indicators, referring to Table 3, shows that East Java has the highest sensitivity index, which is 45.79. The East Java region is indeed extremely vulnerable to food insecurity, as Table 3 illustrates. Because of the significant proportion of household spending on food and the local Consumer Price score, East Java has a high sensitivity score. The quantity of agricultural extension workers and the percentage of young farmers in this region are small. This is what causes the East Java region to be so sensitive and vulnerable to food shortages.

As a result, the ratio of food needs fulfillment is not greater than the ratio of food consumption, meaning that consumption is much higher than production. This situation is exacerbated by East Java’s very large population, making it the second most populous province in Indonesia. In addition, the high Consumer Price Index (CPI) in East Java also leads to inadequate access to food. A similar phenomenon occurs in the provinces of West Java and Central Java, which are among the three largest rice-producing provinces but also have large consumer populations.

Central Kalimantan has the highest adaptive capacity among provinces. Designated as a food estate area by the government, development began in mid-2020, utilizing existing rice fields totaling approximately 30,000 ha. Agricultural infrastructure in the region is robust, with 84% of the rice fields equipped with irrigation. The per capita food stock exceeded 50%. The province also has a substantial proportion of young farmers, accounting for 40%, which is notable compared with other provinces. Furthermore, a favorable exchange rate for farmers contributes significantly to enhancing food availability in the region. East Kalimantan, like East Nusa Tenggara, is not a rice-producing region. Therefore, this province is more vulnerable in various aspects. It is easily exposed to external shocks such as climate change, is more sensitive to food access issues, including shrinking harvest areas and the impacts of extreme climate change, and does not have a large capacity to deal with food insecurity.

Based on the exposure, sensitivity, and adaptive capacity index, we can observe the position of each province in the following Cartesian diagram. The index scores in this diagram represent the values of the exposure, sensitivity, and adaptive capacity indices.

According to the map, provinces shaded in brown are susceptible to food insecurity, with darker shades indicating higher levels of vulnerability. In contrast, areas with low vulnerability are depicted in green, where lighter green shades represent even less risk. The three provinces most at risk for food insecurity are East Nusa Tenggara, East Kalimantan, and Papua. Additional details are illustrated in Cartesian diagrams that outline exposure–sensitivity, sensitivity–adaptive capacity, and exposure–adaptive capacity, as shown in Figure 4, Figure 5 and Figure 6.

Using the average value from Tabel 3 and Figure 4, Figure 5 and Figure 6 the positions of the exposure, sensitivity, and adaptive capacity are shown in

Table 4. Provincial categorization according to the exposure, sensitivity, and adaptive capacity index.

Exposure	Sensitivity	Adaptive Capacity	Province
Low	Low	High	West Papua, South Sulawesi, Bengkulu, Southeast Sulawesi, Bali
Low	Low	Low	North Sumatra, Riau Island, Central Java, North Sulawesi, West Java, DI Yogyakarta
Low	High	High	South Kalimantan, Lampung, South Sumatra
Low	High	Low	East Java, Riau, Jambi, Bangka Belitung
High	High	Low	Banten, North Kalimantan, Papua, East Kalimantan
High	High	High	West Kalimantan, Central Kalimantan, Central Sulawesi
High	Low	Low	Aceh, DKI Jakarta, East Nusa Tenggara, Maluku, North Maluku
High	Low	High	West Nusa Tenggara, West Sulawesi, West Sumatra, Gorontalo

. It is observed that only 14.7% Province have low levels of exposure, low sensitivity and high adaptive capacity, indicating a low level of vulnerability to food insecurity. These provinces are West Papua, South Sulawesi, Bengkulu, Southeast Sulawesi, and Bali. In the other hand, 11.7% of the regions provinces are extremely vulnerable to food insecurity, characterized by high exposure, high sensitivity, and low adaptive capacity; namely Banten, North Kalimantan, Papua, and East Kalimantan. Additionally, certain conditions may predispose other provinces to food insecurity, albeit not to an extreme degree. These concerning conditions are high exposure with low sensitivity and low adaptive capacity, as well as low exposure with high sensitivity and low adaptive capacity. Regions facing these challenges include Aceh, DKI Jakarta, East Nusa Tenggara, Maluku, North Maluku, East Java, Riau, Jambi, and Bangka Belitung.

5. Discussion

Certain areas known as rice producers remain vulnerable to food insecurity for several reasons. When considering the area of rice fields per capita, the ratio appears low due to their large populations, including provinces like West Java and East Java. This study highlights a new phenomenon where food availability does not match consumption levels. Even if a province is among the largest rice producers, it can still be highly sensitive to food insecurity when their population growth outstrips the province’s production capacity to meet consumption demands, or when the provinces do not have sufficient capacity to reduce vulnerabilities. This concept aligns with the opinion of economist Robert Malthus that population growth can surpass the availability of natural resources. Additionally, the conversion of land in Java is reducing rice field areas, further increasing vulnerability to food insecurity [52].

Farmers can use digital technologies like drones for land mapping and soil nutrient assessment, gaining precise information on fertilizer needs and soil conditions. This enables targeted fertilization, boosting yields while minimizing input waste. Moreover, precision agriculture technology optimizes water, fertilizers, and pesticides management, potentially cutting production costs by up to 40% compared to traditional methods. This approach is essential crucial for drought-prone areas, promoting the efficient and sustainable use of resources [12].

Moreover, high inflation rates in the region have driven up the prices of staple food, eroding people’s purchasing power. Families are struggling to afford basic food items, including rice. Additionally, fluctuations in the rupiah’s exchange rate have impacted the costs of agricultural inputs, making it more challenging for farmers to procure essential materials for production [53].

Compounding this issue is the diminishing interest among the younger generation in pursuing farming careers. Many young people prefer urban jobs, leaving behind the agricultural lands nurtured by their parents. The lack of young farmers hinders the adoption of modern and innovative farming practices, contributing to a decline in overall productivity. Cumulatively, these factors exacerbate food insecurity. This underscores that despite the region’s plentiful rice production, vulnerabilities to demographic, economic, and social issues persist.

This analysis is corroborated by the current food conditions in Indonesia, especially in regions like East Nusa Tenggara, which is facing droughts making the region more vulnerable. The others province is East Kalimantan, classified as experiencing a food crisis due to limited agricultural land, dependence on external food sources, and weak agricultural infrastructure. Similar challenges are observed in other countries, such as Bangladesh, Senegal, Myanmar, Sri Lanka, and Pakistan. The financial crisis exacerbated by conflicts, particularly the Taliban’s rise to power in Afghanistan in August 2021, has worsened conditions. In Sri Lanka, economic turmoil has been aggravated by the war in Ukraine, leading to severe shortages and an annual food price inflation rate of 64% as of December 2022 [54]. Throughout 2022, Bangladesh and Myanmar experienced heightened vulnerabilities, widespread displacement, and restricted population movement, adversely affecting livelihoods, production, and food access [55]. In Pakistan, excessive rainfall from monsoon winds—three times the average of the past 30 years—has resulted in flash floods and landslides, further complicated by a prior heat wave.

Given the continued vulnerability to food insecurity in many parts of Indonesia, it is imperative to implement policies aimed at strengthening the region. Introducing a variety of crops and protein sources, such as fish and poultry, can increase food availability and lower the risk of crop failures, a strategy successfully employed by Vietnam [37]. Additionally, supporting small farmers with access to quality seeds, training in sustainable agricultural practices, modern high technology, and microfinance initiatives can bolster local food production, as seen in China’s approach to empowering farmers with technology and maximizing productivity on limited land. In China, agricultural infrastructure, characterized by effective irrigation, efficient storage and distribution systems, and strong market access, also provides a useful model [23].

In the future, Indonesia needs to tackle the challenges in areas vulnerable to food insecurity. Essential investments in the development and modernization of agricultural infrastructure—such as irrigation systems, farm roads, water management, and storage facilities—are crucial for supporting efficient food distribution. Upgrading irrigation systems is particularly vital for combating drought and ensuring an adequate water supply for crops, especially in regions like NTT and other drought-prone areas [47,48].

It is also important to highlight the critical role of decision-makers, with both central and local governments prioritizing food self-sufficiency to mitigate the region’s vulnerability to food insecurity. Furthermore, enhancing food access through improved storage facilities and maintaining price stability is essential [42].

The limitations of this study mainly stem from data availability; Statistics Indonesia has only updated information up to 2021, and many provinces have not conducted recent censuses. Therefore, future research should concentrate on updating these data and exploring tailored strategies, policies, and actions that address the specific conditions of each Indonesian province.

6. Conclusions

Regional food security initiatives are essential for generating a significant impact at the national level. When a region prioritizes the enhancement of its food security, it can increase food production locally, thereby supporting the national food supply [56]. This production increases the region to not only fulfill its own food requirements but also to begin exporting to other areas. Such actions help reduce reliance on imported food and contribute to strengthening the local economy.

Measuring regional vulnerability to food insecurity is a good initiative because it serves as an early warning for each region on the state of existing food sufficiency [29,57]. When a region prioritizes improving food access and availability, it can strive to increase local food production, food diversity, and infrastructure that makes it easier for people to gain access to food. Such efforts help reduce dependence on imported food and reduce the region’s vulnerability to food insecurity.

To tackle regional vulnerability to food insecurity, certain policies can be implemented, including food diversification, enhancing food storage infrastructure, and strengthening the knowledge and skills of local farmers. Addressing regional vulnerabilities is not just a technical challenge; it is a crucial step toward fostering equity and stability in developing countries like Indonesia. Regions with high vulnerability are at greater risk of experiencing food insecurity crises. Research is vital for pinpointing these vulnerable areas and developing strategies to prevent widespread hunger and malnutrition. Additionally, food insecurity in one area can create ripple effects, affecting neighboring regions by disrupting trade and influencing national food prices. Strengthening regional food security efforts contributes to the creation of a more resilient food system and promotes sustainability at the regional level.

The findings of this study indicate that exposure is a significant factor in a region’s susceptibility to food insecurity. Areas with high values in the exposure and sensitivity dimensions of the food insecurity index are particularly vulnerable. Mapping the conditions related to exposure, sensitivity, and adaptive capacity reveals that 14.7% of regions in Indonesia are extremely vulnerable to food insecurity. These are Banten, North Kalimantan, Papua, East Kalimantan, all exhibiting high levels of exposure and sensitivity coupled with low adaptive capacity. Regions with a high vulnerability index to food insecurity must tackle these challenges by diversifying food sources, improving market access for farmers, investing in crucial agricultural infrastructure such as irrigated rice fields, and enhancing the agricultural sector through human resource development, including increasing the number of young farmers and agricultural extension workers.