Novel Rap-Landslide Method for Assessing Agroforestry Sustainability in Landslide-Prone Areas

Abstract

Landslides are becoming increasingly frequent, intensified by extreme rainfall and human activities, and threaten ecosystems and livelihoods. In Nyomplong, West Java, they have displaced residents and damaged land, which is now repurposed for agroforestry. Sustainable agroforestry management is crucial for reducing landslide risks and enhancing farmer livelihoods, and a comprehensive assessment is required. This study presents Rapid Appraisal for Landslide (Rap-Landslide), a novel method for assessing agroforestry sustainability. Multidimensional Scaling evaluates economic, environmental, social, technological, and institutional dimensions, focusing on key factors in landslide mitigation, land conservation, and productivity enhancement. The approach includes data collection, sustainability evaluation, leverage factor analysis, and validity testing. This study indicates that the sustainability index of agroforestry in Nyomplong ranges from 40.66% to 62.82%, with an average of 56.16%, classifying it as moderately sustainable. Monte Carlo analysis confirms that this study maintains a stable sustainability status with high confidence. Furthermore, Rap-Landslide leverage analysis identifies 15 key attributes significantly influencing sustainability. Key strategies for improvement include more substantial government support in agroforestry policies, farmer group empowerment, the adoption of conservation technologies such as terracing and soil biotechnology, the use of organic fertilizers, appropriate crop selection, and improved market access. Rap-Landslide can be applied to other landslide-prone areas, offering a systematic approach to evaluating sustainability and guiding effective land management strategies.

1. Introduction

Landslide events have become increasingly frequent and destructive in Indonesia and globally, often resulting in severe impacts on human life, livelihoods, and the environment. Yulianto et al. (2021) [1] reported a significant upward trend in disaster occurrences across Indonesia from 1815 to 2019, predominantly caused by climate-related events, including 10,438 floods, 6050 landslides, 2124 droughts, and 1914 forest and land fires, with annual incidences rising from just 1 in 1815 to 3885 in 2019. Similarly, multiple devastating landslides have occurred in Idukki, India, since 1958, with major events in 1989, 1997, 1977, and 1958. The most severe disaster struck Pettimudi village on 6 August 2020, claiming 70 lives due to heavy rainfall-induced floods and landslides, marking the event as having the highest recorded landslide casualties in Kerala [2]. Global warming intensifies extreme precipitation, increasing landslide risks [3]. Over the past decade, climate change has contributed to 32.8% of landslide-related damages in Jiangxi Province, totaling CNY 57 million [3]. Despite this upward trend in landslide disasters, research on effective management and mitigation strategies remains limited.

Landslides also occurred in the Nyomplong area, West Java, in 2020 as part of a series of massive landslides in Bogor Regency, Indonesia. This event led to the relocation of the entire village population and the abandonment of the landslide-affected land. However, residents continue to utilize the land for cultivation as their primary livelihood. The diverse vegetation planted follows an agroforestry pattern, a land management practice that integrates agriculture and forestry to create a system that supports environmental, social, and economic sustainability.

Agroforestry represents an integrated land-use strategy that combines ecological and technological practices to enhance productivity through sustainable management [4]. It is also a highly effective technique for landslide mitigation, as it reduces landslide risk by strategically selecting appropriate tree species based on factors such as species type, age, diversity, and management, particularly in hillside and landscape-scale applications [5]. By implementing agroforestry systems that incorporate a diverse mix of tree crops and food crops, farmers can mitigate landslide risks and vulnerabilities while simultaneously enhancing household food security [6]. Agroforestry offers a sustainable and economically viable strategy for landslide mitigation by enabling the production of diverse resources such as food crops, fodder for livestock, building materials, and medicinal plants [7]. Agroforestry presents a valuable opportunity for smallholder farmers to generate income and has the potential for further expansion by overcoming existing barriers to enhance productivity. Multiple factors affect its effectiveness, including personal attributes, household context, socio-economic conditions, environmental factors, and institutional support [8]. The recovery process is slow in many vulnerable rural areas, especially those relying on agroforestry systems, and community resilience remains limited. There is an urgent need for practical, rapid, and community-adapted methods to assess sustainability and guide targeted interventions for risk reduction and livelihood improvement.

Determining sustainability status is crucial for assisting policymakers and stakeholders in making informed decisions to ensure the long-term viability of agroforestry. Multidimensional Scaling (MDS), implemented through Rapid Appraisal for Fisheries (Rapfish), is one of the tools commonly used to evaluate sustainability. As a type of Multi-Criteria Analysis (MCA), this method applies an ordination technique that ranks quantitative indicators based on their relative performance [9]. Originally, it was designed to facilitate interdisciplinary evaluations of fishery sustainability. Initially developed for fishery policy guidance, it has since been adapted for other sectors, including farming practices (RapLandUse), forestation (RapPforest), and local forest management (RapCF). Additionally, MDS-based studies have been conducted to assess the sustainability of biorefinery production processes involving Palm Oil Mill Effluent (POME) [10].

The Multidimensional Scaling (MDS) method has been widely implemented across various regions in Indonesia, particularly in fisheries, agriculture, forestry, and mining. MDS has been used to analyze the sustainability of citrus farming practices by focusing on ecological, economic, and social dimensions to develop a sustainable agricultural model in Malang, Indonesia [11]. It has also been applied to evaluate key sustainability factors, such as fertilizer availability and vegetation cover, which influence the sustainability of dryland management in Jerowaru, East Lombok, Indonesia [12]. Additionally, MDS has been utilized to assess the post-mining sustainability of coal extraction sites, emphasizing improvements in social and environmental aspects [13]. In Kendari, Indonesia, MDS has been employed to evaluate the sustainability of urban watersheds. The study assessed five dimensions and found that while some watersheds were relatively sustainable, others were less so. Vegetation cover, slope, land degradation, and water usage were identified as key sustainability factors [14]. Sujiman et al. (2024) [15] analyzed the sustainability of landslide management in a coal mining region of Kutai Kartanegara Regency, East Kalimantan, Indonesia. Meanwhile, in Bengkulu Province, Indonesia, MDS was applied to evaluate the sustainability of an economic recovery initiative following the 2019 floods and landslides [16]. Studies using the MDS method to assess post-landslide land sustainability remain limited, particularly for risk reduction, hazard mitigation, and community economic improvement. Furthermore, no research has evaluated agroforestry systems’ sustainability for landslide mitigation and economic enhancement using MDS. With landslides becoming increasingly frequent in Indonesia, especially in rural areas, a comprehensive assessment of agroforestry sustainability as a mitigation strategy is crucial.

This study introduces Rapid Appraisal for Landslide (Rap-Landslide), a novel approach for assessing agroforestry sustainability in the context of landslide mitigation and economic improvement. MDS results depend heavily on the quality and relevance of the input variables. Improvement in methodology is defined by the criteria and rationale for selecting variables, such as slope, rainfall, and land use. To improve this method to enhance the rigor, validity, and practical utility of the MDS approach in Rap-Landslide, several additional controls can be implemented to ensure more reliable and actionable results for decision-making. These include controls for expert bias and the subjectivity, relevance, and independence of indicators, geographic and geomorphological diversity, sensitivity to different scenarios, the temporal dynamics of data, the validation of clustering outcomes, consistency in scaling and measurement, transparent documentation, and integration with decision-support frameworks.

This study is motivated by the need to address these challenges by applying the Rap-Landslide method—a participatory, multidimensional assessment tool designed to evaluate the sustainability of agroforestry systems in landslide-prone regions. By identifying key attributes that influence resilience and sustainability, this method aims to support faster, evidence-based recovery efforts and enhance the adaptive capacity of at-risk communities.

The method is applied through a case study in the Nyomplong area, West Java. Rap-Landslide, an adaptation of Rapfish (Rapid Appraisal for Fisheries), improves sustainability assessments by incorporating economic, environmental, social, technological, and institutional factors, key attributes related to landslide mitigation, land conservation, and productivity enhancement. This study evaluates the sustainability status of agroforestry in Nyomplong and identifies key factors influencing its long-term viability. The method is validated through a Monte Carlo simulation. This work highlights key leverage attributes influencing sustainability and proposes targeted strategies for improvement. The approach highlights the significance of implementing innovative and sustainable land management strategies to reduce landslide risks. This assessment also aids in recognizing and applying more efficient mitigation efforts. Findings from this study are expected to support policymakers and local communities in developing resilient and sustainable agroforestry-based landslide mitigation strategies, for Nyomplong and for other landslide-prone areas.

Despite being practical, rapid, and well adapted to community contexts, this method has limitations, particularly in excluding biophysical and geotechnical factors that could enhance future sustainability assessments—especially in high-risk landslide areas, which should be addressed in further research. As Alcántara-Ayala (2025) [17] noted, a key challenge in reducing landslide disaster risk is understanding and addressing the complex interplay between socio-environmental transformations and geodynamic processes.

2. Materials and Methods

2.1. Study Area

The study area is located in the Nyomplong area in Bogor Regency, West Java, which is approximately 101 km from Jakarta and can be reached by car in about 3 h and 15 min. On 1 January 2020, the village experienced a landslide due to a massive event that struck the western Bogor region. The affected area lies 676–783 m above sea level in a hilly landscape (Figure 1). The topography comprises undulating hills with steep-to-moderate slopes (Figure 1 and Figure 2). Intense rainfall saturates the soil, reducing slope stability and triggering landslides. Over time, the landslide area has undergone natural revegetation, and residents have repurposed the affected land for agroforestry (Figure 3).

2.2. Rap-Landslide Method

This research utilizes an innovative rapid assessment technique known as the Rap-Landslide method, an adaptation of the Rapfish (Rapid Appraisal for Fisheries) approach. It evaluates agroforestry’s sustainability practices for mitigating landslides in the Nyomplong region, West Java. Rapfish was originally developed as a rapid evaluation tool for assessing fisheries’ sustainability and compliance with responsible fishing standards [20]. While it retains the core Multidimensional Scaling (MDS) technique from Rapfish, Rap-Landslide has been methodologically extended and contextually tailored to address the unique challenges of landslide-prone agroforestry systems. The algorithmic structure of the Rap-Landslide method consists of four main procedural steps: (1) collecting primary and secondary data and identifying relevant sustainability indicators through stakeholder consultations, including Focus Group Discussions (FGDs); (2) scoring the sustainability status using a modified MDS approach that incorporates five key dimensions—environmental, economic, social, technological, and institutional—each with context-specific attributes; (3) conducting leverage factor analysis to identify the most sensitive attributes that significantly influence overall sustainability performance; and (4) applying a Monte Carlo simulation to assess the robustness and confidence level of the MDS results. This structured and iterative approach not only enhances the methodological rigor of sustainability assessment but also provides actionable insights for land management in disaster-prone landscapes.

Rap-Landslide employs the Multidimensional Scaling (MDS) approach to evaluate various sustainability dimensions. In this study, the quantitative attribute ranking in Rap-Landslide has been adjusted to incorporate factors relevant to landslide mitigation and farmer income improvement. Rap-Landslide breaks new ground through five tailored dimensions of sustainability populated with landslide-prone agroforestry system-specific indicators.

Agroforestry systems can aid in restoring and stabilizing landslide-affected areas while contributing to sustainable land use. Trees planted within agroforestry systems help reinforce soil structure and reduce erosion, particularly in landslide-prone areas or regions experiencing heavy rainfall [21]. The adaptation of Rap-Landslide in assessing economic, environmental, social, technological, and institutional dimensions focuses on key factors related to landslide mitigation, land conservation enhancement, and productivity improvement, which include the following:

• Environmental Dimension: focuses on the effectiveness of vegetation in preventing erosion and landslides, soil conservation measures, and overall ecosystem conditions.
• Social Dimension: evaluates community preparedness for landslides, the role and performance of farmer groups, and education related to conservation, agroforestry, and disaster mitigation.
• Economic Dimension: considers capital investment and agroforestry development costs, financial support for farmers, potential economic benefits of agroforestry systems, and their overall feasibility.
• Technological Dimension: examines land management and conservation techniques for landslide mitigation, appropriate vegetation selection for conservation and mitigation purposes, and harvesting and post-harvest processing technologies.
• Institutional Dimension: assesses government involvement in farmer group activities, policies or regulations supporting agroforestry as a landslide mitigation strategy, and coordination among relevant institutions.

These factors serve as the foundation for a Focus Group Discussion (FGD), which is conducted to determine specific assessment attributes for each sustainability dimension.

2.3. Data Collection and Analysis

This research incorporates both primary and secondary data sources. Primary data were obtained from key institutions, such as the Forestry and Plantation Office and the Nyomplong Village Government, as well as through field observations and direct interviews. Surveys were conducted with key stakeholders residing in areas susceptible to landslides to evaluate agroforestry-based sustainability strategies for mitigating landslides across defined dimensions. Secondary data collection involved a literature review of research articles, agroforestry sustainability guidelines, and local forestry policies.

The MDS method was applied to analyze the sustainability of agroforestry practices aimed at landslide mitigation in the Nyomplong region. The selected attributes reflect sustainability levels across disciplines tailored to the resource characteristics under study [22]. A Focus Group Discussion (FGD) was conducted with the participants comprising village government officials, forestry office representatives, farmer group members, agroforestry practitioners, extension agents, analysts, agribusiness organizations, company representatives, and emergency management personnel to evaluate the status of agroforestry stakeholders, support systems, and resource management at the study location. Insights from the FGD informed the formulation of sustainability dimensions and indicators. A questionnaire will be formulated based on the results of the FGD and used to conduct interviews with 20 selected respondents. These 20 respondents were purposively selected based on their active involvement, expertise, and knowledge in mixed garden management within the agroforestry system in the Nyomplong area. The Rap-Landslide method was structured into five key dimensions: environmental/ecological, economic, social, technological, and institutional.

A total of 48 attributes were identified (

Table 1. Rap-Landslide dimensions and their corresponding attributes.

Dimension	Attributes
Environment	Suitability of soil structure and typology for agroforestry Thickness of fertile surface soil Water conservation measures Water source condition Level of soil conservation knowledge and practices Utilization of organic fertilizer in cultivation activities Utilization of inorganic fertilizers in cultivation activities Land productivity level Land suitability for agroforestry farming Pesticide application practices Degree of soil erosion Unauthorized tree logging
Social	Farmers’ level of education Government policies related to conservation aspects Practiced habits related to conservation aspects Social networks related to conservation aspects Community attitudes towards land conservation measures Community perception of land conservation Community understanding of agroforestry conservation Farmer group performance Farmer participation in farmer groups Farmers’ knowledge of controlling pests and diseases Availability of agroforestry technology packages Frequency of agroforestry counseling
Economy	Products produced from agroforestry systems that have economic value Community income outside the agricultural business Formal education level of the community How many working days for land cultivation Product marketing method Acquisition of agroforestry business capital Ease of access to market facilities and infrastructure Is there a cooperative that accommodates agricultural products? Products that are marketed
Technology	How to prepare the land How to maintain the crop How to harvest Post-harvest process Availability of production facilities and infrastructure Suitability of vegetation types with land conservation aspects Crop rotation techniques by land conservation aspects Variety of crops, by land conservation technology Tillage techniques, by conservation technology
Institutional	Understanding and application of customary rules Decision-making processes in farmer group activities Availability of consulting and mentoring assistance from authorities/government/research institutions The existence of financial institutions that help provide production capital The existence of supporting regulations for agroforestry processing businesses from the government The suitability of central and regional policies related to agroforestry management

). These dimensions and attributes were incorporated into a questionnaire, with responses evaluated using a Likert scale. Expert respondents assigned scores of 0 (poor), 1 (average), and 2 (good) to assess sustainability performance. The quantitative ranking of attributes across the environmental, social, economic, technological, and institutional dimensions was adjusted to align with relevant factors in landslide mitigation and farmer income improvement.

2.4. Agroforestry Sustainability Analysis

Sustainability performance is classified into four levels, based on percentage intervals of 0–25% (poor, unsustainable), 25.01–50% (less, less sustainability), 50.01–75% (quite, fairly sustainable), and 75.01–100% (good, very sustainable) [23]. These categories are detailed in

Table 2. Sustainability index categories and status for each dimension.

No	Index Range (%)	Classification	Sustainability Status
1	0–25	Poor	Unsustainable
2	25.01–50	Less	Less
3	50.01–75	Quite	Fairly
4	75.01–100	Good	Very

Source: [24].

.

The ordination method utilizes the alternating least squares method, based on the square root of Euclidean distance, known as the ASCAL algorithm. This approach improves ordination by minimizing the squared differences $d_{ij}$ to the squared data (origin = $o_{ijk}$ across three dimensions (_{i, j, k}), referred to as S-Stress. The ordination process is determined based on Euclidean distance in n-dimensional space and is expressed as follows (Pitcher, 2001) [22]:

$$d=\sqrt{\left({\left|x_1-x_2\right|}^2+{|y_1-y_2|}^2+{\left|z_1-x_2\right|}^2+\dots \right)}$$

(1)

The positioning of objects or points in MDS was determined by regressing the Euclidean distance ($d_{ij}$) between points _i and _j against the reference point ($o_{ij}$), as expressed in the following equation:

$$d_{ij}=\alpha +\beta \delta {\beta }_{ij}+\epsilon$$

(2)

The regression method applied to the equation above utilized the ALSCAL algorithm. This approach optimizes the squared distance ($d_{ijk}$) relative to the squared data (point of origin = $o_{ijk}$), which, in three dimensions (_{i, j, k}), is expressed through a formula known as S-Stress as follows:

$$s=\sqrt{{\displaystyle \frac{1}{m}}\sum _{k=1}^m\left[{\displaystyle \frac{{\sum }_i{\sum }_{j }{\left({ d}_{ijk}^2-{ o}_{ijk}^2\right)}^2}{{\sum }_i{\sum }_{j }{o}_{ijk}^4}}\right]}$$

(3)

where the squared distance is Euclidian distance assigned a value:

$$d_{ijk}=\sum _{a=1}^r{w}_{ka} {\left(x_{ia}-x_{ja}\right)}^2$$

(4)

2.5. Leverage Factor Analysis

Leverage factor values range between 2% and 8%, reflecting a moderate-to-good impact. Factors with values below 2% are deemed not influential, whereas those exceeding 8% are categorized as dominant (sustainable), as outlined in [22].

Table 3. Leverage factor parameter values.

No	Factor Value (%)	Category	Description
1	<2.0	Neutral	Not influential
2	2–8	Influential	Moderate-to-good impact
3	>8.0	Significant	Dominant

Source: [22].

lists the influential and dominant factors.

2.6. Validity Assessment Through Monte Carlo Simulation

Monte Carlo simulation assesses uncertainty in MDS by calculating the error margin. To evaluate the stability of the sustainability index, controlled stochastic variation was incorporated into the score matrix, followed by a series of 25 random simulation iterations. This approach enabled the assessment of the sensitivity of the Multidimensional Scaling (MDS) results and the statistical robustness of the resulting sustainability classifications. A small difference between MDS and Monte Carlo values (less than 5%) indicates that the MDS analysis provides a dependable sustainability assessment with 95% confidence.

3. Results and Discussion

3.1. Sustainability Analysis

The MDS analysis results for agroforestry performance indicate a sustainability score of 56.16% on a 0–100 scale, with R² (SQR) > 0.80, suggesting that agroforestry falls within the quite category and is considered fairly sustainable (

Table 4. Sustainability assessment scores by dimension.

Dimension	Index Score (%)	Stress Value	SQR/R2	Sustainability Status
Environmental	60.99	0.15	0.98	Fairly
Social	56.36	0.18	0.97	Fairly
Economical	42.66	0.16	0.93	Less
Technological	57.97	0.17	0.97	Fairly
Institutional	62.82	0.15	0.98	Fairly
Average	56.16			Fairly

). The score is calculated based on an assessment of 48 attributes distributed across five key dimensions: environmental, social, economic, technological, and institutional. The environmental dimension recorded an index of 60.99%, social an index of 56.36%, economic an index of 42.66%, technological an index of 57.97%, and institutional an index of 62.82%. The average index score across these five dimensions is 56.16%, with R² (SQR) > 0.80. The results of the sustainability evaluation are summarized in Figure 4 and Table 4 and visually illustrated using a radar diagram in Figure 4.

3.2. Leverage Analysis

3.2.1. Environmental Dimension

The agroforestry sustainability score in the environmental dimension is 60.99%, indicating that agroforestry practices in Nyomplong area are classified as fairly sustainable from an environmental perspective. Leverage analysis results reveal that among the twelve attributes within the environmental dimension, two attributes, land productivity and the use of organic fertilizers in cultivation, are at the highest level, with a leverage value of 3.06% (Figure 5).

Enhancing land productivity and utilizing organic fertilizers are crucial environmental factors influencing the sustainability of agroforestry in the post-landslide area of Nyomplong. Organic fertilizers improve land productivity by enhancing soil fertility, structure, and ecosystem health. However, for optimal results, their application must be adjusted according to soil type, crop requirements, and environmental conditions. Organic fertilizers contribute to microbial necromass carbon storage, particularly by promoting the formation of organo-bound Fe and non-crystalline Fe while reducing carbon loss through microbial mineralization. Microbial necromass carbon is stored in decomposed organic matter such as wood, leaves, roots, and dead organisms, present in both natural and agricultural ecosystems.

After 13 years, using 100% and 50% organic fertilizers resulted in a 110.0% and 99.0% increase in soil organic carbon (SOC) content, respectively, at a depth of 0–10 cm. This finding highlights that replacing chemical fertilizers with organic alternatives is a sustainable approach that improves SOC stability through organic–mineral interactions, supporting soil fertility and the global carbon cycle [25]. Furthermore, substituting 25% and 37.5% of nitrogen-based chemical fertilizers with organic fertilizers optimized grain yield [26]. This replacement notably impacts nitrate nitrogen residue in the soil, organic matter levels, and microbial communities, which contribute to regulating plant growth, optimizing water productivity, and improving nitrogen utilization efficiency, ultimately resulting in higher grain yields.

The sustainability of land productivity is supported by a combination of soil conservation practices and crop rotation. A high level of knowledge and implementation of soil conservation practices influences community awareness in restoring vegetation in landslide-affected areas. Another key leverage attribute within the environmental dimension is land suitability, which encompasses biophysical, climatic, topographical, socio-economic, and environmental aspects. A comprehensive understanding and assessment of these factors ensure the effective implementation of agroforestry, enhancing productivity, preserving environmental sustainability, and supporting community well-being. Implementing targeted measures to enhance land productivity, encourage organic fertilizer use, and assess land suitability for agroforestry in post-landslide areas is essential for facilitating vegetation recovery as part of landslide mitigation efforts.

3.2.2. Social Dimension

The sustainability index of agroforestry in the social dimension is 56.36% (Table 4), indicating that agroforestry is fairly sustainable from a social perspective. Among the twelve assessed attributes, two had the highest leverage in enhancing agroforestry activities for landslide mitigation: farmer group performance and community perception of land conservation, with influence of 3.06% and 3.05%, respectively (Figure 6). Effective farmer group performance is a key factor in achieving sustainable agroforestry. Through collaboration, education, efficient resource management, and conservation practices, farmer groups can play a central role in sustaining agroforestry from economic, social, and environmental perspectives. One critical aspect related to farmer group performance that requires improvement is farmer participation within the group, as it significantly affects the group’s effectiveness and the benefits gained by both members and the broader community (2.72%). Involvement in peer groups plays a crucial role in various innovation programs, particularly those introduced by external stakeholders [27].

Agroforestry’s sustainability is significantly influenced by community perceptions of land conservation. Awareness of its importance has grown in various communities, especially following landslides, flash floods, and soil degradation [28]. Raising awareness about conservation benefits and actively involving the community in agroforestry practices can enhance sustainability by integrating economic, social, and ecological advantages. Therefore, implementing education programs, fostering community participation, and providing incentives are essential to strengthen positive perceptions of land conservation.

Agroforestry contributes to improving community livelihoods and plays a significant role in preserving natural forests within the study area. Thus, stakeholders must prioritize the sustainable development of agroforestry systems [29]. Policies supporting agroforestry development can further enhance the community’s perception of land conservation as an effective landslide mitigation strategy. A well-functioning farmer group structure, high levels of farmer participation, and a strong community understanding of land conservation will collectively improve disaster preparedness and promote effective collaboration in landslide mitigation efforts.

3.2.3. Economic Dimension

The agroforestry sustainability index for the economic dimension in Nyomplong is 42.66%, indicating that agroforestry practices in the area are less sustainable from an economic perspective (Table 4). Leverage analysis results show that the attribute with the highest influence is the level of formal education within the community, with a score of 3.84% (Figure 7), making it the most critical factor to improve. This finding highlights the need to enhance formal education within the community as a strategic step toward achieving sustainable agroforestry. According to [30], the effectiveness of agricultural and plantation innovations is influenced by multiple factors, including farmer demographics, education levels, land ownership, and the availability of agricultural extension support.

Formal education significantly contributes to the economic sustainability of agroforestry by enhancing community knowledge, skills, and awareness. This relationship is mutually reinforcing—better economic conditions enable access to education, while education facilitates the adoption of more productive and sustainable agroforestry practices. Government financial support is essential in funding farmer education, which can also contribute to the costs of landslide mitigation efforts, for farmers with limited knowledge of agroforestry, social norms, social structures, and community support play crucial roles in adoption.

Research indicates that the perceived benefits of agroforestry serve as key drivers of agricultural innovation adoption [31]. However, access to conventional knowledge alone is insufficient to promote agroforestry adoption. Socio-economic factors such as social participation, networks, peer groups/associations, and access to microloans also play significant roles. Farmer-to-farmer relationships facilitate the exchange of information, knowledge sharing, and discussions of challenges, as farmers often share similar geographical, economic, and social contexts. In Ghana, farmers exchange agroforestry knowledge related to diversification, production, vulnerability, ecology, innovation, and technology, which are crucial for successfully implementing agroforestry practices [32]. Strengthening community education, fostering social networks, and providing financial incentives can create an enabling environment for sustainable agroforestry adoption, ultimately enhancing economic resilience and environmental conservation in landslide-prone areas.

Another key leverage factor in the economic dimension is community income from non-agroforestry activities, which has a leverage value of 3.52. To enhance the sustainability of agroforestry, the diversification of agroforestry-based enterprises can be pursued, including agrotourism and ecotourism, as well as the development of non-timber forest products such as honey and essential oils. Additionally, food businesses utilizing forest and plantation products, such as tea and coffee, present viable economic opportunities. Agroforestry, in particular, can support the development of these programs while enhancing community competencies in these sectors.

Economic analysis suggests that providing beehives can be a profitable venture under various economic scenarios related to crop value (dollars per ton) and pollination costs (dollars per hive) [33]. To anticipate and encourage farmers’ potential involvement in non-agricultural sectors, diversification is essential [34]; therefore, agroforestry practitioners can remain focused on agricultural and forestry sectors [35].

3.2.4. Technological Dimension

The sustainability score for the technological dimension is recorded at 57.97% (Table 4), suggesting that the technological dimension exhibits moderate sustainability in agroforestry practices. The results of the leverage assessment suggest that the nine attributes within this dimension have leverage values ranging from 1.88% to 3.84% (Figure 8). Among these, the how-to-harvest attribute in agroforestry holds the highest leverage value at 3.84%, making it a crucial aspect for improvement. Effective planning and management are essential in agroforestry to maximize economic, ecological, and social benefits. With a holistic approach, agroforestry can serve as a sustainable solution for enhancing productivity while supporting land conservation and landslide mitigation efforts.

Choosing appropriate plant species and planting arrangements in agroforestry systems can generate economic advantages while contributing to climate change mitigation and adaptation efforts [4]. Vegetation has been identified as a key factor in stabilizing slopes vulnerable to landslides, with natural regrowth contributing to a significant reduction in scarp retreat. At Site 2, the retreat rate declined steadily as the accumulation zone became partially overgrown, leading to improved slope stability. This site is characterized by a large earth-slide-type landslide formed through a continuous mass movement. The landscape features a coastal escarpment shaped by landslide dynamics and shoreline abrasion. Changes in groundwater outflow primarily due to rising water levels have initiated sliding activity, resulting in a pronounced landslide cirque. The upper section of this slope failure caused notable destruction, including damage to an old cemetery [36].

Integrating seasonal crops with deep-rooted trees enhances soil stability and promotes high transpiration rates [37]. Increasing soil infiltration through integrating deep-rooted trees is an anchor to stabilize the upper soil layers. Variations in tree root distribution across different plant species in agroforestry systems can be strategically utilized to mitigate landslide risks. Mixed vegetation is one of the simplest and most effective approaches to maintaining soil binding and anchoring functions [38].

Another key attribute in the technological dimension with a significant leverage value is the question of how to maintain the crop, with a leverage value of 3.52%. The limited availability of farming equipment for land management and crop maintenance contributes to the high leverage of this attribute. Improving land management and crop maintenance technologies would enhance productivity, allowing farmers to experience more significant benefits from agroforestry. This could positively influence farmers’ motivation to sustain agroforestry practices over the long term.

The lowest leverage value in the technological dimension is associated with post-harvest processing technology, which holds a leverage value of 1.88%. While land and crop management attributes exhibit high leverage, agroforestry practitioners in Nyomplong have demonstrated relatively strong post-harvest processing capabilities, outperforming other technological attributes. The values of the technological dimension attributes are presented in Figure 8.

3.2.5. Institutional Dimension

The sustainability score for the institutional dimension is 62.82% (Table 4), suggesting that this dimension demonstrates moderate sustainability in agroforestry practices in Nyomplong. The leverage assessment for the institutional dimension identified six attributes that significantly influence the enhancement of agroforestry activities in supporting landslide mitigation strategies. The leverage values of these attributes range from 4.10% to 5.71%.

The most critical aspect to improve is the availability of consultation and assistance services, which has the highest leverage value of 5.71%. The success and sustainability of agroforestry require government involvement and institutional coordination. During on-field farming activities, government facilitators are essential, as they play a crucial role in supporting agroforestry management through needs-based planning and policy formulation aligned with farmers’ perceptions [39]. In Central Java, Indonesia, the government has supported agroforestry expansion by implementing social forestry initiatives and promoting individual land ownership to enhance community well-being [40].

The landslide in Nyomplong prompted the local government to implement a policy of evacuating residents from the landslide-affected area and providing them with permanent housing in a safer location away from landslide threats. This policy also supports the utilization of post-landslide land for agroforestry, serving as both a landslide mitigation strategy and a means to enhance community income.

The five other influential attributes in the institutional dimension include the suitability of central and regional policies related to agroforestry management, the existence of supporting regulations for agroforestry processing businesses from the government, decision-making in farmers’ group activities, the existence of financial institutions that assist in providing production capital, and the understanding and application of customary rules (Figure 9).

3.3. Monte Carlo Analysis

The Monte Carlo analysis assessed the influence of random errors by employing a scatter plot approach with 25 iterations, maintaining a 95% confidence level for each axis. The results indicate that the sustainability index values show minor variations from the MDS analysis, suggesting that the analytical process and data assessment have minimal deficiencies. Figure 10a–e present the Rap-Landslide ordination and Monte Carlo index analysis results as scatter plots for each dimension.

Table 5. Discrepancies between the Rap-Landslide ordination index and Monte Carlo results.

Dimension	Ordination (%)	Monte Carlo (%)	Variation (%)
Environmental	57.97	57.27	0.70
Social	60.82	61.22	1.60
Economic	57.97	57.26	0.73
Technology	57.97	58.82	0.95
Institutional	62.82	61.22	1.60

evaluates the Rap-Landslide ordination and Monte Carlo values. The Rap-Landslide ordination index shows no significant variation from the Monte Carlo findings. The Monte Carlo index is 57.27% for the environmental dimension, while the Rap-Landslide ordination index is 57.97%, resulting in a minor difference of 0.70%. Similarly, the differences for the other dimensions are 1.60% for social, 0.73% for economic, 0.95% for technological, and 1.60% for institutional (Table 5).

The Monte Carlo analysis confirms the stability of the sustainability assessment, as the results remain consistent within the 95% confidence interval. The minimal variation between the Monte Carlo values and the Rap-Landslide ordination index suggests a low margin of error in scoring individual attributes and a high level of accuracy in the analytical approach. These findings align with [41], who also reported a slight discrepancy between MDS sustainability indices and Monte Carlo results. This consistency indicates that scoring errors for individual attributes are relatively small, variations in assessment due to differing opinions are minimal, the repeated MDS analysis process is relatively stable, and data entry errors and data loss were effectively avoided. Based on these results, the Rap-Landslide method provides a highly reliable sustainability assessment for agroforestry in landslide-prone areas. The Rap-Landslide approach demonstrates that various characteristics provide sufficient test findings, making it a quantitative and rapid tool for assessing agroforestry sustainability practices in Nyomplong. The Rap-Landslide ordination results and Monte Carlo analysis indicate that agroforestry sustainability is experiencing disturbances, as reflected in the scattered plot distribution. A sustainability index study on milkfish aquaculture showed a similar trend, with scatter plot analysis identifying the need for specific corrective measures [42]. Likewise, agroforestry sustainability in Nyomplong still requires improvements, particularly in priority attributes.

3.4. Enhancing Agroforestry Sustainability for Landslide Mitigation and Farmer Income Improvement

Agroforestry or agrisilviculture can enhance land conservation and productivity as a landslide mitigation strategy and increase farmers’ income. The agroforestry system is an effective landslide mitigation measure due to its dense and layered tree canopy coverage, combined with deep-rooted plant species that align with the land’s characteristics. Agroforestry can enhance slope stability and mitigate landslides by strategically organizing plant strata based on forestry and agricultural layers [43].

Agroforestry is a sustainable land-use approach incorporating trees and woody perennials into farming systems by maintaining existing vegetation while actively establishing and managing new plantings [44]. Agroforestry contributes to climate change mitigation, biodiversity conservation, soil quality improvement, and enhancement in the quality of air and water [45,46]. Additionally, it supports microclimate regulation, soil fertility enhancement, agricultural productivity, and landscape resilience [47]. The combination of plant species in agroforestry has been shown to have a lower environmental impact regarding global warming, acidification, and eutrophication [48].

Landowners have utilized the post-landslide areas owned by the community in Nyomplong for planting practices that align with an agroforestry system [49]. The awareness of the Nyomplong community in terms of engaging in planting activities emerged after their region was affected by landslides. Enhancing the status and sustainability of agroforestry is crucial for improving community welfare and providing protection against landslide hazards. Agroforestry developed near human settlements can help reduce deforestation and address food security challenges [50].

According to Desmiwati et al. (2021) [51], in Parung Panjang, Indonesia, the agroforestry system contributes 15.8% to farming households, with an average annual income of IDR 16,780,000 (USD 1198.6) per farmer per year. The sustainability of agroforestry in Nyomplong can be enhanced through strategic improvements in the weaker attributes within each dimension (

Table 6. Prioritization of attributes for enhancing agroforestry sustainability in landslide mitigation and farmer income improvement in Nyomplong.

Dimension	Influential Attributes	Leverage Value (%)	Improvement Strategies
Environment	Land productivity level	3.06	○ Enhancing the selection and effectiveness of vegetation for landslide prevention. ○ Improving soil conservation through terracing, ridges to enhance infiltration, and using organic fertilizers. ○ Enhancing ecosystem quality by increasing ground cover vegetation and reducing pesticide use.
	Utilization of organic fertilizers in cultivation activities	3.06	○ Enhancing the use of organic fertilizers to support plant growth and improve soil structure.
Social	Farmer group performance	3.06	○ Enhancing farmers’ capacity and skills for sustainable agroforestry practices and education on disaster mitigation. ○ Improving access to facilities and infrastructure. ○ Optimizing marketing and market access.
	Community understanding of agroforestry conservation	3.06	○ Community-based education: training and workshops. Community empowerment and participation: involving local leaders and indigenous figures, collective action, and tangible initiatives.
	Farmer participation in farmer group	2.72	○ Enhancing farmers’ awareness and capacity. ○ Strengthening farmer group institutions. ○ Economic incentives and market access. ○ Technology and innovation in agroforestry. ○ Policies and government support.
Economy	Formal education level of community	3.84	○ Integration of agroforestry and disaster mitigation into the education curriculum. ○ Implementing agricultural literacy programs for communities that have not completed formal education. ○ Training and certification for farmers and local communities.
	Community income outside the agricultural business	3.52	○ Strategies that optimize local resources and strengthen community engagement. ○ Diversification of agroforestry-based enterprises: agrotourism and ecotourism. ○ Non-timber products: honey and essential oils. ○ Culinary businesses based on forest/garden products: tea and coffee.
Technology	How to harvest	3.84	○ Optimization of land-use planning, selection of crop combinations and appropriate cultivation techniques. ○ Enhancement of mitigation methods such as terracing and soil biotechnology.
	How to maintain the crop	3.52	○ Improving soil fertility. ○ Water and irrigation management. ○ Pest control and crop maintenance. ○ Regular evaluation. ○ Timely harvesting.
Institutional	Availability of consulting and mentoring assistance	5.71	○ Establishing a community-based network of consultants and mentors: farmer to farmer. ○ Partnerships with the private sector. ○ Engaging academics and practitioners.
	Knowledge and implementation of customary rules	4.63	○ Assisting indigenous communities in mapping customary territories and applicable regulations for forest and land management. ○ Strengthening indigenous institutions in agroforestry management.
	Existence of financial institutions that help provide production capital	4.56	○ Strengthening cooperatives and farmer groups to function as microfinance institutions that provide direct loans to agroforestry farmers. ○ Connecting farmers with large companies that require raw materials from agroforestry systems (for example: coffee, cocoa, rubber).
	Decision-making in farmer group activities	4.35	○ Enhancing farmers’ capacity and literacy by providing regular training on group management, agroforestry techniques, and sustainability strategies.
	The suitability of central and regional policies related to agroforestry management	4.33	○ Harmonizing national and regional policies. ○ Increasing the involvement of farmer groups in policy formulation. ○ Enhancing capacity building and technical assistance.
	Existence of supporting regulations for agroforestry processing businesses from the government	4.10	○ Simplifying the licensing process for agroforestry businesses, especially for farmer groups and Micro, Small, and Medium Enterprises. ○ Enhancing special agroforestry microcredit schemes with low interest rates and flexible repayment terms.

).

Leverage analysis indicates that among the 48 attributes with leverage factors ranging between 2 and 8%, 15 weaknesses are identified as priority leverage points for improvement. These 15 leverage attributes consist of 2 attributes from the environmental dimension, 3 from the social dimension, 2 from the economic dimension, 3 from the technological dimension, and 6 from the institutional dimension. Effective agroforestry adaptation requires a holistic approach that integrates environmental, social, economic, technological, and institutional factors to ensure sustainability and deliver long-term benefits to the community and the environment.

Based on this study, the institutional dimension, which consists of six attributes, significantly influences agroforestry’s sustainability. The most sensitive attribute, with the highest value of 5.71, is derived from the institutional dimension: the availability of consulting and mentoring assistance from authorities/government/research institutions. In contrast, not all attributes from the environmental, social, economic, and technological dimensions have a significant impact. The sustainability of agroforestry is strongly influenced by local government policies, as indicated by the most sensitive attribute in the institutional dimension. A lack of government support has contributed to a decline in agroforestry land in Europe, highlighting the consequences of policy neglect in this sector [52]. Although not all dimensions have a significant influence, the key attributes within each dimension remain a priority for improving the sustainability of agroforestry in Nyomplong. Strategies for enhancing these priority attributes can be implemented through the measures outlined in Table 6. Improving strategies for sensitive attributes is crucial, as it impacts farmers’ income growth, thereby ensuring the sustainability of agroforestry.

Recent developments in slope stability monitoring using Unmanned Aerial System (UAS) and Terrestrial Laser Scanning (TLS) technologies allow more precise identification of landslide-prone areas, enabling the prioritization of interventions and support for sustainable land-use strategies such as agroforestry. For example, assessing the survey results allows the identification of particular segments more prone to slope failures [53].

Despite this study being supported by a strong analytical framework, it has limitations in terms of its geographical focus, as it only covers a single case study location. As a result, the findings may not be fully generalizable to other areas with different biophysical and socio-economic conditions. In addition, temporal dynamics, such as seasonal variation and long-term climatic factors that may influence sustainability indicators, were not included in the analysis. Nevertheless, the Rap-Landslide method demonstrates strong potential for broader application. This method can be adapted and further developed for various agroforestry systems in other landslide-prone areas across Indonesia. It can serve as a decision-support tool for policymakers, practitioners, and local communities in achieving sustainable land management, particularly through agroforestry systems in the context of landslide mitigation and economic improvement.

4. Conclusions

The evaluation of the agroforestry system’s sustainability in Nyomplong indicates moderate performance across environmental (60.99%), social (58.36%), technological (57.97%), and institutional (62.82%) dimensions, with the economic dimension being notably lower (42.66%). The overall sustainability index is 56.16%, categorized as fairly sustainable. Monte Carlo analysis confirms the reliability of these findings, and the Rap-Landslide method is demonstrated to be an effective, rapid, and quantitative tool for assessing agroforestry sustainability. Leverage analysis identified 15 key attributes significantly influencing sustainability, particularly for landslide mitigation and economic improvement.

Institutional strategies should strengthen policy support, public–private collaboration, farmer literacy, technical assistance, and cooperative networks. Environmental improvements should focus on increasing land productivity and using vegetation and organic fertilizers to support landslide control and economic value. Technological interventions should emphasize land conservation techniques, optimized land use, the selection of appropriate plant combinations, and proper cultivation methods. Social strategies should foster community engagement and cooperation. At the same time, economic measures should promote education on agroforestry, disaster mitigation, and agroforestry diversification—such as agrotourism, ecotourism, and non-timber products like honey and essential oils.

These strategies reinforce the sustainability of agroforestry systems and play a direct role in mitigating landslides, conserving land, boosting agricultural productivity, and strengthening the economic stability of rural communities. The Rap-Landslide method is a practical tool for pinpointing crucial sustainability factors and informing precise, evidence-based actions in regions vulnerable to landslide disasters.