Search Results (11)

Background/Objective: This study explores the epidemiology and clinical features of re-emerging mpox in Jakarta, Indonesia. Methods: This study used a retrospective study design to describe the epidemiological data, clinical features, and mortality of mpox patients from August 2022 to December 2023. In addition, this study also aims to identify the differences in both the epidemiology and clinical features of mpox in people living with HIV (PLHIV) and in non-HIV patients (non-PLHIV). Results: Our study shows that, as of the end of December 2023, 59 mpox cases were treated in Jakarta. All of the mpox cases in Jakarta were diagnosed in males, mainly found in MSM (91.5%), and PLHIV (78%). Most patients would manifest with fever, rash, and skin lesions. Syphilis was found as a concomitant infection in this group (22/59, 37.2%). Severe manifestations were found among PLHIV without antiretroviral therapy (ART). Conclusions: Mpox cases in Jakarta were all found in males and most of them were PLHIV. There are various manifestations of mpox; however, since immunosuppressed patients could present differently, a strong surveillance and vaccine notification system, cautious management, and spreading vaccination awareness are needed to prevent and treat mpox. Full article

Privatization, often proposed as a means to regulate natural resource use, sometimes paradoxically leads to overexploitation and social exclusion. Within the unique context of Ogan Komering Ilir (OKI) Regency, Indonesia, the privatization of swamp floodplains and rivers via the “Lelang Lebak, Lebung, Sungai” (L3S) system is a testament to this dilemma. L3S grants auction winners exclusive rights to fish, thereby privatizing common-pool resources. This study delves into the intricacies of the L3S mechanism, highlighting its significance in guiding inland fisheries’ management. Through stakeholder analysis, we pinpoint the crucial actors, as well as their interests, influence, and interrelationships. Our investigation revealed 20 distinct stakeholders, each playing different roles within the L3S framework. Based on their influence and vested interests, these stakeholders are categorized as key players, subjects, context setters, and crowds. This classification aids in discerning potential conflicts, cooperation, and synergies. Effective L3S execution hinges on collaboration, especially with pivotal entities such as fishery services, village and district heads, and village-owned enterprises. Insights gathered during the study indicate that while privatization has streamlined resource distribution, it intensifies overfishing and deepens socioeconomic divisions. This study calls for a harmonious blend of historical insights and modern governance, with a central focus on stakeholder collaboration and community involvement. Full article

The issue of poor local government capacity has been considered one of the problems impeding the implementation of decentralization, especially in developing countries. This study addresses this issue in the case of Indonesia, a country that has implemented massive decentralization (administrative, fiscal, and political) over the last two decades. The study aims to provide empirical evidence for the impact of local government capacity on public service delivery in the decentralization regime. Local government capacity is measured based on a policy capacity framework at the organizational level that includes three types of capacities: analytical, operational, and political. The regression of the panel data model, estimated with the Hausman–Taylor method, reveals that government capacity in terms of interactions of three types of capacities has a positive impact on public service delivery. This finding indicates the three types of capacities are complementary and effectively improve local government’s achievement in delivering public services. While operational capacity (including fiscal capacity) has long been reckoned in designing decentralization, this result gives empirical evidence that other critical capacities should be well considered, political and analytical capacities. It underpins the efforts to internalize local government capacity in designing and implementing decentralization programs. Full article

This study provides empirical evidence of the effect of human capital on innovation in young entrepreneurs’ SMEs. Furthermore, this study also examines the role of social media networking and knowledge sharing, as a mediating variable, on the effect of human capital on open innovation. The current study employs the survey method to collect data. The respondents of this study are 438 young entrepreneurs who attended incubators by universities in Central Java and Yogyakarta, Indonesia. Data analysis techniques include using Structural Equation Modeling (SEM) with AMOS software. The result shows that human capital, knowledge sharing, and social media networking directly affect innovation. Social media networking and knowledge sharing partially mediate the effect of human capital on innovation. Full article

Irrigation and fertilization technologies need to be adapted to climate change and provided as effectively and efficiently as possible. The current study proposed pocket fertigation, an innovative new idea in providing irrigation water and fertilization by using a porous material in the form of a ring/disc inserted surrounding the plant’s roots as an irrigation emitter equipped with a “pocket”/bag for storing fertilizer. The objective was to evaluate the functional design of pocket fertigation in the specific micro-climate inside the screenhouse with a combination of emitter designs and irrigation rates. The technology was implemented on an experimental field at a lab-scale melon (Cucumis melo L.) cultivation from 23 August to 25 October 2021 in one planting season. The technology was tested at six treatments of a combination of three emitter designs and two irrigation rates. The emitter design consisted of an emitter with textile coating (PT), without coating (PW), and without emitter as a control (PC). Irrigation rates were supplied at one times the evaporation rate (E) and 1.2 times the evaporation rate (1.2E). The pocket fertigation was well implemented in a combination of emitter designs and irrigation rates (PT-E, PW-E, PT-1.2E, and PW-1.2E). The proposed technology increased the averages of fruit weight and water productivity by 6.20 and 7.88%, respectively, compared to the control (PC-E and PC-1.2E). Meanwhile, the optimum emitter design of pocket fertigation was without coating (PW). It increased by 13.36% of fruit weight and 14.71% of water productivity. Thus, pocket fertigation has good prospects in the future. For further planning, the proposed technology should be implemented at the field scale. Full article

In recent decades, catastrophic wildfire episodes within the Sumatran peatland have contributed to a large amount of greenhouse gas emissions. The El-Nino Southern Oscillation (ENSO) modulates the occurrence of fires in Indonesia through prolonged hydrological drought. Thus, assessing peatland vulnerability to fires and understanding the underlying drivers are essential to developing adaptation and mitigation strategies for peatland. Here, we quantify the vulnerability of Sumatran peat to fires under various ENSO conditions (i.e., El-Nino, La-Nina, and Normal phases) using correlative modelling approaches. This study used climatic (i.e., annual precipitation, SPI, and KBDI), biophysical (i.e., below-ground biomass, elevation, slope, and NBR), and proxies to anthropogenic disturbance variables (i.e., access to road, access to forests, access to cities, human modification, and human population) to assess fire vulnerability within Sumatran peatlands. We created an ensemble model based on various machine learning approaches (i.e., random forest, support vector machine, maximum entropy, and boosted regression tree). We found that the ensemble model performed better compared to a single algorithm for depicting fire vulnerability within Sumatran peatlands. The NBR highly contributed to the vulnerability of peatland to fire in Sumatra in all ENSO phases, followed by the anthropogenic variables. We found that the high to very-high peat vulnerability to fire increases during El-Nino conditions with variations in its spatial patterns occurring under different ENSO phases. This study provides spatially explicit information to support the management of peat fires, which will be particularly useful for identifying peatland restoration priorities based on peatland vulnerability to fire maps. Our findings highlight Riau’s peatland as being the area most prone to fires area on Sumatra Island. Therefore, the groundwater level within this area should be intensively monitored to prevent peatland fires. In addition, conserving intact forests within peatland through the moratorium strategy and restoring the degraded peatland ecosystem through canal blocking is also crucial to coping with global climate change. Full article

Evapotranspirative irrigation is a simple idea in a watering field based on the actual evapotranspiration rate, by operating an automatic floating valve in the inlet without electric power to manage water levels. The current study introduces a model of evapotranspirative irrigation and its application under different water levels. The objectives were (1) to evaluate the performances of evapotranspirative irrigation under various irrigation regimes, and to (2) to observe crop and water productivities of the system of rice intensification (SRI) as affected by different types of irrigation. The experiment was performed during one rice planting season, starting from July to November 2020, with three irrigation regimes, i.e., continuous flooded (CFI), moderate flooded (MFI) and water-saving irrigation (WSI). Good performance of the system was achieved; low root mean square error (RMSE) was indicated between observed water level and the set point in all irrigation regimes. Developing a better drainage system can improve the system. Among the regimes, the WSI regime was most effective in water use. It was able to increase water productivity by up to 14.5% while maintaining the crop yield. In addition, it has the highest water-use efficiency index. The index was 34% and 52% higher than those of the MFI and CFI regimes, respectively. Accordingly, the evapotranspirative irrigation was effective in controlling various water levels, and we recommend the system implemented at the field levels. Full article

A simple model for predicting Coronavirus Disease 2019 (COVID-19) epidemic is presented in this study. The prediction model is presented based on the classic Susceptible-Infectious-Recovered (SIR) model, which has been widely used to describe the epidemic time evolution of infectious diseases. The original version of the Kermack and McKendrick model is used in this study. This included the daily rates of infection spread by infected individuals when these individuals interact with a susceptible population, which is denoted by the parameter β, while the recovery rates to determine the number of recovered individuals is expressed by the parameter γ. The parameters estimation of the three-compartment SIR model is determined through using a mathematical sequential reduction process from the logistic growth model equation. As the parameters are the basic characteristics of epidemic time evolution, the model is always tested and applied to the latest actual data of confirmed COVID-19 cases. It seems that this simple model is still reliable enough to describe the dynamics of the COVID-19 epidemic, not only qualitatively but also quantitatively with a high degree of correlation between actual data and prediction results. Therefore, it is possible to apply this model to predict cases of COVID-19 in several countries. In addition, the parameter characteristics of the classic SIR model can provide information on how these parameters reflect the efforts by each country to prevent the spread of the COVID-19 outbreak. This is clearly seen from the changes of the parameters shown by the classic SIR model. Full article

The COVID-19 pandemic was impacting the health and economy around the world. All countries have taken measures to control the spread of the epidemic. Because it is not known when the epidemic will end in several countries, then the prediction of the COVID-19 pandemic is a very important challenge. This study has predicted the temporal evolution of the COVID-19 pandemic in several countries using the logistic growth model. This model has analyzed several countries to describe the epidemic situation of these countries. The time interval of the actual data used as a comparison with the prediction results of this model was starting in the firstly confirmed COVID-19 cases to December 2020. This study examined an approach to the complexity spread of the COVID-19 pandemic using the logistic growth model formed from an ordinary differential equation. This model described the time-dependent population growth rate characterized by the three parameters of the analytical solution. The non-linear least-squares method was used to estimate the three parameters. These parameters described the rate growth constant of infected cases and the total number of confirmed cases in the final phase of the epidemic. This model is applied to the spread of the COVID-19 pandemic in several countries. The prediction results show the spread dynamics of COVID-19 infected cases which are characterized by time-dependent dynamics. In this study, the proposed model provides estimates for the model parameters that are good for predicting the COVID-19 pandemic because they correspond to actual data for all analyzed countries. It is based on the coefficient of determination, R², and the R² value of more than 95% which is obtained from the non-linear curves for all analyzed countries. It shows that this model has the potential to contribute to better public health policy-making in the prevention of the COVID-19 pandemic. Full article

Subsurface drainage technology may offer a useful option in improving crop productivity by preventing water-logging in poor drainage paddy fields. The present study compared two paddy fields with and without sheet-pipe type subsurface drainage on land and water productivities in Indonesia. Sheet-pipe typed is perforated plastic sheets with a hole diameter of 2 mm and made from high-density polyethylene. It is commonly installed 30–50 cm below the soil surface and placed horizontally by a machine called a mole drainer, and then the sheets will automatically be a capillary pipe. Two fields were prepared, i.e., the sheet-pipe typed field (SP field) and the non-sheet-pipe typed field (NSP field) with three rice varieties (Situ Bagendit, Inpari 6 Jete, and Inpari 43 Agritan). In both fields, weather parameters and water depth were measured by the automatic weather stations, soil moisture sensors and water level sensors. During one season, the SP field drained approximately 45% more water compared to the NSP field. Thus, it caused increasing in soil aeration and producing a more significant grain yield, particularly for Inpari 43 Agritan. The SP field produced a 5.77 ton/ha grain yield, while the NSP field was 5.09 ton/ha. By producing more grain yield, the SP field was more effective in water use as represented by higher water productivity by 20%. The results indicated that the sheet-pipe type system developed better soil aeration that provides better soil conditions for rice. Full article

More than 50% of the world’s population consumes rice. Accurate and up-to-date information on rice field extent is important to help manage food and water security. Currently, field surveys or MODIS satellite data are used to estimate rice growing areas. This study presents a cost-effective methodology for near-real-time mapping and monitoring of rice growth extent and cropping patterns over a large area. This novel method produces high-resolution monthly maps (10 m resolution) of rice growing areas, as well as rice growth stages. The method integrates temporal Sentinel-1 data and rice phenological parameters with the Google Earth Engine (GEE) cloud-based platform. It uses monthly median time series of Sentinel-1 at VH polarization from September 2016 to October 2018. The two study areas are the northern region of West Java, Indonesia (0.75 million ha), and the Kedah and Perlis states in Malaysia (over 1 million ha). K-means clustering, hierarchical cluster analysis (HCA), and a visual interpretation of VH polarization time series profiles are used to generate rice extent, cropping patterns, and spatiotemporal distribution of growth stages. To automate the process, four supervised classification methods (support vector machine (SVM), artificial neural networks (ANN), random forests, and C5.0 classification models) were independently trialled to identify cluster labels. The results from each classification method were compared. The method can also forecast rice extent for up to two months. The VH polarization data can identify four growth stages of rice—T&P: tillage and planting (30 days); V: vegetative-1 and 2 (60 days); R: reproductive (30 days); M: maturity (30 days). Compared to field survey data, this method measures overall rice extent with an accuracy of 96.5% and a kappa coefficient of 0.92. SVM and ANN show better performance than random forest and C5.0 models. This simple and robust method could be rolled out across Southeast Asia, and could be used as an alternative to time-consuming, expensive field surveys. Full article