National Socio-Economic Survey Research Articles

Mapping the Digital Footprint of Women Entrepreneurs in East Java

This research objective comprehensively analyze characteristics based on East Java female entrepreneurs. The selection of East Java as the research subject stems from being the second province with the highest number of MSMEs in Indonesia. The research gap, examined descriptively and spatially, aims to provide a more comprehensive insight into the digital transformation of female entrepreneurs in East Java and its correlation with the social construction perspective through an in-depth literature review. The patterns within the relationship between female entrepreneurship and socio-cultural constructs will contribute novelty to this analytical study. The data utilized in this study are secondary and numeric, obtained through the National Socioeconomic Survey (SUSENAS) in 2022 and have been analyzed in descriptive statistics. The result revealed that from spatial analysis, it is observed that Sumenep, Pamekasan, Bojonegoro, Malang, and Jember are the regions with the highest levels of female entrepreneurship in East Java. Meanwhile, areas with the lowest levels of female entrepreneurship are the cities of Madiun, Pasuruan, Probolinggo, and Mojokerto. The high motivation of female entrepreneurs is for additional income, and they adopt digitalization strategies to optimize their operations and income. Further, there remains a noticeable credit access, usability, and digital usage divide gap among male and female entrepreneurs in East Java. Keywords: women empowerment, SMEs, digitalization, gender equality

How Microcredit Programs Improve Business Household Well-being in the Local Economy? An Impact Evaluation

Household welfare can be improved through microfinancial institutions' support by providing microcredit programs. The shock of the COVID-19 pandemic caused the impact on household welfare to decrease by 2.6% in 2020 in Bengkulu. This study aims to evaluate the impact of the People's Business Credit (KUR) program on the welfare of business households in Bengkulu Province through the National Socio-Economic Survey of the Central Bureau of Statistics (SUSENAS) for the 2022 wave using the propensity score matching (PSM) method. The study results show that microcredit influences household welfare in Bengkulu. Households receiving KUR had higher expenditures of 8.89% than groups not receiving the KUR program. In addition, age, number of households, education, savings account, marital status, and agricultural business influence KUR program recipient participation. The KUR program is expected to improve the quality of MSMEs and provide recommendations for enhancing KUR program services to related financial institutions.

Education of Cardiovascular Disease in the Elderly through Health Seminars and Health Corner

Advanced age or elderly refers to individuals who have reached the age of 60 and above. According to data from the National Socioeconomic Survey in March 2020, there is a total of 10.48%, consisting of 51.81% elderly women and 48.19% elderly men. The elderly population undergoes the aging process, making them at a higher risk of degenerative diseases. According to Basic Health Research in 2013, the most common diseases among the elderly are hypertension (57.6%), arthritis (51.9%), stroke (46.1%), dental and oral problems (19.1%), chronic obstructive pulmonary disease (8.6%), and diabetes mellitus (4.8%). Hypertension can lead to other disorders, such as cardiovascular disease. Cardiovascular diseases have a high mortality rate and can be caused by various factors, such as diabetes mellitus and obesity resulting from an unhealthy lifestyle. Therefore, through education on cardiovascular diseases and the formation of elderly cadres and health corners, efforts to prevent cardiovascular diseases in the elderly are expected to be optimally implemented. The main target of this program is the congregation of the Indonesian Christian Church (GKI) in Sepanjang Sidoarjo, Taman District, Sidoarjo Regency. Activities include pre-tests and post-tests related to cardiovascular diseases in the elderly, health seminars, and the establishment of health corners. The results of this activity show that the respondents' knowledge level, assessed through questionnaires, had an average pre-test score of 12.52 and a post-test score of 14.71, indicating a significant change with a p-value < 0.001 meeting the significant level of 95%.

Makna Generasi Sandwich Pada Film Cinta Pertama, Kedua, dan Ketiga (Analisis Semiotika Charles Sanders Peirce)

Indonesia is facing the phenomenon of the sandwich generation, which plays a dual role in the financial affairs of three generations at once. Data from the March 2022 National Socio-Economic Survey shows that 8.4 million Indonesians (62.71%) belong to the sandwich generation. The movie "First, Second, and Third Love" reflects this reality, directed by Gina S. Noer based on a true story. This study applies Charles Sanders Peirce's Semiotic method to analyze triadic signs. The research shows that individuals give meaning to societal experiences by using the Social Reality Construction Theory. The movie becomes a representation of social reality, helping to understand the complexity of the sandwich generation's life in the context of Indonesian families. To break the chain of the sandwich generation that can damage the next generation, priority awareness, implementation of life limit setting, role as an entrepreneur, and increased educational awareness are needed to change the toxic culture.

Food Insecurity and Outpatient Care Utilization Among Indonesian Older Adults.

This study aims to examine the complex relationship between household food insecurity and outpatient care utilization among Indonesian older adults. Individual-level data from the 2020 National Socioeconomic Survey (SUSENAS; n = 29 950 older adults aged 60 and over in poor self-rated health who are unable to do daily activities) and environmental-level data (n = 84 096 villages in a data aggregation across 514 municipalities) from the 2021 Village Potential Data Census Collection Survey (PODES) are used in a two-level binary logistic regression model. Older adults who live in severely food insecure households (odds ratio [OR] 1.963; CI [1.658, 2.319]) and lack of health insurance (OR 1.654; CI [1.556, 1.747]) are more likely of not utilizing outpatient care. The interclass correlation coefficient value is 0.162, indicating that primary health care services in every village improve outpatient care utilization. Food insecurity is the major determinant of reduced likelihood of outpatient care utilization, which can be explained by household resource constraints.

Sociodemographic Factors and Policy Implications for Improved Food Security

Ensuring food security is a pressing challenge facing East Kalimantan, and practical solutions are necessary. With the impending relocation of Indonesia's capital to this region, it's crucial to evaluate the area's food security in light of projected population growth and economic shifts. Prior to the new capital city project, it's essential to understand East Kalimantan's socio-economic factors to develop policies that strengthen food security for the future. This research uses logistic regression to analyze data from the Food Insecurity Experience Scale (FIES) module of the 2021 National Socio-Economic Survey (Susenas-BPS). The results show that 14.75% of households experience food insecurity, while 85.25% maintain food security. Factors such as education, family size, land ownership, marital status, employment, residence, and retirement security influence food security status significantly. However, age, gender, and home ownership have little impact. Notably, agricultural workers are more likely to experience food insecurity, while education and land ownership correlate with higher food security. Additionally, larger families are more vulnerable to food insecurity.

Determinants of Household Extreme Poverty Among Female-Headed Households in Indonesia: Does Disability Matter?

ABSTRACT This paper investigates factors contributing to extreme poverty among female-headed households in Indonesia, with a specific focus on the impact of disabilities. Analyzing data from the 2021 National Socio-Economic Survey, this research combined both principal component and path analysis to uncover the link between poverty dimensions (isolation, physical weakness, powerlessness, and vulnerability) and extreme poverty. The study revealed that various dimensions influence extreme poverty, and the presence of disabilities within a household exacerbates the risk of extreme poverty and can alter the significance of initially insignificant variables. These findings underscore the critical role of disabilities in shaping extreme poverty outcomes.

The Role of Root and Tuber Crops on Food Diversification Facing the Climate Change in East Java Indonesia

Root and tuber crops consisting of cassava, sweet potato, potato, taro and others root and tubers have the important roles as the source of food, nutrition and cash income for many farmers in Indonesia. These crops also as a source of carbohydrates beside rice, corn, cereals, wheat etc. Root and tuber crops are the second most important group of crop plants after the cereals. The government of Indonesia accelerate food diversification based on local food resources, especially facing the climate change. The objective of this study was to estimate the role of root and tuber crops on food diversification and to estimate the household root and tuber crops demand in East Java Indonesia. The research used SUSENAS (Indonesian National Socio-Economic Survey) 2020 data with 31.990 household respondents in East Java Indonesia. Demand for food was estimated by AIDS (Almost Ideal Demand System) model. The results show that the average consumption for root and tuber crops was 0,69 kg/household/week (11,23% from carbohydrates foods), whereas rice consumption amount 4,86 kg/household/week (79,68 %), maize amount 0,25 kg/household/week (4,13%) and cereals amount 0,3 kg/household/week (4,96%). The expenditure elasticity of root and tuber crops was 1,36, while the expenditure elasticity of rice amount 0,78 (normal food), maize (1,41) and cereals (1,27). The expenditure elasticity more than 1 means that root and tuber crops as a superior food, also for maize and cereals. People no longer considers that root and tuber crops to be an inferior food. The root and tuber crops consumptions have the highest proportion after rice. It can be mean that root and tuber crops have the important role on food diversification in East Java Indonesia. Facing the climate change, root and tuber crops development be a right decision, moreover, root and tuber crops can be planted on dry land which is still widely available in Indonesia.

Influence of Environmental Risks on the Feasibility of Household Sanitation in Purworejo Regency, Central Java Analysis of Geographic Location, Income, and Education Level

This study examines the factors that influence the feasibility of household sanitation in Purworejo Regency, Central Java. The research utilizes survey data from Indonesia's National Socio-Economic Survey (SUSENAS) that includes 785 households in Purworejo Regency from March 2022. The results reveal that 23.3% of households in the region do not have suitable sanitation facilities. The findings show that location, particularly in rural areas, income level, and the level of education attained by the household head significantly impact the availability of appropriate sanitation. Households located in rural zones and those with lower incomes or heads of household with lower education levels are at greater risk of lacking suitable sanitation. The conclusions suggest that improvements to income and education, as well as infrastructure development in rural settings, can help boost access to appropriate sanitation.

Social Demographic Dimensions of Contraceptive Use in the Land of Papua: A Cross-Sectional Approach

Background: The use of contraception is one of the efforts to prevent unwanted or mistimed pregnancies. Therefore, it has become a family planning program for motivating families to have ideal plans for pregnancies in time and with a desired number. However, although nationally, 58.7% of married women aged 15-49 years old used contraception in 2019, the percentage of contraceptive users remained the lowest in Papua, with only 13.7% of married women of the same age group using contraceptives in addition to 20% of the women having the unmet need for contraception. This study aims to analyze the determinants of the use of contraception in women of childbearing age in Papua Province.Method: This study employed data from the 2020 National Socioeconomic Survey (Susenas) with a cross-sectional approach. Respondents were 666,866 married women aged 10-54 years. Descriptive statistics and logistic regression analysis were performed using SPSS with a 95% confidence interval (p < 0.05) to express statistical significance.Results: Residence, educational status, pregnancy, employment, age at first marriage, number of children, cell phone ownership, and health insurance were significantly correlated with contraceptive use (p < 0.001). Residence in an urban area, junior high school education, pregnancy, marriage at less than 20 years of age, having more than two children alive, and ownership of a cell phone and health insurance were associated with an increased chance of using contraceptive methods among married women of reproductive age in Papua. The chance to use contraception was the highest for married pregnant women of reproductive age, and the women, in this case, were 35 times more likely to use contraceptives compared to unpregnant ones.

Regional disparity in age-related disability: toward healthy aging in Indonesia

Purpose: Maintaining functional ability and minimizing age-related disability of older adults are required to promote healthy aging. A supportive physical and social environment, in addition to individual variables, has a role in reducing the risk of age-related disability. Infrastructure development differs between Java-Bali and outer Java-Bali regions. This study aims to determine the extent to which the disability of older adults in Java-Bali and outer Java-Bali regions. 
 Methods: This study is cross-sectional, using data from the 2020 National Socio-Economic Survey (SUSENAS) with 122.344 Indonesian older adults aged 60 and over. Disability is the outcome variable. The explanatory variable is regional disparity (Java-Bali and outer Java-Bali regions), which refers to where the older adults live. In addition, the control variables include age, sex, marital status, educational level, employment status, leisure activity, household wealth status, and self-rated health status (SRHS). A multivariate logistic regression statistical analysis is performed. 
 Results: The outer Java-Bali region has a slightly greater prevalence of older adults with age-related disability than the Java-Bali region, with 28.8 and 22.9 percent, respectively. However, older adults living in the outer Java-Bali region are 1.63 times more likely (OR 1.63; 95% CI (1.58-1.68)) to have disability than those living in the Java-Bali region. Other socio-demographic variables are significantly associated with age-related disability. 
 Conclusion: Living in the Java-Bali region increases the risk of age-related disability. Infrastructure development in the outer Java-Bali region needs to be improved so that older adults can experience healthy aging.

Could the minimum wage policy reduce food insecurity among households of formal workers in Indonesia?

BackgroundPrevious studies have concluded that minimum wages increase workers' wages. However, whether this effect will continue to improve households' food insecurity is an interesting question, especially in Indonesia, where food insecurity is still a public policy challenge. This study explores the ongoing impact of minimum wages on household food insecurity in Indonesia, leveraging data from the National Socioeconomic Survey (2017–2019) and provincial-level variations in minimum wages. The study employs unconditional quantile regression to provide nuanced insights by analyzing three food insecurity indicators: per capita calorie intake, per capita consumption of vegetables and fruits, and food diversity. We also investigate potential mechanisms driving the link between the minimum wage and food insecurity.ResultsThe study revealed that the real minimum wage reduced food insecurity, especially at specific distribution points. Significantly, the effect on per capita calorie intake was observed in lower deciles. The impact on dietary diversity was observed up to the seventh decile. However, the minimum wage increase did not significantly improve the consumption of nutritious foods like fruits and vegetables, except for the top deciles. The study confirmed that the minimum wage's impact on food insecurity operated through wage increases, particularly in the bottom-to-median wage distribution within the manufacturing sector.ConclusionsThe study concluded that the minimum wage policy ameliorated household food insecurity indicators in specific distribution segments. Our results support the effectiveness of government policies in increasing the minimum wage as a viable approach to mitigating food insecurity among formal worker households, especially within the manufacturing sector. However, additional policies targeting the lower end of the per capita calorie intake distribution are necessary, as the minimum wage was recognized to have no impact on this group.

THE DETERMINANTS OF REPRODUCTIVE HEALTH CARE BEHAVIOR IN ADOLESCENT: A CROSS-SECTIONAL STUDY

Background: The quality of reproductive health during adolescence determines the quality of reproductive health in adulthood. The 2018 National Socioeconomic Survey found that 11% of adolescents were married before the age of 18, and 0.56% were married before the age of 15. Adolescent reproductive health issues continue to increase every year. Purpose: The study aims to analyze the determinants of reproductive health care (RHC) behavior in adolescents. Methods: This study is an analytic observational research using a cross-sectional design. The research was conducted at SMPN 20 Kupang City in 2022. The sample size are 82 students selected using a random sampling technique. The research variables are the characteristics of respondents, health literacy, parental support, teacher support, perceived vulnerability, seriousness, benefits, barriers, cue to act and RHC behavior. Bivariate data analysis used chi-square, and multivariate data analysis used logistic binary regression. Results: The results show that 57% of the respondents have a deficient reproductive health care behavior. The most dominant variable influencing RHC behavior was living with parents (PR= 4.86; CI= 1.22-19.27). Adolescents who live with their parents are 4.86 times more likely to do RHC compared to adolescents who do not live with their parents. Conclusion: These findings recommend the importance of optimizing the role of parents as peers in providing RHC education for adolescents. Parents who do not live with their children have to pay attention and remind their children to keep doing RHC.

Exploring the determinants of energy poverty in Indonesia’s households: empirical evidence from the 2015–2019 SUSENAS

This study explores the determinants of household-level energy poverty in Indonesia by using highly granular, household-level socioeconomic data on Indonesia from the 2015–2019 National Socioeconomic Survey (SUSENAS). This study utilizes two distinct methods to assess energy poverty in Indonesia with regard to accessibility, aiming to gain a more comprehensive understanding of the issue. Using logistic regression with the combination of district-level fixed effects and interactions between regional and yearly terms, this study finds that, in general, the likelihood of a household being under energy poverty is negatively associated with household expenditure, dwelling size, family size, full-time employment status, and the marital status and educational attainment of the household head, while the associations with other determinants, such as the gender of the household head and LPG and electricity prices, are positive. These associations between the incidence of energy poverty and households’ socioeconomic and demographic variables, as well as the prices of modern and alternative energy, are in parallel with the findings from other similar studies that have been conducted in other developing countries or regions. Furthermore, this study finds some substantial variations in the estimation results for Java and outside Java.

Factors Associated with Expenditure on Animal Protein among Indonesian Households

Background: Eating animal protein (AP) can prevent stunting in children under five, which currently is still 21.5%. Due to scarce resources, households had trouble distributing the cost and frequently had to choose between it and other food expenses. Objectives: This study aimed to examine the relationship between various food expenditures and expenditure on AP among Indonesian households. Methods: This was a cross-sectional study using secondary data. Data on household food expenditures on AP, prepared food and beverage, cereals, instant noodles, fruits, cooking oil, cigarette, and sugar, total expenditure, household size, and age and education of household head from 97,467 household samples with children under five were obtained from the National Socioeconomic Survey (Susenas) March 2018. Susenas data were collected through interviews using a structured questionnaire. Using IBM SPSS Version 22, a multiple linear regression was carried out, adjusted for household socioeconomic factors. Results: The average per-capita household expenditure on AP was IDR 24,912, contributing 4.72% to total food expenditure. This expenditure was higher than that on cereals (3.77%) but lower than that on prepared foods and beverages (6.15%). There was a positive association (p<0.001) between fruits, instant noodles, cooking oil, sugar, and beans and nuts expenditure and AP expenditure. Contrarily, there was an inverse relationship between prepared food and beverage (p<0.001), cereals (p=0.004), and cigarette expenditure (p<0.001) and animal protein expenditure. Conclusions: The amount spent on animal proteins was positively correlated with other food. It is possible that the consumption of animal proteins would increase if household funds were diverted from cigarettes and prepared food and beverage.

Efektivitas Program Indonesia Pintar terhadap Partisipasi Sekolah di Kawasan Barat dan Timur Indonesia

Smart Indonesia Program (PIP) is a government program that aims to make the 12-year compulsory education program a success. The PIP program has been running since 2015. However, the Badan Pusat Statistik (BPS) notes that there are still school-age residents who are not attending school, even though the percentage of children not attending school has decreased. This study aims to measure the implementation of PIP and other factors on school participation in two regions, namely the West Indonesia Region (KBI) and the East Indonesia Region (KTI) in 2021. This research uses data from the 2021 National Socio-Economic Survey (Susenas) in the Indonesian Region West (KBI) and Eastern Indonesia Region (KTI). Data analysis used logistic regression method. The results showed that all independent variables, PIP, gender, marital status of head of household, classification of area of residence, per capita expenditure, other social assistance had a significant effect on school enrollment in the Western Regions of Indonesia (KBI) and Eastern Indonesia (KTI). . The biggest tendency for children to participate in school is the PIP.

Do Food Price Subsidies Increase Nutritional Intake of Indonesian Households?

Indonesia's economy has developed rapidly, but it has not solved undernourishment issues among low-income people. Therefore, similar to other developing countries, Indonesia has instituted a food price subsidy program known as Rice for the Poor (RASKIN) to help low-income families meet their needs and alleviate some of their financial burdens. This study examined how RASKIN affected the intake of calories and three macronutrients of Indonesian households using the representative National Socioeconomic Survey (SUSENAS) data. In comparison to intake without the subsidy, the estimation results based on the endogenous switching regression model suggested that receiving the subsidy raised the household calorie intake by 368.4 Kcal/day for recipients and 454.6 Kcal/day for nonrecipients. Likewise, households receiving the subsidy raised their macronutrient intake, encompassing protein, carbohydrate, and fat, compared to those not receiving it. Therefore, RASKIN contributed to raising the intake of calories and three macronutrients. However, a certain portion of non-poor households were found to receive RASKIN owing to mistargeting, suggesting that the government should rectify targeting errors to enhance the effectiveness of the subsidy and attain the key purpose of improving the well-being of people with low incomes.

Geospatial Big Data Approaches to Estimate Granular Level Poverty Distribution in East Java, Indonesia using Machine Learning and Deep Learning Regressions

One of the economic development the focus of the Indonesian government's efforts is for reducing poverty. In Indonesia, collecting poverty data uses the conventional method, the name is National Socio-Economic Survey (SUSENAS) which takes a large cost, time, and effort. To overcome these limitations, there is a need for additional data to provide more detailed poverty data. Recent studies show that the use of geospatial big data could identify poverty at a granular level, with a lower cost and faster update because of their unique and unbiased capacity to identify physical and socioeconomic phenomena. The integrated multi-source satellite imagery data such as the normalized difference vegetation index (NDVI) for detecting rural areas based on vegetation, built-up index (BUI) for identifying urban areas through building distribution, normalized difference water index (NDWI) for land cover detection, day time land surface temperature (LST) for identifying urban regions based on surface temperature, and pollutants such as carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) to evaluate economic activities based on pollution. Additionally, point of interest (POI) density and minimum POI distance are used to measure area accessibility. Therefore, the contribution of this research is to implement the utilization of geospatial big data to estimate the numbers of poverties at a granular level to the 666 sub-districts in East Java Province using machine learning and deep learning regression models. The evaluation results to estimate sub-district level poverty shows that the best model development using Support Vector Regression (SVR) in machine learning was the best root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) values of 0.365, 0.293, and 0.032 with R-squared of 0.59 and MLP in deep learning algorithm with 0.444, 0.345, and 0.039 values of RMSE, MAE, and MAPE with R2 0.52. In addition, the results of visual identification revealed that high estimates of lower poverty are typically found in urban areas with high accessibility, and these areas are not spatially deprived areas with limited accessibility.

Integrating Satellite Imageries and Multiple Geospatial Big Data for Granular Mapping of Spatial Distribution of Human Development Index in East Java, Indonesia

The availability of data on the Human Development Index (HDI) is crucial as a gauge of regional performance, particularly in terms of assessing the development of human resources. In Indonesia, the collecting of HDI data usesthe conventional method, such as undirect estimation, National Socio-Economic Survey (SUSENAS), The Ministry of Religion, or inventory of sectoral data that used the large cost, time, and effort. Additional data are required to provide more detailed poverty data at a lower cost and with more recent information to overcome these limitations. According to recent studies, the quality of life for measuring HDI can be identified down to the granular level using geospatial big data. Therefore, the contribution of this research is to implement the use of geospatial big data, such as integrated multi-source satellite imagery data and Point of Interest (POI). Besides that, this study develops the relative spatial human development index in 11 km x 11 km resolution for the granular mapping of the quality of life to measure the HDI in East Java, Indonesia. The kinds of weighted sum models used in this study such as equal weight (EWS), Pearson (PCCWS), Spearman (SCCWS) correlation-based weight, and Principal Component Analysis (PCA)-based weight (PCAWS). The best RSHDI PCCWS for representing the human development index in East Java in 2022, which was determined using a weight-sum model based on Pearson correlation, has a correlation coefficient of 0.7858 (p-value = 5.078 x 10-9) and is highly correlated with official HDI data. The use of this RSHDI as a predictor variable in the estimation of HDI data shows the ideal model had an RMSE of 3.098% and an R2 of up to 61.75% using RSHDI PCCWS. According to the findings of the descriptive analysis of this map, areas with low RSHDI scores typically in some regencies areas in Madura Island and the east area of East Java with geographically depressed, while areas with high RSHDI scores typically have dense populations and have better accessibility such as urban area in Surabaya and Kota Malang. As a result, the official human development index data can be supported by the RSHDI's ability to map spatially deprive areas

Small Area Estimation of Multidimensional Poverty in East Java Province Using Satellite Imagery

The government has so far focused on a monetary approach to overcoming poverty, while poverty is multidimensional. Holistic and accurate poverty indicators are needed as material for policy formulation, such as the Multidimensional Poverty Index (IKM), which is calculated from raw data from the National Socioeconomic Survey (SUSENAS). However, the direct estimation of the multidimensional poverty headcount (AKM) is only accurate at the provincial level, as seen from the relative standard error (RSE) of several districts and cities, which is still above 25 percent. Increasing the sample size requires time, effort, and cost, so the Small Area Estimation (SAE) method can be an alternative. Apart from using official statistics for accompanying variables, satellite imagery has the advantage of being up-to-date and available up to a granular level. This study aims to estimate the AKM at the district/city level in East Java Province by utilizing satellite imagery and official statistics in SAE. The results showed that SAE HB Beta-logistics, with the accompanying variables combined with satellite imagery and official statistics, has a higher accuracy than direct estimation.