BPS-Statistics Indonesia Research Articles

Measuring Well-Being Index with Environmental in Mind: Evidence Forest Land Use in Indonesia

This project aims to create an objective composite wellbeing index from the point of view of the whole by using a complete welfare methodology and suggested weightings to take into account the differences between the components. Forestry total productivity (TFP) was also compared because of the importance of the environmental component in preparing the well-being index. This study examined 64 social, economic, environmental, and institutional indicators from the BPS-Statistics Indonesia, the Ministry of Environment and Forestry, and the National Disaster Management Agency. Three primary analysis elements were highlighted in this investigation. First, PCA created a weighted index of eleven important domains. Second, it creates a well-being index model for Indonesia's environmental sustainability. Third, comparing forestry's environmental dimension to its TFP. This study found that the Indonesian wellbeing model under construction weighs environmental quality, living conditions, including housing, and happiness. Indonesia's disaster-prone locations make environmental quality important, unlike other wellbeing indices. Forest degradation has decreased the composite wellbeing index, notwithstanding other socio-economic improvements. This study stands out from past research by being the first to compare the environmental dimension with forestry total factor productivity (TFP). Deforestation significantly affects the well-being index in Indonesia.

DETERMINANTS MODELING OF UNDERNUTRITION IN TODDLERS IN ACEH PROVINCE: A PLS-SEM APPROACH

This study examines the escalating prevalence of underweight and wasting in Indonesia from 2019 to 2022. The prevalence of underweight has increased from 16.35% in 2019 to 17.1% in 2022 while wasting has increased from 7.4% to 7.7% during the same period. Aceh province faces a pressing issue of toddler malnutrition, ranking second with the highest prevalence of underweight (24.8%) and fourth highest in wasting prevalence (11.3%). According to the World Health Organization's malnutrition indicators classification, Aceh experiences notably high levels of underweight and very high levels of wasting. Employing Partial Least Squares Structural Equation Modeling (PLS-SEM) with data sourced from SSGI, publications from the Ministry of Health and BPS-Statistics Indonesia, and Aceh Provincial Food Agency, this research aims to model undernutritioned toddlers in Aceh Province. Findings reveal that undernutrition is directly affected by health access and food intake, with socioeconomic factors exerting an indirect effect. Notably, food intake emerges as the primary determinant of undernutrition.

The Effect of E-Commerce on Gross Regional Domestic Product and Clustering of Its Characteristics by Utilizing Official Statistics and Big Data

The objective of this study is to examine the impact of e-commerce on Gross Regional Domestic Product (GRDP) and categorize GRDP according to e-commerce features in 17 provinces throughout Java, Sumatra, and Bali. The Human Development Index (HDI), which measures people's proficiency with technology—among which is e-commerce—is greatest on these three islands. This study makes use of big data in the form of Google Trends data as well as official statistics data obtained from the BPS-Statistics Indonesia. K-means clustering and regression analysis are the research methods employed. The study's findings demonstrate that the three islands' GDP growth rates are considerably accelerated by e-commerce companies. There were two ideal clusters identified: the low and high GRDP clusters. All of the provinces on the island of Java are included in the high cluster, with the exception of Central Java, which is distinguished by high transaction values and e-commerce-related keyword searches. Provinces in the low cluster are located on the Indonesian islands of Sumatra and Bali, and they are distinguished by the usage of Cash on Delivery (COD) and a limited number of employees in e-commerce businesses.

Measuring the Urban Metropolitanization of Kedungsepur Based on Polycentricity and Spatial Transformation

Kedungsepur, situated in Central Java Province, Indonesia, encompasses the regions of Kendal, Demak, Ungaran, Semarang, Salatiga, and Purwodadi, making it a strategically significant area. Its designation as a metropolitan area was established by Presidential Decree Number 78 of 2017, with one of its primary objectives being to promote equity by reducing urban primacy. This study seeks to assess the metropolitanization of Kedungsepur from 2016 to 2020, focusing on two key indicators: polycentricity and spatial transformation. Polycentricity is evaluated based on concentration, accessibility, and connectivity, while spatial transformation is measured by analyzing the percentage of built-up land and urban level. Polycentricity is assessed using secondary data from BPS-Statistics Indonesia, while the percentage of built-up land and urban level are determined through the interpretation of Sentinel 2A satellite imagery from 2016 and 2020. The findings indicate a moderate improvement in polycentricity during the aforementioned period, with partial spatial transformation occurring, particularly along highway corridors between cities. In conclusion, the process of metropolitanization demonstrates positive progress toward its objectives, albeit requiring more balanced control over spatial transformation processes.

Prospective Peri-Urban Areas Around the New Capital City of Nusantara, Indonesia: Sustainable Development and New Urban Agenda Perspectives

In 2022, the Indonesian Parliament passed the historical new capital city bill, commencing the relocation of the country’s capital from Jakarta to Nusantara in Kalimantan Timur. This relocation has been predicted to impact the surrounding areas by, for instance, triggering (peri-)urbanization. This research aimed to analyze the locations and roles of peri-urban areas and discuss the processes that drive their emergence and development in the context of the New Urban Agenda. For this purpose, potential peri-urban areas were determined by examining three spatial elements: the development level, accessibility, and position of a village (administrative unit) relative to the capital. Supporting primary data were acquired through a field survey, and secondary data were obtained from the Village Potential Statistics (PODES) from BPS-Statistics Indonesia. Results show that the identified potential peri-urban areas had the following characteristics: (1) situated within the new capital’s development zone, (2) directly adjacent to the capital, (3) having a high level of development and adequate access to the capital, and (4) currently parts of the peri-urban areas of Samarinda and Balikpapan Cities. According to the New Urban Agenda, peri-urban areas can help provide open green space to support rural-urban linkage and perform the new capital’s ecological functions.

POVERTY MACRO SYSTEM DYNAMICS MODELING BASED ON SIMULTANEOUS EQUATIONS MODELS

Poverty factors are multidimensional and complex. Currently, to predict the number of people living below the poverty line using the concept of linear thinking. It is necessary to study the causal relationships among poverty factors in form of a system dynamics model. This study aims to predict the poverty rate people in “The Golden Indonesia” 2030 using poverty macro models. The data used are time series data from 2009 to 2018 at the national level (Indonesia), and data sources from the BPS Statistics-Indonesia, and the Ministry of Environment and Forestry of the Republic of Indonesia. The research method uses a system dynamics model, where the system of thinking is created based on the two-stage least square (2SLS) simultaneous equation model. The 2SLS simultaneous equation model testing results show that there are three significant simultaneous equations, including poverty, economic growth, and human development index. Furthermore, the three simultaneous equations show a causal loop diagram (CLD) in a system dynamics model. The mean absolute percentage error (MAPE) is 2.34%, meaning that the macro poverty model is valid. The scenario formats for prediction include “optimistic” for economic growth and the “moderate” for human development index (HDI), total population, unemployment, and environmental quality index variables. The predicted percentage number of poor people in 2030 is 4.12%, a positive deviation of 0.12% from the government’s target of 4%. All parties need to work hard and together for the “optimistic” scenario to be implemented, which is to raise Indonesia’s economic growth to 7.4%. This study assumes that there is no Covid-19 problem and only predicts 10 years due to limited data used in 2010-2018. The novelty of this study is the alignment of the prediction results between the system dynamics and the simultaneous equation models. In general, the system dynamics model is valid and could answer the complexity of a phenomenon to predict poverty.

MODELING FACTORS AFFECTING EDUCATED UNEMPLOYMENT ON JAVA ISLAND USING GEOGRAPHICALLY WEIGHTED POISSON REGRESSION MODEL

The eighth goal of the SDGs, which aim to promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all, addresses the problem of unemployment. Indonesia, the fourth-largest country in the world, keeps on dealing with unemployment and its negative consequences. Three provinces on the island of Java have higher unemployment rates for educated people than any other provinces. The purpose of this study is to examine the variables affecting educated unemployment in Java. This study uses cross-sectional data published from BPS-Statistics Indonesia website and the Indonesia Investment Coordinating Board (BKPM) for 119 regencies/cities across six provinces on Java Island in 2021. The predictor variables are Gross Regional Domestic Product (GRDP), investment, labor force participation rate, mean years of schooling, regency/city minimum wage, and inflation. The number of working-age population is used as an exposure measure. Four models were used to analyze the factors affecting educated unemployment on Java Island: Poisson regression model and Geographically Weighted Poisson Regression (GWPR) model, both with and without an exposure. Based on the smallest AIC/AICc, the best model is the GWPR model with an exposure. This model creates 11 groups of locations based on the same predictor variables that significantly affect educated unemployment

The simultaneous effect of credit on sustainable food crop production and agricultural economic growth in Indonesia

In general, Indonesian farmers still face limited capital in their production. Therefore, credit is needed as additional capital, which is expected to help increase their agricultural business, especially rice production. This study analyzes how credit influences rice production and agricultural economic growth simultaneously. Secondary data are a time series over 12 years (2010-2021) from BPS Statistics Indonesia and Bank Indonesia. The Statistical Analysis System/Econometric Time Series (SAS/ETS) program version 9.4 is used to estimate this study using two-stage least squares (2SLS). The results show that credit simultaneously influences rice production sustainability and economic growth in the agricultural sector through credit interest rates. A simulation model that combines an increase in agricultural credit distribution of 20% and an interest rate of 5% has a greater impact on increasing rice production and economic growth in the agricultural sector compared to a simulation model that only provides a credit interest rate of 5% or 3%.

Peningkatan Kualitas Statistik Resmi Produktivitas Padi melalui Imputasi Data Non-respons Menggunakan Model Aditif Geospasial

This study is motivated by the non-response problem in the Crop Cutting Survey conducted by the BPS-Statistics Indonesia as the official statistics provider. BPS has a vision of providing quality statistical data for advanced Indonesia. Handling non-response is essential to supporting this vision because non-response can potentially cause some sample characteristics to be unrepresented. This study proposed a non-response data imputation technique through statistical modeling. The proposed model was an additive model with the addition of geospatial smoothing functions of thin plate regression splines (TP) and Gaussian process (GP). Selection of the best model based on the smallest MSEP of 1000 iterations. Then we compared the average rice productivity between listwise deletion and imputation techniques through three scenarios of non-response data. The results showed that the model with the addition of the GP smoothing function gave the best performance with the smallest MSEP. The other results showed that the imputation method of non-response data is better than ignoring non-response. BPS can consider the imputation method to improve the quality of official statistics on rice productivity.

IS THE EMPLOYMENT SITUATION IN INDONESIA FAVORABLE? IMPLEMENTATION OF VERHULST MODEL DIFFERENTIAL EQUATION

This research aims to calculate the limit number of workers and unemployment in each province of Indonesia which is estimated to use Carrying Capacity and calculate the employment growth rate of each province in Indonesia. This calculation will help to identify provinces in Indonesia where the growth rate of the working population is negative, the unemployment rate is positive. All of these calculations use the Verhulst Model Differential Equation. The data used in this research is secondary data obtained from the internet from the official website of the BPS-Statistics Indonesia regarding the Labor Force Situation in Indonesia from 2020-2023. The provinces with a lower working population growth rate, especially have negative value demands particular focus on labor absorption that are West Papua, Central Sulawesi that have high level warning status as well as Maluku and Bali that have medium level warning status. Besides the province with a greater unemployment population growth rate, especially has positive value demands particular focus on labor absorption that is Central Java that have medium level warning status

Harnessing Blockchain in BPS Microdata Dissemination

Towards achieving BPS-Statistics Indonesia missions, the dissemination process of statistical products must be carried out well. One of BPS-Statistics Indonesia statistical products is the microdata. In this case, the activity of disseminating microdata should be conducted through the implementation of feasible best practices. Related to that, in a fast-paced of the ever-changing world that heavily relies on the evolution of technology, the process of bringing out the best efforts in disseminating microdata must as well follow the rhythm of the moving technology to meet the current needs of the digital society, because otherwise it will be obsolete as time goes by. One of the important issues is the limitation of the existing system in tracking microdata to ensure its authenticity and integrity, in case where the users have purchased the microdata from BPS-Statistics Indonesia. In addressing this traceability issue, a solution through the implementation of the cutting-edge Blockchain technology is considered. A design is proposed to incorporate Blockchain into the existing mechanism of BPS-Statistics Indonesia microdata dissemination. Therefore, a system architecture and a schema for smart contract utilization are proposed to reinforce the microdata tracking.

Pojok Statistik Virtual Improvement: Development of Online Consultation and Scientific Articles Modules

With a commitment to improving statistics literacy in Indonesia, BPS Statistics Indonesia built a Pojok Statistik. Pojok Statistik is a collaborative service between BPS Statistics Indonesia and Universities initiated to answer the needs of academics and students for statistics. Due to the effects of the pandemic and the increasing interest from students, a virtual version of Pojok Statistik (Pojok Statistik Virtual) was built to meet all the needs of the offline version. However, the features are still limited and do not represent the criteria of the Pojok Statistik Offline. From the results of interviews with the Pojok Statistik Team, several plans exist to improve the Pojok Statistik Virtual, including adding online consultation and scientific articles modules. Therefore, this study aims to add online consulting service features and scientific articles modules to the Pojok Statistik Virtual. The system development process uses the Prototyping Methodology. System evaluation is conducted by black-box testing and usability testing using the USE Questionnaire. The evaluation results show that all functions in both modules are running and functioning properly. The usability test results using the USE Questionnaire reveal that these two features are feasible or usable to support the statistical needs of academics and students.

Agricultural Digitalization: Can This Transformation Increase Farmers' Income In East Java?

The era of the industrial revolution 4.0 has encouraged various economic sectors to utilize technology and information in their activities, including the agricultural sector. This study provides an overview of the impact of agricultural digitization on farmers' income and examines the characteristics of farmers in East Java who have and have not utilized agricultural digitalization as a first step toward agricultural extension targets. The data comes from the August 2022 National Labor Force Survey in East Java conducted by BPS-Statistics Indonesia with a sample size of 7.852 farmers carrying out agricultural businesses. The t-Student test results show that farmers who utilize agricultural digitization have an average income higher than those who do not utilize it. The binary logistic regression results also show that digitization of agriculture, gender, education, agricultural business field, and business status also affect farmers' income. The results random undersampling analysis and random oversampling classification and regression trees results show that there are two types of characteristics of farmers in East Java who take advantage of agricultural digitization, namely farmers who graduated at least junior high school and farmers who graduated elementary school/equivalent, come from X, Y, or Z generations, and work assisted by permanent workers/paid workers.

The Correlation Between the Bureaucratic Reform and Performance Achievement: A Case Study at the Statistics Indonesia

This study investigates the correlation between bureaucratic reform and performance due to conflicting theories about existing phenomena. In theory, it is posited that implementing bureaucratic reform should enhance performance by addressing various bureaucratic issues, resulting in a positive or directly proportional correlation. However, empirical evidence indicates persistent problems in bureaucratic performance, including public service-related complaints and other issues within the government. The government's proclamation of bureaucratic reform is expected to address these existing problems and facilitate the realization of Indonesia's goal of establishing a world-class government. Understanding the correlation between bureaucratic reform and performance achievement is crucial for designing effective programs to achieve the goals of bureaucratic reform. Given that certain conditions regarding bureaucratic reform within the work units of BPS (Statistics Indonesia) have not yet received national recognition, examining the correlation between bureaucratic reform and performance achievement is of utmost importance for BPS. A quantitative approach with correlation analysis was employed as the analytical method. The study's results reveal a positive correlation between bureaucratic reform and performance achievement, albeit not highly intense. This suggests that the variation in performance, which can be attributed to the implementation of bureaucratic reform, is not highly significant. Consequently, it becomes apparent that other factors beyond bureaucratic reform substantially influence performance at BPS. Therefore, BPS must optimize the implementation of bureaucratic reform to enhance productivity and attain superior performance.

The impact of oil palm and paddy production on greenhouse gas (GHG) emissions in Indonesia’s agricultural sector

The most widely produced agricultural commodities in Indonesia are oil palm and paddy crops, which contribute the most to national income in the agricultural sector. On the other hand, in 2020, the agricultural sector contributed 9% to national greenhouse gas (GHG) emissions. This study aims to determine the effect of agricultural crop production, namely oil palm and paddy on GHG emissions in Indonesia’s agricultural sector from 2000-2020. Data for the study were obtained from the Directorate General of Climate Change, the Ministry of Environment and Forestry and BPS-Statistics Indonesia. The GHG effect of agricultural crop production were analyzed using multiple linear regression. The findings showed that the production of oil palm and paddy crops significantly affects the agricultural sector’s GHG emissions. Oil palm and paddy production have a significant level of 5% with a regression coefficients of 0.4958 and 0.0003, respectively. From the findings, it can be implied that an increase in oil palm and paddy production will raise Indonesia’s agricultural sector GHG emissions. The government can draw up regulations related to (1) protecting forest areas and peatlands close to community residential areas so that land conversion does not occur in oil palm plantations and (2) a sustainable agricultural system to increase paddy productivity, hoping that the agricultural sector’s GHG emissions will decrease.

Application of Panel Regression Model in Gender Studies in East Java

Gender inequality remains one of the exciting issues to discuss. The role of women in social and economic continues to increase from year to year. This study aims to see the effect of the Gender Empowerment Index (GEI), Gender Development Index (GDI), and poverty rate on the Gender Inequality Index (GII) in East Java. Data sourced from the BPS-Statistics Indonesia of East Java Province for the 2018-2020 period. The statistical method used was multiple linear regression with panel data. Based on panel model testing, the random model is the best. Simultaneously, all variables affect the GII. Partially, GEI and GDI have a significant negative effect on GII. On the other hand, the percentage of poor people has a significant positive effect on GII. Based on the results of this study, comprehensive policies related to macro-social economics are needed so that the level of GII continues to decline.

Competitive advantages of biopharmaceutical commodities in Bali province

In the midst of a shift in people’s lifestyles that leads to an increasingly intensive use of herbal medicines, it has a positive impact on the existence of biopharmaceutical commodities that are increasingly economically valuable. This study aims to analyze (1) the leading biopharmaceutical commodities and (2) the competitive advantages of the biopharmaceutical commodities of the Province of Bali. The research was conducted in eight districts in the province of Bali. The number of respondents was determined using a purposive method, with a total of 160 respondents. Primary data collection was carried out through direct interviews with farmers using a questionnaire, while secondary data was collected from BPS-Statistics Indonesia. The location quotient (LQ) analysis is used to identify the top biopharmaceutical commodities, and the policy analysis matrix (PAM) method is used to study competitive advantage. The results showed that the leading biopharmaceutical commodity for Bali Province was turmeric, while ginger, galingale, galangal, and curcuma were not among the leading biopharmaceutical commodities. The results of the analysis using the PAM approach with the Private Cost Ratio indicator show that turmeric, ginger, galangal, galingale, and curcuma have competitive advantages.

Assessing The Impact of Jajar Legowo Planting System on Wetland Paddy Productivity and Income of Farmers in Indonesia

This study aims to assess whether Jajar Legowo planting system has a significant impact on increasing the productivity of wetland paddy and the income of the paddy growers in Indonesia. We applied a linear regression model to the results of the 2017 National Cost Structure of Paddy Cultivation Household Survey conducted by BPS-Statistics Indonesia in all 34 provinces. The main contribution of this study is to provide an evaluation of the performance of Jajar Legowo planting system in increasing paddy productivity and income of the farmers. Therefore, our research can be used by the government as a reference for future improvement of the implementation of Jajar Legowo cultivation system. Our findings show that the new cultivation system has a significant impact on increasing the productivity of wetland paddy. Without controlling for other variables affecting productivity, the estimation result pointed out that on average, the new cultivation system can increase productivity by about 10 per cent. However, after controlling for other variables (the farmers and other cultivations characteristics), the magnitude decreases to around 5 per cent. Moreover, our estimation results also show that the income of the farmers rises by around 12 per cent by implementing Jajar Legowo. Our study indicates that the implementation of Jajar Legowo planting system results in better efficiency than that of the conventional one.

Implementation of the Panel Model on Investment Determinants in Indonesia in 2018-2022

Investment plays an essential role in the economic growth of a country. A country's ability to attract investment in various sectors can positively impact infrastructure development, job creation, and improving people's welfare. This study aims to determine the effect of the Gross Regional Domestic Product (GRDP), Regional Income, and Human Development Index (HDI) on investment in Indonesia. The variables of Domestic Investment and Foreign Investment measure investment. Data is sourced from the BPS-Statistics Indonesia for the 2018-2022 period—the statistical method used with multiple linear regression with panel data. Based on panel model testing, the PCSE model is the best. Simultaneously, all variables affect investment in Indonesia. Partially, GRDP, Regional Income, and HDI have a significant positive effect on investment in Indonesia. Based on the results of this study, comprehensive policies related to macro-social economics are needed so that the level of investment continues to increas.

Potential Carbon Footprint in Food System Based on Household Vegetable Consumption in Yogyakarta

Consumption is one part of the food system in a region. Food is a basic need that cannot be separated from various activities. Food systems account for about a quarter of the global carbon footprint, indicating that every activity in it will impact the environment. This study aims to explain the potential carbon footprint resulting from the vegetable consumption commodities in Yogyakarta as part of the food system. The city of Yogyakarta became the research area with the consideration that this area is an urban area with a high population density, a high proportion of waste transported to the final landfill, and the composition of organic waste, which is more than half the total volume of waste. This study uses secondary data from the Socio-Economic Survey (Susenas) from the BPS-Statistics Indonesia and relevant literature. A quantitative descriptive analysis technique was used in this study to explain the vegetable food consumption of the people of Yogyakarta City. The potential for carbon footprint and food waste is calculated using emission factors that include production activities up to distribution. The results show that eggplant has the highest potential carbon footprint based on consumption data, with an average value of 0.25 kg CO2-eq/kg per household in one week. The average potential carbon footprint of vegetable consumption per household in one week in Yogyakarta City is 1.9 kg CO2-eq/kg produce. Potential food waste based on consumption activities has an average value of 0.15 kg per household in one week.