Indonesian Central Bureau Of Statistics Research Articles

Forecasting Coffee Exports to the United States Using the Holt-Winters Exponential Method

A study was conducted to estimate coffee exports to the United States using the Holt-Winters Exponential method. The aim of this research is to project coffee export activity over the next four periods. Data on coffee exports to the United States from 2000 to 2022 was obtained from the Indonesian Central Bureau of Statistics and used as a research object. The range of values used in this study is between 0.1 and 0.5 for α, between 0.1 and 0.5 for β, and between 0.1 and 0.9 for ϒ. The results of this research state that it is estimated that in 2023, Indonesia will export coffee to the United States amounting to 61,332.60 tons, in 2024 amounting to 60,661.50 tons, in 2025 amounting to 61,563.27 tons, and in 2026 amounting to 60,196.50 tons

Comparison of Weights in Weighted Least Square Method For Handling Heteroscedasticity on Multiple Regression Model

Regression analysis is the most popular and commonly used to determine causality between two or more variables. In regression analysis there are several assumptions that must be held, so that the property of the best linear unbiased estimator (BLUE) is still guaranteed. In fact, we often found violations of the assumptions. One of them was violations of the homoscedasticity or occurs heteroscedasticity. The impact of heteroscedasticity in the regression model is that the ordinary least square (OLS) estimator no longer has a minimum variance although still linear and unbiased. To handle this, weighted least square (WLS) regression is used instead, which giving weights on the observations. But the problem often encountered is choosing which the best weight in WLS method. This paper aimed to compare and determine the best weight among 1/X, 1/ , 1/Y and 1/s in multiple regression model. Human development index factors data, which were obtained from the Indonesian Central Bureau of Statistics, were used. The results showed that the best weight on human development index data was 1/s. The coefficient of determination was 98.7% indicating that the model was very good.

Pengaruh Kesehatan Reproduksi Wanita dan Pemberdayaan Wanita Terhadap Tingkat Partisipasi Angkatan Kerja Wanita di Indonesia

This study aims to find out and analyze how the influence of women's reproductive health and women's empowerment on the participation rate of the female workforce in Indonesia. This study used secondary data sourced from the Indonesian Central Bureau of Statistics with the research variables grouped into two parts, namely the bond variable which in this study was determined as the female labor force participation rate and the independent variables consisting of women's life expectancy, young women's marriage, female mother, female education level, female per capita income and female involvement in parliament. This study uses panel data regression analysis with the selected method, namely the Common Effect Model (CEM). The results showed that women's life expectancy, young women's marriage, women's fertility rates and women's involvement in parliament each had a negative and insignificant effect on women's labor force participation. Women's education level has a negative and significant effect on female labor force participation and women's per capita income has a positive and significant effect on female labor force participation.

Comparative Analysis of LSTM Neural Network and SVM for USD Exchange Rate Prediction: A Study on Different Training Data Scenarios

Purpose: This paper aims to investigate and compare the performance of LSTM Neural Network and Support Vector Machines (SVM) in predicting the USD exchange rate using three different training data scenarios: 45%, 55%, and 75%. The study employs a dataset from the Indonesian Central Bureau of Statistics (BPS) for the period of January 1 to June 30, 2021, encompassing attributes USD Selling Rate.Methods: The methods involve implementing LSTM and SVM algorithms within the Python programming language using Google Colaboratory. Three distinct training data scenarios are explored to evaluate the models' robustness. Performance metrics, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared, are employed for evaluation.Result: Results reveal that LSTM demonstrates superior prediction accuracy compared to SVM across all scenarios, even though it incurs a longer training time. Notably, in the 75% training data scenario, LSTM achieves an MAE of 49.52, RMSE of 63.08, and R-squared of 0.37906, outperforming SVM with MAE of 138.33, RMSE of 161.58, and R-squared of 0.34277.Novelty: This study innovatively compares LSTM Neural Network and Support Vector Machines (SVM) for USD exchange rate prediction across different training scenarios (45%, 55%, and 75%). Unlike previous research focusing on individual models, this study systematically evaluates both methods, highlighting the nuanced balance between prediction accuracy and training time. The findings offer novel insights into LSTM and SVM applicability in currency forecasting, providing valuable guidance for researchers and practitioners in model selection based on specific predictive task requirements.

The Effect of Foreign Investment And Domestic Investment on The Gross Regional Domestic Product in Indonesia (Survey of 34 Provinces for 2019-2022)

The purpose of this study was to determine the effect of foreign investment and domestic investment on gross regional domestic product in Indonesia. The research subjects are 34 provinces in Indonesia for the period 2019 – 2022. This research was conducted in Indonesia. This type of research is quantitative research. The data used in this study are secondary data obtained from the Indonesian Central Bureau of Statistics. The research method used in this study is the explanatory method. Data analysis techniques in this study are descriptive analysis and panel data regression analysis. The results of this study simultaneously indicate that there is an influence of foreign investment and domestic investment on gross regional domestic product. Partially, there is no effect of foreign investment on gross regional domestic product, while domestic investment has an effect on gross regional domestic product.

Effect of durian and jackfruit seed starch combination variation on bioethanol content using Aspergillus niger and Saccharomyces cerevisiae

Durian and jackfruit seeds are around 5-15% of whole fruit, and only few is utilized as animal feed and generally become waste. Based on the Indonesian Central Bureau of Statistics, durian production in Indonesia reached 1.35 million tons in 2021 and increased by 19.40% compared to 2020. The government issued a policy to encourage the development of renewable energy sources as an alternative to fuel oil because the oil supply will run out in about 12 years. The government targets the use of renewable energy in 2025 to reach 23% by preparing a program to implement the use of bioethanol in motor vehicles and preparing the bioethanol industry in Indonesia. The purpose of this study is to get the best seeds combination to produce highest bioethanol content. Research used 50 gram 80 mesh durian and jackfruit seed starch combination and was started with multistage fermentation with addition of Aspergillus niger for 72 hours to produce glucose then continued with Saccharomyces cerevisiae for 120 hours to produce ethanol. The next stage was to distill for 6 hours to separate ethanol and water using the boiling point difference principle. The ethanol will be analyzed using refractometer. The highest ethanol content obtained was 20% from a combination of 25% jackfruit and 75% durian seed starch. This ethanol content was higher than the previous research with 100% durian seed starch which was up to 1.61% and for 100% jackfruit seed starch was up to 2.435%.

Pengaruh Angka Partisipasi Sekolah (APS) Dan Tingkat Partisipasi Angkatan Kerja (TPAK) Terhadap Indeks Pembangunan Manusia (IPM) di Indonesia

This study aims to determine the effect of the School Participation Rate (SPR) and the Labor Force Participation Rate (LFPR)) on the Human Development Index (HDI in Indonesia. This study uses secondary data sourced from the Indonesian Central Bureau of Statistics (BPS) for the 2012-2021 period. Data were analyzed using the Multiple Linear Regression analysis method. The results of the research partially show that the variable School Participation Rate (SPR) has a positive and significant effect on the Human Development Index (HDI) and the Labor Force Participation Rate variable (LFPR) has no effect and is not significant on the Human Development Index (HDI) in Indonesia. The results of the study simultaneously with the School Participation Rate (SPR) and Labor Force Participation Rate (LFPR) variables have a positive and significant effect on the Human Development Index (HDI) variable.

Interrelation of urban farming and urbanization: an alternative solution to urban food and environmental problems due to urbanization in Indonesia

Urbanization is the process of increasing the population migrating to urban areas, and urban farming is a farming practice carried out within the city. Both concepts have significant impacts on urban life and the environment. This research aims to analyze the interrelation of the positive impacts of urban farming and the negative impacts of urbanization. The analysis focuses on food and environmental aspects as alternative problem-solving methods in the cities of Bandung, Denpasar, and Palembang. This research uses qualitative method. Data collection uses field interview techniques with 30 informants, as well as a review of several scientific articles, previous research results, and reports from data-providing agencies such as the Indonesian Central Bureau of Statistics. Data analysis used the Miles and Huberman Model, with the stages of reduction, display, and conclusion drawing. The results of the analysis show that there is an interrelation between the positive impacts of urban farming and the negative impacts of urbanization in the cities of Bandung, Denpasar, and Palembang. In terms of food aspect, urban farming can provide various types of easily accessible food for urban dwellers, such as vegetables, fruits, fisheries, and small-scale livestock. The food produced is relatively close to residential areas, so the quality is still fresh and healthy and the price is affordable as well. In the environmental aspect, urban farming can optimize the use of limited or vacant land in residential areas into productive land, such as for green spaces, farming activities, gardening, fisheries, and livestock. Other functions include enhancing the beauty of the environment, reducing household waste, and preserving organism biodiversity.

ASSESSING THE INFLUENCE OF THE ISLAMIC FINANCIAL SYSTEM ON INDONESIA'S ECONOMIC GROWTH IN THE LONG AND SHORT RUN FROM 2011 TO 2022

This study aims to see the performance of the Islamic financial system on Indonesia's economic growth in the long and short run from 2011 to 2022. The research method uses the Autoregressive Distributed Lag (ARDL) analysis method. The data used in this study are secondary. Secondary data is a source of data that is not directly obtained from objects through interviews. Secondary data can be obtained from other organizations or individuals such as census data collected. Data from the Indonesian Central Bureau of Statistics (BPS) and the Financial Services Authority (OJK). This study uses economic growth as the dependent variable and the Indonesian Sharia Stock Index and Islamic banking financing as independent variables. The research provides results that the performance of Islamic banking financing and the Indonesian Sharia Stock Index provides positive and significant results on economic growth. Based on the results of this study, it is hoped that the government will further strengthen policies that focus on the development of Islamic finance in Indonesia because improving the performance of the Islamic financial system can improve and encourage economic growth in Indonesia.

Understanding the Dynamics of Unemployment and Poverty in the Tomini Bay Area

This study aims to analyze the effect of education level, gini ratio and labor force participation rate on unemployment, as well as the effect of unemployment on poverty in the Tomini Bay region. The data used in the study is secondary data in the form of 10 regencies/cities in the Tomini Bay area, for the 2018-2022 period, sourced from the Indonesian Central Bureau of Statistics. The novelty of this study is trying to trace the relationship between educational and economic aspects to the phenomenon of poverty in the Tomini Bay Region, as a regional economic power. The future impact of this study is the mapping of the actual condition of poverty and the availability of more evidence-based policy recommendations in reducing unemployment and poverty in the Tomini Bay Area. This study used descriptive quantitative methods. With an approach (Simultaneous equation regression model) using the Indirect Least Square (ILS) regression technique with Fixed Effect Model (FEM). The results of this study show that the level of education and the labor force participation rate have a negative and significant effect on unemployment. In contrast to the Gini ratio which actually has a positive and significant effect on unemployment. On the other hand, unemployment shows a positive and significant influence on poverty. The implication of the research is the need for a truly massive policy to strengthen the education dimension, to accelerate the increase in human capital and the importance of a sustainable program to increase employment opportunities from the government so as to reduce unemployment and poverty.

Analysis of the Competition Structure of Scrap Iron Buying and Selling Businesses (A Case Study in Kuin Cerucuk, Banjarmasin)

This research project aims to analyze and identify the competitive structure that influences competitive advantage in the scrap metal sales market and formulates key success factors, or KSFs. This study seeks to explain the causal relationship between one variable and another, which is known as explanatory (causality) research (Sekaran & Bougie, 2017). Primary data was gathered through questionnaire instruments and in-person interviews with business owners, managers, employees, and customers who bought or sold scrap metal. Secondary data was gathered from publications, journals, the internet, libraries, and associated organizations like the Ministry of Industry and Trade and Indonesian Central Bureau of Statistics. Through the use of observation, interview, and literature study methodologies, data gathering procedures were obtained. Competitive industry analysis with models from Five Porces Porter, competitive advantage, and descriptive analysis with company profile analysis are the analysis methodologies employed in this study. The findings show that: substitute products in the market lessen the threat of replacement products for scrap metal; the level of rivalry among competitors in the scrap metal buying and selling industry is strong; the threat of new entrants into the used buying and selling industry is weak; suppliers have strong bargaining power; and buyers have strong bargaining positions. Key success factors are economies of scale, marketing systems and capacities, financial availability, raw material and technological access.

Determinants of Information and Communication Technology Development in Indonesia (2018-2021)

This study aims to analyze the influence of average household consumption for telecommunications, households that own and control cell phones, Number of Villages or Regions Receiving Cell Phone Signals and the Covid-19 Pandemic on the Information and Communication Technology Development Index in Indonesia for 2018-2021. The data used in this study is secondary data, namely the Information and Communication Technology Development Index, Average Household Consumption for Telecommunications, Households Who Own and Control Cell Phones, Number of Villages/Regions That Receive Cell Phone Signals and the Covid-19 Pandemic as dummy variables, which have been published by the Indonesian Central Bureau of Statistics (BPS). The analytical method used in this study is panel data regression analysis using the Fixed Effect Model approach. The study results show that variables Average Household Consumption for Telecommunications, the variable Households Who Own and Control a Cellular Telephone have an influence, the variable Number of Villages/Regions Receiving Cellular Telephone Signals and Communication and the Covid-19 Pandemic variable have a positive and significant influence on the variable Information and Communication Technology Development Index in Indonesia 2018-2021.

The Impact of the Increase of Oil Fuel Price and Government Subsidy on Indonesia’s Economic Performance

The policy of increasing domestic fuel oil, as a consequence of rising world oil prices, has resulted in changing economic conditions, bearing in mind that oil prices and production are wrong macroeconomic assumptions and are included in the State Revenue and Expenditure Budget. This study aims to determine the impact of rising fuel prices and government subsidies on Indonesia's economic performance. The data used in this study are time series data from 2000 to 2022. Data were obtained from the Indonesian Central Bureau of Statistics, the Ministry of Energy and Mineral Resources, the Ministry of Finance, and Bank Indonesia. This study uses an econometric model using a system of simultaneous equations. The research results show that; The main factors that caused the increase in domestic fuel prices, including crude oil prices, gasoline, diesel, kerosene and aviation fuel, were the increase in world oil prices and the previous year's oil prices. The estimation results also show that the increase in gasoline and diesel fuel can increase the number of poor people, unemployment and inflation in Indonesia. The policy simulation results show that the increase in oil prices has a significant impact on increasing the number of poor people, increasing unemployment and inflation, if this increase is not followed by subsidies in the form of non-energy.

Autoregressive Vector (VAR) Method in Analyzing Inflation Persistence in Indonesia

One of the most important economic variables is inflation. It is known that some changes in each major variable in the economy are caused by the rate of inflation, such as unemployment and future economic conditions. This is what makes inflation a variable that is often observed and tested, both theoretically and empirically. Economic development is said to run well if supported by stable inflation values, which will later serve to make the population more prosperous in the future. This research is a quantitative research using secondary data, namely inflation and CPI data from January 2018 to December 2022. Data obtained from Bank Indonesia and the Indonesian Central Bureau of Statistics. This study aims to see persistence in Indonesia and see the effect of CPI on inflation both in the long and short term. Where the model used in this study is using the VAR model of differential levels, because the data is not stationary at the level level. Determination of the optimal lag length is obtained from the lowest Akaike Information Criterion (AIC) value. The results of the analysis show that the persistence of inflation in Indonesia is fairly high. This is because the lag value in inflation is close to 1 or even more, which is 6.71. The high persistence of inflation is expected to cause shocks that affect the inflation rate in Indonesia. Then the length of time it takes for inflation to return to the equilibrium position is about 1 year and a half or 18 months. Furthermore, for the effect of inflation on CPI, in this case it has an influence in the long run, while for the short term influence is only influenced by its own variables.

Does financial digitalization affect macroeconomic stability in Indonesia? An application of the autoregressive distributed lag (ARDL) model

Digitalization has transformed the monetary system more radical for many years. This study aims to investigate the effect of digital payments on macroeconomic stability. Electronic money is used as a proxy for digital payment. The macroeconomic stability is calibrated using exchange rate volatility and inflation rate. This study uses monthly data ranging from January 2009 to March 2020. Macroeconomic data were collected from the Indonesian Central Bureau of Statistics and the Organisation for Economic Co-operation and Development. Industry and market data from the Central Bank of Indonesia (Statistic of Bank Indonesia) and the Indonesian Stock Exchange (IDX). The data were analyzed using the Autoregressive Distributed Lag (ARDL) to examine the long-run and short-run relationship between the studied variables. This study found that digital payments affect Indonesian macroeconomic stability. Electronic money as a proxy of digitalization has a positive and significant relationship with exchange rate volatility and inflation. Cross-border e-commerce might induce exchange rate volatility due to its convenience as a one-stop shopping service and its lower switching cost of currency. The driver of higher inflation is electronic money, which increases people's spending, thus increasing the velocity of circulation and total consumption.

Halal Industry Development in Indonesia: Opportunities and Challenges Post Covid-19 Pandemic

Indonesia is a country where the development of the halal industry can become a sizeable potential, not only domestically but also abroad. The halal industry has played an important role in improving the economy in Indonesia. The halal industry is recorded to have contributed USD 3.8 billion to Indonesia's Gross Domestic Product (GDP) each year. Looking at the facts on the ground, even though Indonesia is a country with the largest Muslim population in the world. However, the large Muslim population has not been able to make Indonesia a supplier country for the needs of halal commodities in the world. For this reason, this study aims to look at the Development of the Halal Industry in Indonesia regarding Opportunities and Challenges in the Post-Covid-19 Pandemic. The data collection technique for this research uses documentation and literature studies. Documentation studies, namely by downloading files on development reports of companies and businesses engaged in the halal industry on the official website of the Indonesian Central Bureau of Statistics. The problem-solving framework in this study starts from selecting the research topic and then formulating the problem to see what the problem is to be studied. Furthermore, the researcher collects the required data and performs an analysis based on the data that has been collected, and then draws conclusions based on the descriptive analysis that was carried out. Through this research, the authors hope to contribute to a portrait of the halal industry in post-pandemic Indonesia, so that they can see opportunities for development.

Analisis Pengaruh Modal Manusia dan Penggunaan Teknologi Informasi Komunikasi (TIK) Terhadap Pengembalian Pendidikan Di Indonesia

This study aim to determine the return to education in Indonesia analyzed based on various types of education as well as the influence of human capital and ICT use. Method used to analyze is the Mincerian Earning Function with the Heckman Two Step approach. We use micro data from the March 2021 National Socioeconomic Survey obtained from the Indonesian Central Bureau of Statistics. We found increasing years of school will increase the return to education just as work experience will increase the return of education, but increasing work experience will lead to a decrease in return on education. Individual characteristics, namely the male population with unmarried status, residing in urban areas, working in secondary business fields and the formal sector and with full working hours will increase the return on education. Health variables that cause a decrease in education returns as a result of the COVID-19 pandemic conditions in Indonesia. The return of general education and vocational education, and non-formal education is higher than madrasah education or Islamic education. The use of computers and the Internet for economic activity purpose provides excellent value for increasing educational returns.

Analisa Metode Backpropagation Pada Prediksi Rata-rata Harga Beras Bulanan Di Tingkat Penggilingan Menurut Kualitas

Rice is a staple food in Indonesia and plays a crucial role in the food structure as a source of nutrition. The diverse population of Indonesia, spread across various islands, makes rice availability highly important. The government continues to strive for food security, particularly by increasing domestic production. These considerations become even more significant for Indonesia due to its growing population and extensive geographical distribution. To meet the population's food needs, Indonesia needs sufficient food supply and distribution to fulfill consumption and maintain adequate reserves for extensive logistical operations. Rice shortage can be seen as a threat to economic and political stability. The significance of rice as a food commodity means that it is constantly in demand by people from all walks of life. Price fluctuations over time due to imbalances between supply and demand have a significant impact on the middle class and working class. The instability of rice prices greatly affects both the general public and farmers. Generally, prices are determined by the interaction of supply and demand. If supply is high and demand is low, prices will decrease. Conversely, if supply is low and demand is high, prices will increase. Prediction is an important tool to anticipate future events by recognizing patterns from the past. Backpropagation can be used as a method to predict rice prices. The data used in this study are the average monthly rice prices at the milling level according to the quality of large-scale traders from January 2023 to December 2023, in Indonesian Rupiah per kilogram. This research utilizes data obtained from the website of the Indonesian Central Bureau of Statistics (BPS) from 2013 to 2022. The study employed 5 different architectures for data testing, namely the 15-15-1 architecture with a testing mean square error (MSE) of 0.00644604, the 15-19-1 architecture with a testing MSE of 0.01005532, the 15-30-1 architecture with a testing MSE of 0.02119922, the 15-31-1 architecture with a testing MSE of 0.00009938. The best architecture in this study was the 15-17-1 model with 5206 iterations and a runtime of 18 seconds, achieving the smallest testing MSE of 0.00000105 and the highest accuracy of 100%. From the obtained architectures, it is evident that backpropagation can perform with a high level of precision. This research can serve as a guideline for the government to determine rice availability and establish average rice prices based on quality, thus preventing future rice shortages.

UPAYA P2TP2A DALAM PERLINDUNGAN HUKUM TERHADAP KORBAN PEDOFILIA

This research discusses the efforts made by P2TP2A in legal protection for child victims of pedophilia in Aceh Singkil. This research is motivated by the Indonesian Central Bureau of Statistics which records that pedophile crimes continue to increase. Not only in cities, but spreading to villages, one of which is Aceh Singkil. In victimology, children are very vulnerable to becoming victims of crime. Based on this, the guarantee of a decent life, the widest possible opportunity for children to grow and develop, both physically and mentally, is hampered due to the act of pedophilia and of course causes deep psychological trauma to the victim. The problem raised in this study is, What are the factors that cause pedophilia in Aceh Singkil? What are the efforts of P2TP2A Aceh Singkil for legal protection for child victims of pedophilia? aims to find out what are the factors causing the occurrence of pedophilia crimes in Aceh Singkil and the efforts made by P2TP2A Aceh Singkil for legal protection for child victims of pedophilia. The research method used in this study is descriptive analysis, with the type of research library research) and (field research). Based on the results of the research, the authors found that the factors causing the occurrence of pedophilia in Aceh Singkil were easy access to videos that contained elements of decency, alcohol, and a lack of strong faith, a lack of control over the family from parents as protectors, and a lack of education about sex against victim). There are several legal protection efforts carried out by P2TP2A Aceh Singkil, namely providing legal aid services, medical assistance, social rehabilitation efforts, reintegration and assisting all victim recovery referral mechanisms to the provincial P2TP2A.

THE EFFECT OF FOREIGN DEBT, FOREIGN INVESTMENT AND STATE REVENUES ON POVERTY IN INDONESIA

This study aims to analyze the effect of Foreign Debt (FD), Foreign Direct Investment (FDI) and State Revenue (SR) on the number of poor people in Indonesia. The data used in this study is time series data for 1990-2021 obtained from the Indonesian Central Bureau of Statistics and the World Bank. The data were then analyzed using the Autoregressive Distributed Lag (ARDL) model. The results of this study indicate that, in the short term, the previous 1 year had a negative and significant effect on the number of poor people in Indonesia, while the previous 3 years had a positive and significant effect on the number of poor people. In the long term, foreign debt has a positive and significant effect on the number of poor people in Indonesia. FDI in the previous 0 and 3 year lag had a negative and significant effect on the number of poor people in Indonesia, while 1 year before and 3 years earlier FDI had a positive and significant effect on the number of poor people. In the long term, FDI has a negative and insignificant effect on the number of poor people. SR at lag 0 has a negative and significant effect on the number of poor people in Indonesia, whereas in the previous 3 years SR had a positive and significant effect on the number of poor people. In the long term SR has a negative and significant effect on the number of poor people in Indonesia. Based on the results of this study, it is suggested that the government should carefully calculate the amount of foreign debt needed and pay attention to the distribution of allocations for the use of foreign debt, especially in the poverty alleviation sector. In addition, the government is expected to create a conducive investment climate and increase state revenues, especially through taxes.