Jurnal Statistika Terapan (JSTAR)
Aim: JSTAR studies applied statistics at the regional and national levels of East Nusa Tenggara which are directed to contribute to the government in making regional development policies. JSTAR pays special attention to official and modeling statistics, big data and data mining, and the application of statistics in various fields that are included in the output of BPS activities such as agriculture, local government finance, poverty, demography, GIS, health, and economic growth. Scope: 1. Official statistics – Manuscripts dealing with survey design, questionnaire design and evaluation, measurement error, estimation and inference using frequentist or Bayesian, data collection, analytical uses of data, imputation, quality aspects of official statistics production, total survey error, systems and architectures for statistics production, evaluation and identification of statistical needs, small area estimation, and other subject related to official statistics. 2. Statistical Methodology – Manuscripts dealing with new and innovative data analysis techniques and methodologies include, but are not limited to: bootstrapping, classification techniques, design of experiments, parametric and nonparametric methods, statistical genetics, outlier detection, cross-validation, functional data, fuzzy statistical analysis, mixture models, model selection and assessment, nonlinear models, partial least squares, latent variable models, structural equation models, and robust procedures. 3. Applied Statistics in Economics, Social and Population Studies – Manuscript dealing with econometrics, demography, spatial analysis, time series analysis, longitudinal analysis, multilevel analysis, spatio-temporal analysis, and other subjects related to Applied Statistics in Economics, Social, and Population Studies. 4. Data Science – Manuscript dealing with big data, data mining, data science, data engineering, data visualization, machine learning, and data exploration. 5. Computational Statistics – Manuscripts dealing with the use of computing in statistical methodology (e.g., statistical databases, statistical information systems, Bayesian computation, computer-intensive inferential methods, numerical and optimization methods, parallel computing), and the development, evaluation, and validation of statistical software and algorithms.
Articles
66 Documents
<![CDATA[COMPARATIVE ANALYSIS OF SINGLE-SAMPLE HYPOTHESIS TESTING: CRITICAL EVALUATION OF FREQUENTIST APPROACHES AND BAYESIAN INFERENCE ON SIMULATED DATA ]]>
<![CDATA[Pardomuan Robinson Sihombing]]>
<![CDATA[ Jurnal Statistika Terapan (ISSN 2807-6214) Vol 6 No 1 (2026): Jurnal Statistika Terapan ]]>
Publisher : <![CDATA[Badan Pusat Statistik Provinsi NTT ]]>
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DOI: 10.64930/jstar.v6i1.142
<![CDATA[The validity of statistical inference is a key pillar in data-driven decision making, but it is often threatened by the inappropriate selection of methods for non-ideal data. This study aims to evaluate the performance of single-sample hypothesis testing methods by comparing the frequentist paradigm (Student's t-test, Wilcoxon signed-rank test, sign test) and the Bayesian paradigm (Bayes factor). Through Monte Carlo simulations using R Studio with 1,000 iterations, this study investigates statistical power, Type I error rate, and the accuracy of effect size estimates (Cohen's d, Rank-Biserial Correlation, Cohen's g) under Normal, Heavy-tailed (t-Student), and Skewed (Log-normal) distribution conditions with sample variations . The results show that under the t-Student distribution ( ), the Wilcoxon test consistently outperforms the T-test in terms of power (0.514 vs. 0.416 at n ). Another crucial finding is the bias in Cohen's d estimation on Log-normal data, which tends to underestimate the actual impact of location when compared to Rank-Biserial Correlation. The Bayesian approach proved to be more conservative but provided better inference stability in large samples]]>
<![CDATA[ANALISIS NEET (NOT IN EMPLOYMENT, EDUCATION OR TRAINING) PADA GEN Z USIA PRODUKTIF DI PROVINSI NUSA TENGGARA TIMUR ]]>
<![CDATA[Hery Wahyu]]>
<![CDATA[ Jurnal Statistika Terapan (ISSN 2807-6214) Vol 6 No 1 (2026): Jurnal Statistika Terapan ]]>
Publisher : <![CDATA[Badan Pusat Statistik Provinsi NTT ]]>
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DOI: 10.64930/jstar.v6i1.146
<![CDATA[The phenomenon of Not in Employment, Education, or Training (NEET) among youth, particularly Generation Z (Gen Z), poses an important challenge to Indonesia’s human capital development. Although the national NEET rate declined from 24.28 percent in 2020 to 20.31 percent in 2024, the figure remains sufficiently high to indicate that many productive-age youth are still not fully engaged in education, training, or the labor market. A similar condition is observed in East Nusa Tenggara (NTT), which records a NEET rate of 14.1 percent and has the highest dependency ratio nationally, reaching 61.6 percent based on the 2035 population projection. These circumstances highlight the need to maximize the participation of the productive-age population to ensure that the demographic bonus is effectively utilized rather than becoming a demographic burden. This study analyses the NEET status of productive-age Gen Z in NTT and examines the determinants influencing NEET outcomes using binary logistic regression. The independent variables considered include gender, age group, marital status, disability status, area of residence, highest educational attainment, and household size. The results show that all variables have a significant effect on the likelihood of Gen Z being categorized as NEET. Keywords: Gen Z, NEET, binary logistic regression]]>
<![CDATA[PREDIKSI PERUBAHAN TUTUPAN LAHAN MENGGUNAKAN CITRA SATELIT PENGINDERAAN JAUH PADA KAWASAN DESTINASI PARIWISATA SUPER PRIORITAS: STUDI KASUS KECAMATAN KOMODO, KABUPATEN MANGGARAI BARAT, NUSA TENGGARA TIMUR ]]>
<![CDATA[Elisa Imania]]>;
<![CDATA[Raka Ikmana]]>
<![CDATA[ Jurnal Statistika Terapan (ISSN 2807-6214) Vol 6 No 1 (2026): Jurnal Statistika Terapan ]]>
Publisher : <![CDATA[Badan Pusat Statistik Provinsi NTT ]]>
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DOI: 10.64930/jstar.v6i1.149
<![CDATA[Introduction: Labuan Bajo is designated as one of Indonesia’s five super priority tourism destinations. Background Problems: Population growth and rapid development of Labuan Bajo tourism destination have had a significant spatial impact on the Manggarai Barat Regency. Novelty: This study aims to analyze land cover changes in the Komodo District, Manggarai Barat Regency, during the period 2022-2024, predict land cover in 2027, and then analyze its relationship with sustainable tourism development. Research Methods: The data used in this study consists of land cover maps, road maps, and National Digital Elevation Model maps sourced from ESRI through Living Atlas and the Geospatial Information Agency. Land change potential modeling was conducted using Artificial Neural Network with Multi-Layer Perceptron structure. Findings/Results: The results of the land cover change modeling show that 90.76% of the land cover can be mapped correctly. The validity test results also indicate that the model performs very well with a Kappa value of 0.86009, making it suitable for predicting future land cover. The 2027 land cover prediction shows that compared to 2022, trees will decrease by 707.70 ha, while built-up area and rangeland will increase by 445.75 ha and 340.24 ha, respectively.]]>
<![CDATA[PENGARUH PEREMPUAN DALAM MENGENTASKAN KEMISKINAN: ANALISIS REGRESI PANEL WILAYAH PARIWISATA DAN NONPARIWISATA DI PROVINSI NUSA TENGGARA TIMUR, 2017-2024 ]]>
<![CDATA[Kautsar Hilmi Izzuddin]]>;
<![CDATA[Muhammad Dzaky Fawwaz]]>
<![CDATA[ Jurnal Statistika Terapan (ISSN 2807-6214) Vol 6 No 1 (2026): Jurnal Statistika Terapan ]]>
Publisher : <![CDATA[Badan Pusat Statistik Provinsi NTT ]]>
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DOI: 10.64930/jstar.v6i1.156
<![CDATA[Introduction: Nusa Tenggara Timur (NTT) consistently occupies a position as one of the provinces with the highest poverty levels in Indonesia. This situation is further worsened by poverty reduction targets that have not been met as of 2024, even though the region has great tourism potential. This poverty phenomenon is also closely linked to the economic participation of women. Background Problem: This study aims to analyze the impact of women on poverty and compare this effect between tourism and non-tourism areas in NTT. Novelty: While many studies on poverty have been conducted, research that compares the role of women by separating tourism and non-tourism bases in NTT remains very limited. Research Method: This study uses panel data regression analysis from 22 regencies during the 2017–2024 period, which also splits the model into tourism and non-tourism categories. Finding/Results: Results show that increases in women's life expectancy, expenditure, and literacy rates significantly lower poverty in tourism areas. However, in non-tourism areas, the labor force participation rate and literacy are the main factors, while life expectancy does not have a significant effect. On the contrary, the percentage of women of productive age does not show a significant impact in either region.]]>
<![CDATA[PENGARUH UPAH DAN KEMAHALAN KONSTRUKSI TERHADAP PENGELUARAN PER KAPITA DI PROVINSI NUSA TENGGARA TIMUR TAHUN 2019-2024 ]]>
<![CDATA[Ahsan Anwar Basari]]>
<![CDATA[ Jurnal Statistika Terapan (ISSN 2807-6214) Vol 6 No 1 (2026): Jurnal Statistika Terapan ]]>
Publisher : <![CDATA[Badan Pusat Statistik Provinsi NTT ]]>
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DOI: 10.64930/jstar.v6i1.159
<![CDATA[Introduction/Main Objectives: Household welfare is commonly measured by per capita expenditure, which reflects consumption capacity. In Nusa Tenggara Timur Province (NTT), welfare conditions are characterized by low per capita expenditure and low wage levels, along with relatively low regional cost levels as reflected by the Construction Cost Index (IKK), which is used as a proxy indicator to capture regional price disparities. Background Problems: Theoretically, such conditions should provide room for higher purchasing power; however, empirical evidence is still required to confirm this relationship. Novelty: This study provides recent study on the effects of wages and the Construction Cost Index (IKK) on per capita expenditure in NTT. Research Methods: This study aims to analyze the effect of wages and the IKK on per capita expenditure across 22 regencies/municipality in NTT during the period 2019-2024. The study uses panel data obtained from official publications of the Badan Pusat Statistik (BPS). The analysis is conducted using a Fixed Effect Model (FEM) estimated with Feasible Generalized Least Squares (FGLS). Finding/Results: show that wages have a positive but not significant effect on per capita expenditure at the 5 percent level of significance but are statistically significant at 10 percent, while the IKK has a negative and significant influence at the 5 percent significance level. These findings indicate that income improvements increase consumption, whereas regional cost conditions remain a constraint on household welfare.]]>
<![CDATA[IKHTISAR SATU DEKADE KEMISKINAN DI NTT DALAM DIMENSI SOSIAL, EKONOMI, DAN INFRASTRUKTUR (ANALISIS REGRESI PANEL PADA DATA 2015-2024) ]]>
<![CDATA[Abdul Rosyid Rexy Andryan]]>
<![CDATA[ Jurnal Statistika Terapan (ISSN 2807-6214) Vol 6 No 1 (2026): Jurnal Statistika Terapan ]]>
Publisher : <![CDATA[Badan Pusat Statistik Provinsi NTT ]]>
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DOI: 10.64930/jstar.v6i1.161
<![CDATA[Introduction/Main Objectives: The poverty in East Nusa Tenggara Province (NTT) over the past decade still shows a high number. The percentage of poverty in NTT is far above the national average and occupies the fourth highest position in Indonesia by 2025. Background Problems: This study explains the social, economic, and infrastructure factors in influencing poverty in NTT during 2015-2024. Novelty: This study uses time series data for poverty and possible variables that affect it in the last ten years by considering social, economic, and infrastructure dimensions. Long time series can provide more varied and efficient information whereas the panel data on the study better explains dynamic changes. Research Methods: The methods used in this research is panel data regressions which tests the panel data to find the best regression model. Finding/Results: The results of this study show that Labor Participations Rate (TPAK), average length of schooling, and per capita expenditure have a negative effect on poverty in NTT while life expectancy has a positive effect on poverty. The R-squared generated in the panel data regression model shows a figure of 74.95 percent so that it can explain the model well]]>
