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All Journal JEJAK Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal of Business, Law, and Education Prosiding Seminar Nasional Official Statistics
Wahyuni, Krismanti Tri
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Transportation Other

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Industrialization and Convergence of West Java Manufacturing Labor Productivity, Indonesia Nasution, Nauli Fitriyanni; Wahyuni, Krismanti Tri
JEJAK: Jurnal Ekonomi dan Kebijakan Vol 15, No 1 (2022): March 2022
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jejak.v15i1.33459

Abstract

West Java as a national manufacturing center has experienced industrialization since 1989. This is marked by the continuous increase in the manufacturing sector so that it is able to shift other sectors. Unfortunately, the industrialization that occurred in West Java was not followed by a reduction in the manufacturing labor productivity in West Java. The convergence of manufacturing labor productivity in West Java is an important phenomenon because inequality can lead to a different pace of development and exacerbate inequality. This study uses dynamic panel data regression with the first-different GMM (FD-GMM) method for inferential analysis and Location Quotient (LQ), Klassen Typology and the calculation of the coefficient of variation for descriptive analysis. The results showed that only 7 out of 27 regencies/cities in West Java had the economy dominated by the manufacturing sector and there were fluctuations in the productivity of the manufacturing workforce in these areas. Based on Klassen's Typology, there are still many areas that are categorized as developing and underdeveloped areas. However, there is a decrease in inequality between regions as seen from the results of the convergence analysis. Sigma convergence and beta convergence occurred in West Java with the time needed to close half the gap (half-life convergence) of less than one year. Factors that significantly affect the convergence process of manufacturing labor productivity are the manufacturing labor productivity lag, FDI, DDI, and real wages of manufacturing workers.
Kajian Kebijakan Larangan Ekspor Bijih Nikel Indonesia Fadlillah, Sarafina; Wahyuni, Krismanti Tri
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1740

Abstract

Indonesia, as the world's largest producer of nickel ore, seeks to increase exports of processed nickel by establishing a policy of banning nickel ore exports. However, Indonesia is not among the fifteen largest nickel export countries in the world. This study aims to analyze general picture of Indonesia's processed nickel export volume, and analyze the effect of Indonesia's nickel ore export ban policy and other factors on Indonesia's processed nickel export volume. The methods used are line graphs and Error Correction Mechanism (ECM). In the long run, Indonesia's processed nickel export volume is influenced by the dummy of Peraturan Menteri ESDM Nomor 1 Tahun 2014, dummy of Peraturan Menteri ESDM Nomor 11 Tahun 2019, China's industrial GDP, real exchange rate of rupiah against US dollar, and world nickel processed prices. Meanwhile, in the short term, Indonesia's processed nickel export volume is influenced by the dummy of Peraturan Menteri ESDM Nomor 1 Tahun 2014, China's industrial GDP, and real exchange rate of rupiah against US dollar.
Peranan dan Analisis Faktor Produksi Subsektor Bahan Galian Golongan C di Indonesia: Estimasi Regresi Panel Data Makro Anggraini, I Gusti Ayu Puspita; Wahyuni, Krismanti Tri
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2115

Abstract

The production results of the mining and other quarrying subsectors are often called class C excavations and are mostly used by other sectors as raw materials. The importance of class C excavation for other sectors makes it necessary to increase production output. Production results can be increased by using a combination of inputs that can be seen with the production function. Therefore, this research aims to look at the role and potential of class C minerals, analyze the general description of production and production functions and analyze the stats that influence output. The analytical method used is the panel data regression method with the SUR approach. The research results show that there are 18 provinces with mining and other quarrying subsectors classified as basic or superior. Production output and production factors appear to fluctuate. Variables that influence output were analyzed using the SUR method panel data regression model and it was found that labor, capital and technology had a positive and significant effect on production results, while fuel had a negative and significant effect.
Measuring Well-Being Index with Environmental in Mind: Evidence Forest Land Use in Indonesia Wahyuni, Krismanti Tri; Purwanto, Agung; Sumargo, Bagus; Sitorus, Agnes Vera Yanti; Kurniawan, Robert; Nugroho, Yoga Dwi; Syaifudin, Syaifudin
International Journal of Business, Law, and Education Vol. 5 No. 2 (2024): International Journal of Business, Law, and Education
Publisher : IJBLE Scientific Publications Community Inc.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56442/ijble.v5i2.873

Abstract

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.
A MACHINE LEARNING FRAMEWORK FOR SUICIDAL THOUGHTS PREDICTION USING LOGISTIC REGRESSION AND SMOTE ALGORITHM Berliana, Sarni Maniar; Samosir, Omas Bulan; Karim, Rafidah Abd; Valenzuela, Victoria Pena; Wahyuni, Krismanti Tri; Alfian, Andi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1409-1420

Abstract

Suicide, a global health challenge identified in Goal 3 of the global agenda for enhancing worldwide well-being, demands urgent attention. This study focused on predicting suicidal thoughts using machine learning, leveraging the 2021 National Women's Life Experience Survey (SPHPN) involving women aged 15 to 64. Analyzing 11,305 ever-married women, 504 (4.5%) reported experiencing suicidal thoughts. The outcome variable was binary (1 for suicidal thoughts, 0 for none). The study used seven predictors: age, education level, residence type, physical and sexual violence, smoking frequency, alcohol consumption, and depression. Ordinary logistic regression and SMOTE-based logistic regression were applied. The former identified physical violence, depression, and sexual violence as crucial factors, while the latter emphasized physical violence, sexual violence, and age. In cases of class imbalance, the SMOTE-enhanced model exhibited improved performance in terms of sensitivity, false positive rate, balanced accuracy, and Kappa statistic, with lower standard errors of parameter estimates. The findings highlight the importance of addressing violence and mental health in policies aimed at reducing suicidal thoughts among women. Policymakers can use these insights to develop targeted interventions, and healthcare providers can identify high-risk individuals for timely interventions. Community programs and public health campaigns should promote mental well-being and prevent suicidal behaviors using these findings. Future research should include more predictors, diverse populations, and longitudinal data to better understand causal relationships and timing. Interdisciplinary collaboration and advanced machine learning techniques can enhance predictive accuracy and model interpretability.
Determinants of Green Total Factor Productivity in Indonesia: The Role of Environment in Economic Development with A Parametric Approach Pradiana, Bella; Wahyuni, Krismanti Tri
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 14 No 3 (2024): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Pusat Penelitian Lingkungan Hidup, IPB (PPLH-IPB) dan Program Studi Pengelolaan Sumberdaya Alam dan Lingkungan, IPB (PS. PSL, SPs. IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.14.3.545

Abstract

Environmental degradation occurs during economic development. Green Total Factor Productivity (TFP) was developed by incorporating environmental variables into traditional TFP to measure the efficiency of using technology to produce output, while balancing environmental quality. This study aims to determine the general description of economic development in Indonesia in 2015–2021, estimate economic development, and calculate Green TFP in Indonesia in 2015–2021, know the general description of Green TFP, and the variables that are thought to influence Green TFP in Indonesia in 2015–2021. 2021 and analyzed the variables influencing Green TFP in Indonesia in 2015–2021. The estimation results of the economic growth model showed a trade-off between economic growth and environmental quality in Indonesia. The Green TFP results for provinces in Indonesia are obtained using the Cobb-Douglas production function and panel data regression. The value of Green TFP in Indonesia is stagnant, at approximately 0.002. The analysis of variablesaffecting Green TFP using panel data regression shows that HDI, government spending on education, electricity consumption, industry share, capital structure, and trade openness have significant effects on Green TFP.
Co-Authors Agung Purwanto Alfian, Andi Anggraini, I Gusti Ayu Puspita Bagus Sumargo, Bagus Fadlillah, Sarafina Karim, Rafidah Abd Nasution, Nauli Fitriyanni Nugroho, Yoga Dwi Pradiana, Bella Robert Kurniawan, Robert Samosir, Omas Bulan Sarni Maniar Berliana, Sarni Maniar Sitorus, Agnes Vera Yanti Syaifudin Syaifudin, Syaifudin Valenzuela, Victoria Pena