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Muhammad Arif
Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Economics, Econometrics & Finance

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Urban Poverty (Case Study of East Java from 2018-2022) Alfinta Lestianpuri; Muhammad Arif
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 8 No 1 (2025): Sharia Economics
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v8i2.6022

Abstract

This study seeks to assess how average years of schooling, job opportunities, population density, and local revenue affect poverty in nine cities within East Java Province from 2018 to 2022. The research utilizes secondary data and adopts a quantitative approach. A panel data regression method using a Fixed Effect Model (FEM) is employed. Findings indicate that average years of schooling, employment opportunities, and population density all have a significant negative impact on urban poverty. In contrast, Regional Original Income does not significantly affect urban poverty. It is crucial for the government to effectively manage local revenue to ensure equitable distribution among the population, particularly benefiting the poor.
Determinants of Female Labor Force Participation Rate in 2019-2023 in 34 Provinces of Indonesia Avista Nur Aini; Muhammad Arif
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 8 No 1 (2025): Sharia Economics
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v8i1.6309

Abstract

This study examines the determinants of the Female Labor Force Participation Rate (FLFPR) across 34 provinces in Indonesia from 2019 to 2023, utilizing secondary panel data from the Indonesian Statistics Agency (BPS). Guided by relevant labor economics theories and prior empirical studies, this research considers key socioeconomic factors, including Female Labor Force Participation Rate (FLFPR), Average Years of Schooling (AYS), Life Expectancy of Women, Marital Status of Women, and Adjusted Per Capita Expenditure. Panel data regression analysis is conducted using the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM), with model selection based on Chow and Hausman tests. Diagnostic tests are applied to address potential issues such as autocorrelation and heteroskedasticity, ensuring the robustness of results. Findings indicate that the FEM is the most suitable model, explaining 98.05% of the variation in FLFPR. Women's education, life expectancy, and per capita expenditure significantly influence FLFPR, while the marital status of women aged 20-24 does not show a significant impact. This unexpected result suggests the need for further exploration of regional and cultural differences in marriage and labor participation. Policy recommendations emphasize expanding educational access, improving healthcare services, and promoting women's economic independence. Future research should incorporate additional explanatory variables and alternative econometric approaches for a more comprehensive analysis.
Analysis of the Impact of MSMEs, Wage Levels, Population Size, and Education Levels on Unemployment in East Java Province Marisa Kurniawati; Muhammad Arif
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 8 No 2 (2025): Sharia Economics
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v8i2.6483

Abstract

Unemployment remains a significant socioeconomic concern, diminishing both productivity and income while potentially triggering broader societal issues. This study investigates how Micro, Small, and Medium Enterprises (MSMEs), wage levels, population size, and education levels affect unemployment rates across districts and cities in East Java Province from 2019 to 2023. Utilizing secondary data sourced from the Central Bureau of Statistics (BPS), this research applies panel data analysis, integrating time series data from 2019 to 2023 with cross-sectional data from 39 districts and cities. Three regression models Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM) were examined, with the Fixed Effect Model (FEM) determined as the most suitable approach. Findings reveal that the independent variables collectively influence unemployment rates, as evidenced by an F-statistic of 10.87244 and a p-value of 0.000000, signifying strong statistical relevance. Further analysis reveals that wage levels negatively affect unemployment, implying that higher wages reduce unemployment rates. Meanwhile, population size and education levels positively influence unemployment, suggesting that an increasing population and higher education levels do not necessarily lead to lower unemployment. Interestingly, the study finds that MSMEs do not significantly impact unemployment rates in East Java.
Co-Authors Alfinta Lestianpuri Avista Nur Aini Marisa Kurniawati