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All Journal Jurnal Riset Multidisiplin Edukasi Journal of Shariah Economics
Ridwansyah
Universitas Jambi
Religion Economics, Econometrics & Finance Education Social Sciences Other

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Implementasi Triple Bottom Line dan Pengaruhnya Terhadap Pendapatan Usaha di Kecamatan Jambi Timur Kota Jambi Windy Sim; Heriberta; Ridwansyah
Jurnal Riset Multidisiplin Edukasi Vol. 3 No. 4 (2026): Jurnal Riset Multidisiplin Edukasi (April 2026)
Publisher : PT. Hasba Edukasi Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71282/jurmie.v3i4.1821

Abstract

Culinary businesses such as ayam geprek continue to grow rapidly and contribute to local economic activity. The Triple Bottom Line (TBL) framework is one approach that can support business sustainability. This study aims to describe the implementation of the TBL concept and examine its influence on the income of ayam geprek businesses in East Jambi District, Jambi City. The research uses a quantitative approach with descriptive analysis. A saturated sampling method was applied, involving 28 business owners as respondents. Primary data were collected through questionnaires and processed using Microsoft Excel and SPSS. The results show that the economic, social, and environmental aspects of TBL have been applied well, as indicated by the high average scores across indicators. The regression analysis reveals that the economic and social aspects have a positive and significant effect on business income, while the environmental aspect shows a negative and significant effect on the income of ayam geprek businesses in East Jambi District.
Prediksi Kemiskinan Ekstrem di Provinsi Jambi Berbasis Data Mikro SUSENAS: Perbandingan Regresi Logistik, Random Forest, dan XGBoost serta Analisis Determinan Ari Hidayat; Zulgani .; Ridwansyah .; Siti Hodijah; Nurhayani .
JOURNAL OF SHARIA ECONOMICS Vol. 7 No. 2 (2025): Journal of Sharia Economics
Publisher : Program Studi Ekonomi Syariah, Fakultas Ekonomi dan Bisnis Islam, Universitas Al Hikmah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35896/jse.v4i1.1261

Abstract

Extreme poverty is the most severe form of poverty, characterized by a household's inability to meet basic needs and tends to persist despite ongoing social program interventions. In Jambi Province, poverty trends are fluctuating and influenced by macroeconomic dynamics and the agricultural sector; while extreme poverty indicators show an aggregate decline, inequality remains between districts/cities. This study aims to: (1) analyze socioeconomic factors influencing the extreme poverty status of households in Jambi Province, (2) compare the performance of prediction models using econometric approaches (logistic regression) and machine learning (Random Forest and XGBoost), and (3) examine differences in the determinants of extreme poverty between agricultural and non-agricultural households. The data used are SUSENAS microdata for the 2020–2024 period using a pooling approach (cross-section and time series) for all districts/cities in Jambi Province. Extreme poverty status is defined based on the international threshold of USD 2.15 PPP or national adjustment (TNP2K) in the relevant year. Modeling was performed by dividing the training data into 80% and 20% test data, conducting feature selection, model training, and hyperparameter tuning, as well as evaluation based on the confusion matrix and AUC–ROC. In addition to performance evaluation, this study emphasized sectoral comparative analysis by training the model separately on agricultural and non-agricultural subsamples to identify dominant determinants that are both universal and sector-specific.
Co-Authors Ari Hidayat Heriberta Nurhayani . Siti Hodijah Windy Sim Zulgani .