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All Journal JURNAL DINAMIKA EKONOMI PEMBANGUNAN Jurnal Teknologi dan Sistem Komputer
Kurniawan, Bayu Dwi
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering

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Perbandingan Metode Ensemble Machine Learning untuk Klasifikasi Tenaga Kerja di Indonesia dengan Random Forest, XGBoost, dan CatBoost Kurniawan, Bayu Dwi; Wijayanto, Arie Wahyu
Jurnal Teknologi dan Sistem Komputer [IN PRESS] Volume 10, Issue 4, Year 2022 (October 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14031

Abstract

Survei Angkatan Kerja Nasional (Sakernas) adalah survei periodik yang besar sehingga membutuhkan pengolahan data  kompleks serta validasi benar untuk menjaga kualitas data. Salah satu pertanyaan Sakernas yang pengisian dan validasinya secara manual yaitu lapangan pekerjaan utama. Untuk memberikan validasi, Machine Learning dapat diterapkan dengan memanfaatkan informasi pada isian lain. Penelitian ini menggunakan metode Random Forest, XGBoost, dan CatBoost untuk klasifikasi lapangan pekerjaan utama pada Sakernas Agustus 2019. Berdasarkan hasil, ketiga model memiliki performa yang hampir sama baik dari presisi, recall, dan f1 yaitu untuk sektor primer dan tersier diatas 90 % dan sektor sekunder sebesar 80%. Model dari Random Forest, XGBoost, dan CatBoost memiliki akurasi sebesar 91,80%; 90,88%; dan 91,84%. Nilai Area Under Curve (AUC) dari ketiga model relatif tinggi dengan CatBoost memiliki nilai tertinggi pada klasifikasi sektor primer, sekunder, dan tersier masing-masing sebesar 1,00; 0,97; dan 0,98.
Pemetaan Potensi Pengembangan Desa Agroindustri: Membangun Pusat Pertumbuhan Ekonomi Baru melalui Hilirisasi dari Desa di Jawa Tengah Satrio, Roni Anom; Kurniawan, Bayu Dwi
Jurnal Dinamika Ekonomi Pembangunan Vol 8 (2025): Special Issue: Call for Paper Pusaka Jateng
Publisher : Fakultas Ekonomika dan Bisnis, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jdep.8.0.169-190

Abstract

This paper examines rural economic transformation in Central Java Province with a focus on village-based agroindustrial downstreaming. The study develops an Agroindustrial Village Development Potential Index (IPPDA) using factor analysis. The index captures five dimensions, including rural infrastructure, digitalization, village institutions, industrial activities, and access to energy. The results show that villages with high development potential are located in areas with strong infrastructure, institutional capacity, and economic activity. Villages with low potential are mostly found in highland regions and face constraints related to energy access, digital connectivity, and limited integration into local value chains. Spatial panel analysis shows that Village Original Income, Village-Owned Enterprises, and digitalization play a significant role in promoting agro sector development and industrialization. The analysis also identifies positive spatial spillover effects across districts. At the provincial level, agriculture plays a key role in supporting agroindustrial downstreaming. Central Java acts as an important hub within interregional agroindustrial value chains across Java, Bali, Nusa Tenggara, and eastern Sumatra. The findings highlight the importance of developing village-based agroindustrial clusters, strengthening local institutions, improving access to finance, and enhancing agro logistics connectivity.
Co-Authors Arie Wahyu Wijayanto Satrio, Roni Anom