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Budi Susetyo
School Of Data Science, Mathematics, And Informatics, IPB University, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Journal : statistika

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Interpretable Tree-Based Models for Identifying Youth Not in Employment, Education, or Training Siti Nur Azizah; Nabila Syukri; Mauizatun Hasanah; Nimas Ayu Hapsari; Bagus Sartono; Aulia Rizki Firdawanti; Budi Susetyo; Gerry Alfa Dito
Statistika Vol. 26 No. 1 (2026): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v26i1.9117

Abstract

Abstract. Youth Not in Employment, Education, or Training (NEET) is an important indicator in evaluating the extent to which Indonesia's demographic bonus can be optimally utilized. West Java, as the province with the largest number of young people and a NEET rate above the national average, is a strategic context for analysis. Using large-scale SUSENAS 2024 data with class imbalance, this study aims to: (1) compare the performance of Decision Tree, Random Forest, and XGBoost in predicting NEET status under various class imbalance handling strategies; (2) identify key features contributing to predictions using SHAP; and (3) identify NEET typologies based on feature contribution similarities. The Random Forest–Class Weight model showed the best performance with a balanced accuracy of 0.7519. SHAP analysis identified eight key predictors contributing to NEET status, namely age, highest level of education, per capita expenditure, savings account ownership, access to financial services, marital status, KIP/PIP receipt, and gender. Local SHAP-value-based clustering yielded five NEET profiles with distinct combinations of risk factors. Two clusters showed the most distinct risk patterns, each characterized by economic vulnerability and limitations due to domestic roles, making them most easily recognized by the model, while the other clusters showed more complex risk patterns. These findings indicate that NEET status is formed through various risk pathways influenced by economic, educational, and demographic factors, thus requiring the formulation of more targeted policies.
Co-Authors A. Qeis Tenridapi Aam Alamudi Aceng Komarudin Mutaqin Ade Riyawan Aditya Ramadhan adwendi, satria june Agus Mohamad Soleh Ahmad Ansori Mattjik Aji Hamim Wigena Akbar Rizki Anak Agung Istri Sri Wiadnyani Anang Kurnia Andi Illa Erviani Nensi Andina Fahriya Anik Djuraidah Anis Sulistiyowati ASEP SAEFUDDIN Assyifa Lala Pratiwi Hamid Asyifah Qalbi Aulia Dwi Oktavia Aulia Rizki Firdawanti Aunuddin Aunuddin Bagus Sartono Bambang H. Trisasongko Bambang Juanda Brian G. Lees Cici Suhaeni Cici Suhaeni Cut N. Ummu Athiyah DAMAYANTI BUCHORI Darfiana Nur Dela Gustiara Dewi Jasmina Dewi Jasmina, Dewi Dhea Dewanti Dian Kurniasari Dian Kurniasari Dito, Gerry Alfa Dyah R. Panuju Endah Febrianti Erfiani Erfiani Erfiani Fadjrian Imran Fahriya, Andina Faisal Arkan Farit Mochamad Afendi Fitrianto, Anwar Gerry Alfa Dito H Karwono Hafidz Muksin Hari Wijayanto Hazelita Dwi Rahmasari Herlina Herlina Hermawati, Neni I Gusti Ngurah Sentana Putra I Made Sumertajaya Inayatul Izzati Diana Yusuf Indahwati Indahwati Indahwati Indahwati, NFN Intan Juliana Panjaitan Iswan Achlan Setiawan Izzati Rahmi HG Jap Ee Jia Jia, Jap Ee Karwono, H Kesuma Millati Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Kristuisno Martsuyanto Kapiluka Kriswan, Suliana Kusman Sadik Kusni Rohani Rumahorbo La Ode Abdul Rahman La Ode Abdul Rahman La Ode Abdul Rahman M Nur Aidi M Nur Aidi, M Nur Mahda Al Maida Mahmud A. Raimadoya Mardatunnisa Isnaini Mauizatun Hasanah Meavi Cintani Mega Maulina Mohammad Masjkur Muh Nur Fiqri Adham Muhammad Amirullah Yusuf Albasia Muhammad Nur Aidi Muhammad Nur Aidi Muhammad Sayuti Mustofa Usman Nabila Syukri Nimas Ayu Hapsari Nur'aini Nurfadilah, Khalilah Nurfajrin, Tria Ermina Nurul Qomariasih Pannu, Abdullah Pika Silvianti Pika Silvianti Qalbi, Asyifah Qomariasih, Nurul Rachman, Nurul Aulia Rahma Anisa Rahmawat, NFN Rahmawati, nFN Rais Ratnasari, Andika Putri Rifannisa Bahar Rifki Hamdani Rizki Alifah Putri Rizqi Annafi Muhadi Safitri, Wa Ode Rahmalia Sanusi, Ratna Nur Mustika Satriyo Wibowo Sembiring, Febryna Shalshabilla Shafa Siti Nur Azizah Sri Amaliya Sri Ningsih Desi Afriany Sulandra, Ardelia Maharani Sulfikar Amir Suliana Kriswan Supriatin, Febriyani Eka Syahrir, Nur Hilal A. Syahrir, Nur Hilal A. Syella Zignora Limba Sylvia P. Soetantyo Tina Aris Perhati Tiya Wulandari Ulfa Afilia Shofa Utami Dyah Syafitri Wan Muhamad, Wan Zuki Azman Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Windi Pangesti Wulan Andriyani Pangestu Yani Prihantini Hiola Yasmin Erika Faridhan Zahira Rahvenia Robert Zainal A Koemadji Zulhijrah