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All Journal International Journal of Advances in Applied Sciences Jurnal Sains dan Teknologi Nuklir Indonesia (Indonesian Journal of Nuclear Science and Technology) Jurnal Fisika Unand Jurnal Sains & Teknologi Lingkungan JC-T (Journal Cis-Trans): Jurnal Kimia dan Terapannya Warta Ardhia : Jurnal Perhubungan Udara Jurnal Environmental Science JOURNAL OF CIVIL ENGINEERING, BUILDING AND TRANSPORTATION Jurnal Meteorologi Klimatologi dan Geofisika Jurnal Rekayasa Hijau To Maega: Jurnal Pengabdian Masyarakat Variance : Journal of Statistics and Its Applications Jurnal EnviScience (Environment Science) Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jurnal Kolaboratif Sains DiJITAC : Digital Journal of Information Technology and Communication Jurnal Kesehatan dan Pengelolaan Lingkungan Geosfera: Jurnal Penelitian Geografi Jurnal Widya Climago Jurnal Laut Pulau
Agung Hari Saputra
Sekolah Tinggi Meteorologi Klimatologi Dan Geofisika
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Journal : Variance : Journal of Statistics and Its Applications

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PERFORMANCE COMPARISON OF DECISION TREE MODELS FOR PM10 PREDICTION IN JAKARTA Syahrin, Khairummin Alfi; Saputra, Agung Hari
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 1 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

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Abstract

PM10 are airborne particulates that have a diameter of ≤10 μm. The potential hazards of PM10 particulates are an issue that is being intensified by many researchers. This research utilizes PyCaret, a library to accelerate the process of modeling and experimentation in the field of machine learning (ML) and data science. This research compares the performance of three decision tree-based models Extra Trees, Random Forest, and XGBoost in predicting PM10 particulate levels, presenting data and visualizations for each models predictions. The data used is ISPU data at five air quality monitoring stations in Jakarta, with the main dataset of PM10 in 2021. The forecast results show an increasing graph pattern, with higher fluctuations in XGBoost. The Extra Trees model produces the best performance, with MASE 0.8808, RMSSE 0.8113, MAE 12.6173, RMSE 14.7436, MAPE 0.2433, SMAPE 0.207, and R² -1.2013.
Co-Authors Adzan, Muhizzadin Abdul Agustina Rachmawardani Arief Yuniarto Arif Yuniarto Aritonang, Binsar Hakim Arno, Giarno Aulia Nisaul Khoir Azwar Makarim Aldimasqie Cahya Sugiarto Deni Septiadi Disera, Tiara Emanuella Faiz Ahza Ramadhan Fauzi, Naufal Kamil Febby Debora Abigael Giananti, Attiya Shakila Hanggadireksa, Bimo Hani Elindra Hariadi Hariadi Indah Sary Jannata, Juan Idhar M. Arifudin, M. Arifudin Manullang, Safri Merdeka, Juang Muhammad Elifant Yuggotomo Muhammad Zaidan Hakim Musyaffa, Faqih Nanda Putri Kinanti Nesty Youwe, Angelina Serena Gracella Ni Made Orcidia Wulaning Sari Sari Novianti, Rima Novvria Sagita Nugraheni, Imma Redha Nur Riska Lukita Pangestu, Titis Angger Pramuji, Veimas Mahardika Putri, Ashifa Rayhan Rivaniputra Rendy Syahril Amanu Rista Hernandi Virgianto Rohman, Muhammad Faisal Rosyady, Muhammad Panji Sirly Oktarina Sirly Oktarina Syahputra, Rizki Syahrin, Khairummin Alfi Takdir, Muhammad Zaqi Fikanza Taruna, I Wayan Jyesta Jaya Taufiqi, Rafli Iqbal Thenu, Christy Anastasya Yosik Norman Yudistira, Ricko Yusron Faiz Athallah Zikri, Muhammad Aulia