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All Journal MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management MEDIA KONSERVASI Forum Pasca Sarjana FORESTA BIOTROPIA - The Southeast Asian Journal of Tropical Biology TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknosains Jurnal Penelitian Hutan dan Konservasi Alam Jurnal Penelitian Hutan Tanaman Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) BERITA BIOLOGI JURNAL BIOLOGI INDONESIA MAJALAH ILMIAH GLOBE International Journal of Remote Sensing and Earth Sciences (IJReSES) Journal of Sylva Indonesiana Indonesian Journal of Electrical Engineering and Computer Science Jurnal Risalah Kebijakan Pertanian dan Lingkungan International Journal of Electronics and Communications Systems Aceh International Journal of Science and Technology Jurnal Penelitian Kehutanan Wallacea
I Nengah Surati Jaya
Department Of Forest Management, Faculty Of Forestry, Bogor Agricultural University, Academic Ring Road, Campus IPB Dramaga, PO Box 168, Bogor, Indonesia, 16680
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Veterinary

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Application of Random Forest Algorithm to Analyze the Confidence Level of Forest Fire Hotspots in Riau Peatland Unik, Mitra; Sukaesih Sitanggang, Imas; Syaufina, Lailan; Surati Jaya, I Nengah
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 15 No 2 (2025): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Pusat Penelitian Lingkungan Hidup, IPB (PPLH-IPB) dan Program Studi Pengelolaan Sumberdaya Alam dan Lingkungan, IPB (PS. PSL, SPs. IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.15.2.255

Abstract

Forest fires pose a significant challenge in Riau Province, Indonesia, especially in peatland areas. This study employs the Random Forest (RF) algorithm to analyze the confidence levels of hotspots, aiming to predict potential fire occurrences and improve fire management strategies. The research focuses on peatlands spanning 3.86 million ha, using key variables such as NDVI, surface temperature, and peat thickness derived from satellite data. The model achieved an average AUC of 0.732 and a classification accuracy of 70.3%, with medium-confidence hotspots demonstrating the best predictive performance (AUC: 0.707, F1-score: 0.804). However, the model struggled with low-confidence hotspots, reflecting challenges in distinguishing less prominent patterns in the data. Compared to other methods, RF demonstrates strong potential in handling complex environmental datasets, making it a valuable tool for hotspot prediction. This study contributes to understanding forest fire risks in peatlands and provides actionable insights for improving preparedness and mitigation efforts.
Exploration of Data Handling Techniques to Improve PM2.5 Prediction Using Machine Learning Unik, Mitra; Sitanggang, Imas Sukaesih; Syaufina, Lailan; Jaya, I Nengah Surati
International Journal of Electronics and Communications Systems Vol. 5 No. 1 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i1.25687

Abstract

Particulate matter (PM₂.₅) is one of the most dangerous air pollutants because it can penetrate the respiratory system and cause serious health problems. Amidst the limitations of a real-time and comprehensive air quality monitoring system, a data-driven predictive approach is needed that can accurately project PM₂.₅ concentrations. This study aims to develop a PM₂ concentration prediction model using the Random Forest Regressor (RFR) algorithm optimised through a series of data pre-processing techniques. The pre-processing techniques include outlier detection with four methods (Isolation Forest, Autoencoder ANN, OCSVM, IQR) and missing value handling using three approaches (Spline Cubic Interpolation, Nearest Point Interpolation, Data Removal). The daily data used covered 12 environmental variables (including rainfall, temperature, relative humidity, AOD, and NDVI) from the period of March 2022 to March 2023, with PM₂.₅ as the target. The RFR model was built with 100 decision trees and 10-fold cross-validation to improve accuracy. Results showed the combination of IQR (outlier detection) and data deletion (missing values) produced the best performance with RMSE 0.082, MAE 0.027, and R² 0.886. The most influential variables were temperature (TEMP), relative humidity (RHU), and evapotranspiration (ET). This research contributes to the development of an accurate air quality prediction model, supporting the mitigation of PM₂.₅ pollution impacts on public health
Co-Authors Abdul Rosyid Adelia Juli Kardika Agung Budi Cahyono Agung Budi Cahyono Agus P. Kartono Ahyar Gunawan Andry Indrawan Anita Zaitunah Anita Zaitunah Antonius B Wijanarto Antonius B Wijanarto Antonius B Wijanarto Bambang Hero Saharjo Bambang Sapto Pratomosunu Bejo Slamet Beni Iskandar Boedi Tjahjono Bramasto Nugroho Budi Kuncahyo Cecep Kusmana Dahlan Dahlan Dahlan Dahlan Darwo Darwo Darwo Darwo Dede Dirgahayu Dewayany Sutrisno Dewayany Sutrisno Diana Septriana Dito Cahya Renaldi Dito Cahya Renaldi Dwi Noventasari Dwi Putra Apriyanto Dwi Shanty Apriliani Gunadi Elias Elias Ema Kurnia ENDANG SUHENDANG Endang Suhendang Endang Suhendang Suhendang Endes Nurfilmarasa Dahlan Eva Achmad F Gunarwan Suratmo Fahmi Amhar Faid Abdul Manan Fairus Mulia Fairus Mulia Farida H. Susanty Farida Herry Susanty Farida Herry Susanty Florentina Sri Hardiyanti Purwadhi Hanifah Ikhsani Hardian, Dwika Hardjanto Hardjanto Hardjanto Hariaji Setiawan Haryo Tabah Wibisono Hasriani Muis Hendrayanto . Hendri Nurwanto Hermanu Triwidodo Herry Purnomo Herry Purnomo Hidayat Pawitan I Gusti Bagus Wiksuana Iin Arianti Imas Sukaesih Sitanggang Irdika Mansur Ismail HJ Hashim Israr Albar Ita Carolita Iwan Gunawan Jarunton Boonyanuphap Kartodihardjo, Hariadi Kukuh Murtilakono Kukuh Murtilaksono Kukuh Murtilaksono Kusnadi Lailan Syaufina LILIK BUDIPRASETYO Liu Qian Liu Qian Lukman Hakim Lukman Mulyanto M. Bismark Makin Basuki Marlina, Etty Moch. Anwar Muhammad Ardiansyah Muhammad Buce Saleh Muhammad Ikhwan Mulyaningrum Mulyaningrum Muzailin Affan Muzailin Affan N Nurhendra Naik Sinukaban Naik Sinukaban Nanin Anggraini Nining Puspaningsih Nitya Ade Santi Nitya Ade Santi Nitya Ade Santi Nitya Ade Santi Nobuyuki Abe Nurdin Sulistiyono Omo Rusdiana Oteng Haridjaja Oteng Haridjaja Patrich Phill Edrich Papilaya Pratiwi Pratiwi Pratiwi Pratiwi Purnama, Edwin Setia R Assyfa El Lestari Rahimahyuni Fatmi Noor'an Robert Parulian Silalahi Rudi Ichsan Ismail Samsuri Samsuri Samsuri Samsuri Samsuri Samsuri Samsuri, Samsuri Sendi Yusandi Sigit Nugroho Soedari Hardjoprajitno Sri Wahyuni Suria Darma Tarigan Susilawati Suyadi Suyadi Suyadi Suyadi Syamsu Rijal Tatang Tiryana Teddy Rusolono Tien Lastini Tien Lastini Tirta Negara Tirta Negara Tomi Yuwono Tomi Yuwono, Tomi Unik, Mitra Uus Saepul Mukarom Wang Xuenjun Wang Xuenjun Wibisono, Haryo Tabah Wibisono, Haryo Tabah Wibisono, Haryo Tabah Widi Atmaka Widyananto Basuki Aryono Wijanarto, Antonius B. Wijanarto, Antonius B. Yadi Setiadi YANTO SANTOSA Zhang Yuxing