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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Jurnal Silvikultur Tropika (JST) Jurnal Pustakawan Indonesia Bulletin of Electrical Engineering and Informatics Jurnal Ilmu Komputer dan Agri-Informatika Journal of Degraded and Mining Lands Management Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Scientific Journal of Informatics Edulib JOIN (Jurnal Online Informatika) Jurnal Teknologi dan Sistem Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan Bina Hukum Lingkungan ILKOM Jurnal Ilmiah EDUMATIC: Jurnal Pendidikan Informatika Nusantara Science and Technology Proceedings International Journal of Electronics and Communications Systems Jurnal Pustakawan Indonesia Jurnal Informatika dan Teknologi Informasi Bina Hukum Lingkungan Policy Brief Pertanian, Kelautan, dan Biosains Tropika Scientific Journal of Informatics BACA: Jurnal Dokumentasi dan Informasi
Imas Sukaesih Sitanggang
Department Of Computer Science, Faculty Of Mathematics And Natural Sciences, IPB University, Jl. Meranti Wing 20 Level V, IPB Dramaga Campus Bogor, 16680, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation

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Development of Post Fire Severity Assessment Module in Indonesian Forest and Land Fire Prevention Patrol System Sitanggang, Imas Sukaesih; Hidayat, Assad; Syaufina, Lailan
Jurnal Manajemen Hutan Tropika Vol. 32 No. 1 (2026)
Publisher : Institut Pertanian Bogor (IPB University)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7226/jtfm.32.1.97

Abstract

The severity of forest and land fires is a crucial indicator for assessing their impact on ecosystems, particularly vegetation and soil. The assessment results serve as a foundation for forest and land restoration, rehabilitation, and conservation efforts. This study employs a deep learning algorithm to develop a forest and land fire severity assessment module. The CNN model used is MobileNetV2 that has an accuracy of 88.8%. The smart module is integrated into the Indonesian Forest and Land Fire Prevention Patrol Mobile Application and follows the Software Development Life Cycle approach in its development. Field observation images are input to the CNN module in the mobile application. The module then analyzes the fire severity and classifies it into very light, light, moderate, severe, and very severe categories. Testing results indicate that the module accurately predicts fire severity based on established assessment standards. The optimal time for capturing images is a few days after the fire, during daylight hours, to ensure the majority of images depict burned areas. Additionally, the findings highlight that lighting conditions and image quality significantly influence the accuracy of severity predictions. Further development is required to enhance the module's compatibility and flexibility, enabling its use across various devices.
Hyperparameter tuning of MobileNetV2 on forest and land fire severity classification Hidayat, Assad; Sitanggang, Imas Sukaesih; Syaufina, Lailan
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i2.pp964-972

Abstract

Forest and land fires pose significant environmental challenges, causing economic and ecological damage depending on their severity. This study proposes a deep learning-based classification model to assess fire severity using the MobileNetV2 architecture. A dataset of 560 post-fire images was categorized into five severity levels, with dataset preprocessing involving resizing, rescaling, and image augmentation. To enhance model performance, K-means clustering was applied for balanced data distribution across classes. The model was trained using grid search for hyperparameter tuning, with the optimal combination being a batch size of 8, learning rate of 0.0001, and dropout of 0.3. Training was conducted in 50 epochs, and evaluation using the confusion matrix demonstrated an accuracy of 85%, precision of 86%, and recall of 81%. The results indicate that MobileNetV2 effectively classifies post-fire severity levels, offering a reliable tool for post-disaster assessment. This study highlights the significance of dataset preprocessing and hyperparameter tuning in improving model accuracy. Future research should explore alternative architectures and expand the dataset to enhance model generalization. These findings can aid authorities in assessing fire impact, supporting mitigation strategies, and improving post-fire land management.
Forest and Peatland Fire Severity Assessment at Siak Regency, Riau Province using Sentinel-2 Imagery Afina, Fakhri Sukma; Syaufina, Lailan; Sitanggang, Imas Sukaesih
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 11 No 4 (2021): Journal of Natural Resources and Environmental Management
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.11.4.621-630

Abstract

Siak Regency, Riau Province is one of the most forest and land fire-prone regencies in Indonesia. Most of the fires occur in peatland areas which contributes to the transboundary haze pollution in the region. Despite limited studies, fire severity assessment is an essential step in post-fire activities to estimate ecological impacts and economic impacts and law enforcement. This study aims to estimate fire severity using Sentinel-2 imagery at Siak Regency, Riau Province. The methods applied Normalized Burn Ratio on Sentinel-2 Imagery as an identification model based on reflectance value for 2019 imagery. The study revealed that burned areas in Siak Regency could be classified into four fire severity classes: low fire severity, moderate-low fire severity, moderate-high fire severity, and high fire severity. High fire severity was found mainly at Sungai Apit and Mempura Districts.
Development ETL (Extract, Transform and Load) Module in Indonesian Agricultural Commodities OLAP System Yudhistira, Aditia; Sitanggang, Imas Sukaesih; Adrianto, Hari Agung
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1758.335-343

Abstract

The SOLAP system for Indonesian Agricultural Commodities is a successful development based on previous studies. Agricultural commodity data are managed in a data warehouse with a galactic schema, which has 7 fact tables, namely cut flower horticulture, ornamental plant horticulture, horticulture, food crops, plantation, livestock population, and livestock production, as well as 3 dimensional tables, namely location, time, and commodity. The results of SOLAP operations on the system can be visualized in the form of crosstabs, graphs and maps. The system uses a web platform so that it can be accessed by the public. However, the SOLAP system cannot update data in real time. This study aims to develop a data warehouse for Indonesian Agricultural Commodities SOLAP in real time by creating a scraping system. This study has succeeded in developing a data warehouse in real time on the indonesian agricultural commodity SOLAP system by creating a real time scraping system that is applied to the SOLAP server and has succeeded in making the ETL process run in real time on the SOLAP server and optimizing polygon-based spatial data visualization using the Douglas-Peucker. This study has also carried out functional testing of OLAP features and functions on the Indonesian Agricultural Commodity SOLAP system using the black box testing method. The results of this study provide accurate and real-time data on the SOLAP of Indonesian Agricultural Commodities, with the results of SOLAP feature testing achieving 100 percent pass and the data conformity test results of OLAP function as expected. In addition, the results of this study make it possible to automatically update the data according to a predetermined schedule to provide real-time information.
Co-Authors -, Rachmawati Abdul Rahman Saleh Abdul Wakhid Aditia Yudhistira Afina, Fakhri Sukma Agus Buono Agus Mulyana Agus Purwito Ahmad Khusaeri Albar, Israr Alusyanti Primawati Anak Agung Istri Sri Wiadnyani Andi Nurkholis Andita Wahyuningtyas Anna Qahhariana Annisa Annisa Annisa Annisa Annisa Awal, Elsa Elvira Aziz Kustiyo Baba Barus Badollahi Mustafa Boedi Tjahjono Bramdito, Vandam Caesariadi Despry Nur Annisa Ahmad, Despry Nur Annisa DEWI APRI ASTUTI Dhani Sulistiyo Wibowo Dini Hayati Dwi Purwantoro Sasongko Eddy Prasetyo Nugroho Efendi, Zuliar Erliza Hambali Febriyanti Bifakhlina Firman Ardiansyah Hardhienata, Medria Kusuma Dewi Hari Agung Adrianto Hasibuan, Lailan Sahrina Hefni Effendi Hendra Rahmawan Hendra Rahmawan Herawan, Yoga Heru Sukoco Hidayat, Assad HUSNUL KHOTIMAH I Nengah Surati Jaya Ikhsan kurniawan Irman Hermadi Ivan Maulana Putra Khairani Krisnanto, Ferdian Kurnianto, Andi Lailan Syaufina Lilis Syarifah Luki Abdullah Lukman, Yasmin Medria Kusuma Dewi Hardhienata Miftah Farid Mohammad Farid mufti, abdul Muhammad Abrar Istiadi Muhammad Asyhar Agmalaro Muhammad Murtadha Ramadhan Nia Kurniati Peggy Antonette Soplantila Prasetyo Nugroho, Eddy Pudji Muljono Purwanti , Endang Yuni Purwanti, Endang Yuni Putra, Fiqhri Mulianda Raden Fityan Hakim Raharja, Aditya Cipta Ramadhan, Jeri Rd. Zainal Frihadian Rina Trisminingsih Risa Intan Komaraasih Rizki, Yoze Safrudin, Muhammad Safrul Sakti, Harry Hardian Satyawan, Verda Emmelinda Shelvie Nidya Neyman Sobir Sobir Sonita Veronica Br Barus Sonita Veronica Br Barus Sony Hartono Wijaya Suci Indrawati Irwan Sulistyo Basuki Suradiradja, Kahfi Heryandi Suria Darma Tarigan Surjono Hadi Sutjahjo Syarifah Aini Taihuttu, Helda Yunita Taufik Djatna Taufik Hidayat Tenda, Edwin Tiurma Lumban Gaol Toto Haryanto Trisminingsih, Rina Unik, Mitra Wa Ode Rahma Agus Udaya Manarfa Wattimena, Emanuella M C Wisnu Ananta Kusuma Wulandari WULANDARI Yenni Puspitasari Yoanda, Sely