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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Primary: Jurnal Pendidikan Guru Sekolah Dasar Al Fikra : Jurnal Ilmiah Keislaman Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOIV : International Journal on Informatics Visualization Journal of Natural Science and Integration MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Indonesian Physical Review JISKa (Jurnal Informatika Sunan Kalijaga) Scientific Journal of Informatics Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Insearch: Information System Research Journal Journal Automation Computer Information System (JACIS) J-Intech (Journal of Information and Technology) Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Information Technology and Cyber Security
Agung Teguh Wibowo Almais
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Religion Aerospace Engineering Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Physics Social Sciences Other

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Spatial Decision Support System to Determine the Feasibility of Evacuation Posts in Natural Disasters Alviola, Nuril Afni; Almais, Agung Teguh Wibowo; Syauqi, A’la; Chamidy, Totok; A Basid, Puspa Miladin Nuraida Safitri; Anisa, Anisa; Wardana, M. Dafa
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 3 (2025): September 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.3.307-318

Abstract

This study aimed to improve the accuracy of determining the feasibility of evacuation posts after natural disasters using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) within a Spatial Decision Support System (SDSS). A dataset of 50 evacuation posts from the 2021 Mount Semeru eruption was analyzed. The Rank Order Centroid (ROC) method was applied for criteria weighting, and TOPSIS was used to process the data. Results showed 72% accuracy, confirming that TOPSIS is a passable method for assessing post-feasibility based on accessibility, sanitation, and refugee facilities. Although the focus is on evaluating post-disaster evacuation posts, the system can be adapted for use in various other types of disasters. However, it is still dependent on historical data and lacks real-time adaptability. Future research can integrate Artificial Intelligence (AI) and Machine Learning (ML) with real-time data to improve decision-making in disaster management.
Optimasi Extreme Gradient Boosting dengan Particle Swarm Optimization untuk Estimasi Software Effort: Optimized Extreme Gradient Boosting using Particle Swarm Optimization for Software Effort Estimation Alif Pahlevi, Achmad Fahreza; Hariyadi, Mokhammad Amin; Almais, Agung Teguh Wibowo
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 3 (2025): MALCOM July 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i3.2055

Abstract

Estimasi upaya perangkat lunak (SEE) sangat penting dalam manajemen proyek, namun akurasi sering terganggu oleh kompleksitas proyek. Untuk mengatasinya, studi ini mengusulkan metode hibrida inovatif Particle Swarm Optimization (PSO) - Extreme Gradient Boosting (XGBoost) untuk SEE. Algoritma PSO mengoptimalkan hiperparameter XGBoost, meningkatkan kemampuannya memodelkan hubungan nonlinier dalam data proyek perangkat lunak, sehingga mengurangi kesalahan estimasi. Hasil eksperimen pada kumpulan data China dan Nasa93 menunjukkan bahwa PSO-XGBoost secara signifikan mengungguli metode tradisional dan model pembelajaran mesin mandiri. Metode yang diusulkan mencapai Root Mean Square Error (RMSE) yang lebih rendah sebesar 0,024 untuk China dan 0,0653 untuk Nasa93 menunjukkan efektivitasnya dalam memberikan estimasi upaya yang presisi. Meskipun memiliki kompleksitas komputasi dan bergantung pada data berkualitas, studi ini berkontribusi pada bidang SEE dengan menyajikan solusi praktis dan andal, membantu manajer perangkat lunak dalam perencanaan sumber daya dan pengambilan keputusan.
Co-Authors A Basid, Puspa Miladin Nuraida Safitri A'la Syauqi AA Sudharmawan, AA Abd. Rouf Adi Susilo Adinda Dhea Pramitha Afiq Budiawan Ainafatul Nur Muslikah Ainul Yaqin Akbar Roihan Alif Pahlevi, Achmad Fahreza Alviola, Nuril Afni Anis Fatul Fu'adah Anisa Anisa Aniss Fatul Fu'adah Aprilia, Faridha Arief, Yunifa Miftachul Artimordika, Firgy Aulia A’la Syauqi Bunga Puspita, Mayang Cahyo Crysdian Dyah Ayu Wiranti Dyah Febriantina Istiqomah Dyah Wardani Fresy Nugroho Habibiy Idmi, Mohammad Halimahtus Mukminna, Halimahtus Hariyadi, Mokhammad Amin Jesi Alexander Alim Jesi Alexander Alim Khadijah Fahmi Hayati Holle Kurnia Siwi Kinasih Kusuma, Selvia Ferdiana Laela Nurul Qomariyah M. Ainul Yaqin Mandiro, Mulia Anton Mochamad Imamudin Moechammad Sarosa Mokhamad Amin Hariyadi Muhammad Aji Pangestu Muhammad Aziz Muslim Muhammad Fathur Rouf Hasan Mulia Anton Mandiro Musa Thahir Muwardi Sutasoma Neni Hermita Ningtias, Nadila Oktavia Nisrina Darin Farhanah Pizaini Pizaini Pizaini, Pizaini Puan Maharani Kurniawan Putri Purnamasari Rahmatmulya, Revaldi Ramadhan, Rizal Furqan Ririen Kusumawati Roro Inda Melani Safitri, Annisa Heparyanti Sa’adah Rahmaningtyas, Nilmadiana Nur Shinta Rizki Firdina Sugiono Sri Herwiningsih Suhartono Sukir Maryanto Syahiduz Zaman Syauqi, A'la Syauqi, A’la Syawab, Moh Husnus Tanti Rismawati Thahir, Musa Tommy Tanu Wijaya Totok Chamidy Vebrianto, Rian Wardana, M. Dafa