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All Journal VALENSI Voteteknika (Vocational Teknik Elektronika dan Informatika) BAREKENG: Jurnal Ilmu Matematika dan Terapan INTECOMS: Journal of Information Technology and Computer Science Jiko (Jurnal Informatika dan komputer) Jurnal Kartika Kimia JURIKOM (Jurnal Riset Komputer) Jurnal ICT : Information Communication & Technology JATI (Jurnal Mahasiswa Teknik Informatika) Informatics and Digital Expert (INDEX) Journal of Applied Computer Science and Technology (JACOST) International Journal of Quantitative Research and Modeling Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma IJESPG (International Journal of Engineering, Economic, Social Politic and Government) journal Jurnal Matematika Integratif Jurnal Sains dan Kesehatan
Melina Melina
Jurusan Teknik Informatika, Fakultas Sains Dan Informatika, Universitas Jenderal Achmad Yani
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation

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Journal : Jurnal Algoritma

 1 
Prediksi Curah Hujan Menggunakan Metode Bi-LSTM dan GRU Berbasis Data Iklim Abdillah, Fajrul; Hadiana, Asep Id; Melina, Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2305

Abstract

As a tropical country, Indonesia faces great challenges in predicting rainfall due to increasingly dynamic climate change. This study aims to predict rainfall in an urban area in West Java with tropical climate characteristics using deep learning methods, namely Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Unit (GRU) based on climate data collected from local meteorological stations. The results show that the Bi-LSTM method provides more stable prediction performance with a Mean Absolute Error (MAE) value of 0.0108 and a Root Mean Squared Error (RMSE) of 0.0158. In contrast, the GRU method produced variable performance with higher MAE and RMSE values in some test scenarios. The main findings of this study indicate that the BiLSTM model has a higher level of accuracy, making it an effective information technology solution to support disaster mitigation and agricultural sector planning in climatically complex regions.
Klasifikasi Penyakit Monkeypox dengan XGBoost dan SMOTE untuk Penanganan Data Tidak Seimbang Illawati, Adinda Rahma; Hadiana, Asep Id; Melina, Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2349

Abstract

Monkeypox merupakan penyakit menular yang penyebarannya cepat dan memerlukan sistem deteksi dini yang akurat. Penelitian ini bertujuan mengembangkan model klasifikasi penyakit monkeypox dengan mengatasi permasalahan ketidakseimbangan data. Metode yang digunakan adalah Extreme Gradient Boosting (XGBoost) yang dikombinasikan dengan teknik Synthetic Minority Over-sampling Technique (SMOTE). Evaluasi model menggunakan Confusion Matrix dengan hasil akurasi 69%, presisi sebesar 0.69, recall sebesar 0.93, dan F1-score sebesar 0.79. Selain itu, nilai Area Under Curve - Receiver Operating Characteristic (AUC-ROC) mencapai 0.68. Penelitian ini menunjukkan bahwa kombinasi SMOTE dan XGBoost dapat mengatasi ketidakseimbangan data dan meningkatkan deteksi kelas minoritas, sehingga memberikan kontribusi dalam pengembangan sistem deteksi dini penyakit menular secara lebih akurat dan efisien.
Evaluasi Kualitas Klaster Wilayah Rawan Bencana Menggunakan K-Means dengan Silhouette dan Elbow Method Sudrajat, Risqi; Hadiana, Asep Id; Melina, Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2379

Abstract

Natural disasters such as floods, earthquakes, and landslides are recurring threats in Cirebon City, West Java. This study aims to classify disaster-prone areas using the K-Means algorithm based on 1,144 incident data from Open Data Jabar. The data were grouped into three clusters, namely safe, moderate, and dangerous. Cluster quality was evaluated using the Silhouette Score and Elbow Method. The results of this study show that the model without normalization produced a score of 0.6804, reflecting good cluster separation. Conversely, the application of MinMaxScaler normalization significantly reduced the model's performance, with a score of 0.3900. The main contribution of this study is to show that data normalization can disrupt the natural pattern of risk distribution, thereby reducing the quality of clustering. Therefore, the selection of pre-processing techniques needs to be adjusted to the characteristics of local data. It is hoped that this study can be the basis for the development of a more adaptive and data-driven disaster mitigation decision support system.
Co-Authors Abdillah, Fajrul Agus Komarudin Agus Komarudin Ahmad Marjan Akbar Mulya Hadi Ali, Moch. Dzikri Azhari Ardiyansyah, Muhamad Salman Asep Rizaludin Azhari, Moch Dzikri Benedictus Benny Sihotang Cecep Jamaludin Devitri Amisa Dewi Novianti Diana Lupitasari Dudi Darmawan Eddie Khrisna Putra Eina, Muhammad Fikri Emia Rosta Br. Sebayang Endang Rosdiana Fahmi Yusron Fiddin Fajri Rakhmat Umbara Farhan Fadilah Fuji Astari, Dhea Hadiana, Asep Id Herlina Napitupulu Hernandi Sujono Illawati, Adinda Rahma Ilyas, Rid Kasyidi, Fatan Komarudin, Agus Levi Sabili, Naufal Lia Dewi Juliawaty Lia Dewi Juliawaty Monica, Taris Muthmainah, Sekar Ghaida Nabilla, Ulya Nia Sri Hardianti Norizan Mohamed Octo Emerald Siregar Oktaviani, Ayu Nur Putra, Eddie Krishna Rahmat Awaludin Salam Razaki, Adam Restianim, Vivien Reza Fauzi Iskandar Rezky Yuniarti Ridwan Ilyas Senadi Budiman Sudrajat, Risqi Sukono Sukono Sukrido Sukrido Sumantri, Fithra Aditya Tanjung, Irvan Tia Setiawati Valentina Adimurti Kusumaningtyas Wina Witanti Yana Maolana Syah Yana Maolana Syah Yuliana, Trisna Yulison Herry Chrisnanto