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All Journal IKRA-ITH Informatika : Jurnal Komputer dan Informatika INTECOMS: Journal of Information Technology and Computer Science Jurnal Teknologi Informatika dan Komputer International Journal Software Engineering and Computer Science (IJSECS) Abdi Jurnal Publikasi Bulletin of Network Engineer and Informatics (BUFNETS) CSRID Journal of Informatics and Vocational Education
Arya Adhyaksa Waskita
Universitas Pamulang
Computer Science & IT Education Electrical & Electronics Engineering Social Sciences Other

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Comparative Evaluation of 1D-CNN, LSTM and Hybrid 1D-CNN-LSTM for Rainfall Prediction in Banten Province Hilma Nurul Fauzia Rahman; Arya Adhyaksa Waskita; Tukiyat
Bulletin of Network Engineer and Informatics Vol. 4 No. 2 (2026): BUFNETS (Bulletin of Network Engineer and Informatics) October 2026
Publisher : PT. GWEX NET PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59688/a28w0577

Abstract

Hourly rainfall in Banten Province changes rapidly and varies across locations; therefore, its prediction requires models capable of learning both local patterns and temporal dependencies. This study evaluates one-dimensional Convolutional Neural Network (1D-CNN), Long Short-Term Memory (LSTM), and hybrid 1D-CNN-LSTM models for one-hour-ahead rainfall prediction using GSMaP Now data. The dataset covers 1 January-31 December 2024, 155 subdistricts in eight regencies/cities, and 1,361,520 records. Preprocessing included correction of the -99 code, time-based interpolation, Min-Max normalization fitted on the training data, construction of 6, 12, and 24 hour input windows, and chronological data splitting. The experiment produced 72 training runs and used MAE, MSE, and RMSE for evaluation. Based on the configuration with the lowest testing RMSE in each region, 1D-CNN achieved average MAE, MSE, and RMSE values of 0.39 mm/hour, 1.50 (mm/hour)2, and 1.21 mm/hour. The hybrid model achieved 0.38 mm/hour, 1.43 (mm/hour)2, and 1.19 mm/hour, whereas LSTM obtained the lowest values of 0.35 mm/hour, 1.32 (mm/hour)2, and 1.14 mm/hour. LSTM was the best model in all regions, although the optimal input window varied between 6 and 24 hours.
Co-Authors Abdul Haris Achmad Hindasyah Agung Budi Susanto Agung Budi Sutanto Agung Sutopo Choirul Basir Diah Ariefianty Ferdiansyah Winardi Ferhat Aziz Ferry Setefanus Hilma Nurul Fauzia Rahman Indriyani Astuti Iwan Muttaqin Muhammad Al-Farisy Putu Dedi Juliana Risko Sahrul Ramadhan Sapta Nugraha Sarnubih Hasan Syarif Hidayatullah Tri Nurmayati Tukiyat