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All Journal Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknik Elektro Lembaran Ilmu Kependidikan Media Ilmu Keolahragaan Indonesia Rekayasa: Jurnal Penerapan Teknologi dan Pembelajaran Sainteknol : Jurnal Sains dan Teknologi ELINVO (Electronics, Informatics, and Vocational Education) CESS (Journal of Computer Engineering, System and Science) Edu Komputika Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal Cyber Security dan Forensik Digital (CSFD) Jurnal Teknik Informatika (JUTIF) Jurnal Energi Baru dan Terbarukan Electron: Jurnal Ilmiah Teknik Elektro Jurnal Rekayasa elektrika Jurnal Pengabdian Dinamika
Feddy Setio Pribadi
Jurusan Teknik Elektro, Fakultas Teknik, Universitas Negeri Semarang
Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Nursing Public Health Social Sciences Veterinary

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Journal : KOMPUTIKA - Jurnal Sistem Komputer

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Prediksi Kabut Menggunakan Recurrent Neural Network dengan Attention Mechanism di Bandara Ruteng Wiujianna, Atri; Pribadi, Feddy Setio; Djuniadi, Djuniadi; Sunarno, Sunarno; Iqbal, Iqbal
Komputika : Jurnal Sistem Komputer Vol. 14 No. 1 (2025): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v14i1.15380

Abstract

Fog phenomena pose a significant challenge in aviation operations, particularly in regions with complex topography such as Ruteng Airport. Thick fog can reduce visibility and increase flight safety risks. This study aims to develop a deep learning-based fog prediction model by comparing the performance of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) enhanced with Attention Mechanism (AM). The dataset consists of 61,187 entries, covering hourly recorded weather parameters over the past ten years (2013–2023). The experimental results show that the addition of Attention significantly improves model performance. The RNN+Attention model emerges as the best-performing model with an accuracy of 0.9981, precision of 0.7755, recall of 0.76, and F1-score of 0.7677, along with the lowest number of False Positives. Meanwhile, the LSTM+Attention model excels in reducing False Negatives, making it suitable for systems prioritizing comprehensive fog detection. Models without Attention demonstrate perfect recall (1.00), but their low precision indicates overfitting. Overall, the integration of the Attention Mechanism enhances the balance between recall and precision and improves model reliability in handling data imbalance. The contribution of this research is that it can serve as a reference for future studies in developing artificial intelligence-based weather prediction models, particularly in addressing fog phenomena. Keywords – Attention Mechanism; Long Short-Term Memory; Fog Prediction; Recurrent Neural Network
Co-Authors Adhistya Erna Permanasari Adiastoro, Mahendra Agus Suryanto Akbar, Dawam Muhammad Akbar, Dawam Muhammad Al Kindi, Bilal Alam, Mohammad Mahruf Alfian Nur Rahmad, Alfian Nur Alkindi, Muhammad Faizal Ananda, Briska Putra Andriano, Niko Andriyani, Ririn Anggraini Mulwinda Aprilianto, Rizky Ajie Arundaya, Adil Arvina Rizqi Nurul’aini Ati Zuhrotal Afifah, Ning Imas Aviando, Rizqi Awang Harizka, Awang Daniel Happy Putra Djuniadi , Djuniadi Djuniadi Djuniadi Eko Supraptono Fahreza, Rizqy Achmad Faqih, Faiq Mananul Febriantika, Febriantika Hardi, Septian Akbar Noor Wahyu Hesti Wahyu Nugroho, Hesti Wahyu Hirroe Wijaya Ani Kesuma, Hirroe Wijaya Ani Iqbal Iqbal Irwan Irwan Karnisih, Karnisih Kitnas Dian Purwitasari, Kitnas Dian Ningtyas, Mega Wahyu Nurul'aini, Arvina Rizqi Octavianti Paramita Paramita, Octavianti Pongoh, Arthur Gregorius Prima Astuti Handayani Putri, Melinia Rahmahani Rizky Ajie Aprilianto Rusiyanto Rusiyanto, Rusiyanto Samsudin Anis Setiawan Sariyoga, Setiawan Sri Haryono Sri Haryono Sri Sukamta Sri Suning Kusumawardani Sunarno Sunarno Suryanto, Agus Ulfah Mediaty Arief Uswatun Hasanah Wiujianna, Atri Yanuar Arif Pramana