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All Journal Jurnal Mandiri IT Journal of Artificial Intelligence and Digital Business
Aslam, Muhammad Nur
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Library & Information Science Mathematics

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Penerapan Metode Fuzzy Mamdani dalam Prediksi Cuaca di Tegal Aslam, Muhammad Nur; Surorejo, Sarif; Utami, Erni Unggul Sedya
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2357

Abstract

Penelitian ini membahas penerapan metode Fuzzy Mamdani untuk memprediksi kondisi cuaca di Kabupaten Tegal dengan memanfaatkan tiga variabel utama, yaitu suhu udara, kelembapan udara, dan kecepatan angin. Data cuaca diperoleh dari BMKG Tegal periode 2024–2025 dan diolah melalui proses fuzzifikasi, pembentukan aturan IF–THEN, inferensi fuzzy, dan defuzzifikasi menggunakan metode centroid. Sistem yang dibangun menghasilkan prediksi cuaca berupa kategori “cerah”, “berawan”, “hujan ringan”, dan “hujan lebat”. Hasil evaluasi menggunakan Mean Absolute Error (MAE) sebesar 0,29 dan Root Mean Squared Error (RMSE) sebesar 1,08 menunjukkan tingkat akurasi yang tinggi dan kesalahan prediksi yang sangat rendah. Dengan demikian, metode Fuzzy Mamdani terbukti efektif dalam menghasilkan prediksi cuaca yang akurat dan relevan, sehingga dapat dimanfaatkan oleh masyarakat, khususnya petani dan nelayan, untuk perencanaan aktivitas serta mitigasi risiko akibat perubahan cuaca mendadak.
Application of fuzzy tsukamoto method in forecasting weather Murtopo, Aang Alim; Aslam, Muhammad Nur; Andriani, Wresti; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.305

Abstract

In today's information age, accurate weather prediction is essential given its far-reaching impact on various aspects of life and economic activity. This study aimed to test the effectiveness of Fuzzy Tsukamoto's method in predicting important weather variables such as temperature, humidity, and precipitation. This research method uses a combination design that includes experimental methods for model development, quantitative analysis of historical weather data, and model validation using separate data. The results showed that the Fuzzy Tsukamoto method was able to increase the accuracy of weather predictions compared to conventional methods, with a significant decrease in the value of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In conclusion, this study successfully demonstrates that Fuzzy Tsukamoto's method can be a more accurate alternative in weather prediction, making a significant contribution to the field of meteorology and its practical application in decision-making in various sectors that depend on weather prediction.
Co-Authors Aang Alim Murtopo Andriani, Wresti Erni Unggul Sedya Utami, Erni Unggul Sedya Gunawan Gunawan Sarif Surorejo