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All Journal Building of Informatics, Technology and Science Inovasi Fisika Indonesia (IFI)
Wisnawa, Gede Gangga
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Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Materials Science & Nanotechnology Physics

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Penerapan Metode Principal Component Analysis (PCA) dan Long Short-Term Memory (LSTM) dalam Memprediksi Prediksi Curah Hujan Harian Musfiroh, Musfiroh; Novitasari, Dian Candra Rini; Intan, Putroue Keumala; Wisnawa, Gede Gangga
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3114

Abstract

Since the last three years North Luwu has experienced frequent hydrological disasters in the form of floods and landslides. The disaster had a negative impact on the availability of clean water, failed to plant and even tended to reduce the quality of the harvest. Cocoa is one of the leading commodities of North Luwu Regency whose productivity has decreased due to the impact of climate change so that it will affect the sustainability of the local population's income. Therefore, the purpose of this research is to anticipate rainfall that will occur to prevent or reduce the risk of failure and loss. Principal Component Analysis (PCA) Method is used as feature extraction to find out the most influential variables and the Long Short-Term Memory (LSTM) method is used as a prediction method. Future rainfall is predicted using meteorological variables such as pressure, evaporation, maximum temperature, average humidity, and sunshine duration from 1 January 2017 to 30 September 2022. Based on the PCA results, 4 variables are obtained that have the most influence on rainfall, namely: variable evaporation, maximum temperature, average humidity, and length of sunlight. These variables are used as input to predict rainfall using LSTM. In this study using trial parameters, namely the number of hidden, batch size, and learn rate drop period. The best prediction results were obtained for MAPE of 0.0018 with the number of hidden, batch size and learn rate drop periods of 100, 32, and 50 respectively. The prediction results show very heavy rainfall occurring on August 28, 2021 of 101.9734 mm, 21 September 2021 of 108.6528 mm, and 5 April 2022 of 116.5510 mm. In this study PCA was able to increase accuracy in considering all parameters and choosing the most effective.
ANALISIS KARAKTERISTIK GELOMBANG, ANGIN PERMUKAAN DAN CURAH HUJAN DI TIGA WILAYAH PEMBAGIAN ZONA HUJAN TAHUN 2021-2022: Kata Kunci: karakteristik, gelombang laut, angin permukaan, curah hujan, zona hujan. Ramadhany, Ekik Setyo Amalia; Prianbikasatiarsa, Nichou; Melani, Putri; Wisnawa, Gede Gangga; Realita, Arie
Inovasi Fisika Indonesia Vol. 14 No. 1 (2025): Vol 14 No 1
Publisher : Prodi Fisika FMIPA Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/ifi.v14n1.p55-74

Abstract

Artikel ini bertujuan untuk menganalisis karakteristik gelombang laut, angin permukaan, dan curah hujan di tiga wilayah zona hujan Indonesia: Sumatera Barat, Maluku Selatan dan Jawa. Data model yang digunakan diambil dari oPeNDAP BMKG lalu dianalisis per triwulan (DJF, MAM, JJA, SON) dan per tahun (2020-2022). Pada wilayah Sumatera Barat gelombang dan kecepatan angin tertinggi terjadi pada periode JJA dan terendah pada periode MAM dan SON dengan curah hujan yang tertinggi terjadi di bulan september hingga Desember. Pada Wilayah Maluku Tinggi gelombang dan kecepatan angin tertinggi terjadi pada periode JJA dan terendah pada periode MAM dan SON. Pada periode JJA merupakan puncak tertinggi curah hujan di wilayah Maluku. Terakhir, pada wilayah Jawa Tinggi gelombang dan kecepatan angin tertinggi terjadi pada periode JJA dan terendah pada periode MAM dan SON. Pada periode DJF wilayah Jawa mengalami puncak curah hujan dan curah hujan terendah pada periode JJA. Kata Kunci: karakteristik, gelombang laut, angin permukaan, curah hujan, zona hujan. Abstract This article aims to analyze the characteristics of ocean waves, surface winds and rainfall in three rainy zone regions of Indonesia: West Sumatra, South Maluku and Java. The model data used was taken from oPeNDAP BMKG and analyzed per quarter (DJF, MAM, JJA, SON) and per year (2020-2022). In the West Sumatra region, the highest waves and wind speeds occur in the JJA period and the lowest in the MAM and SON periods with the highest rainfall occurring in September to December. In the Maluku region, the highest waves and wind speeds occur in the JJA period and the lowest in the MAM and SON periods. In the JJA period is the highest peak of rainfall in the Maluku region. Finally, in the Java region, the highest wave height and wind speed occurred in the JJA period and the lowest in the MAM and SON periods. In the DJF period, the Java region experienced the peak rainfall and the lowest rainfall in the JJA period.  Keywords: characteristics, ocean waves, surface winds, rainfall, rain zones.
Co-Authors Melani, Putri Musfiroh Musfiroh, Musfiroh Prianbikasatiarsa, Nichou Putroue Keumala Intan Ramadhany, Ekik Setyo Amalia Realita, Arie Sari, Dian Candra Rini Novita