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All Journal Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) CogITo Smart Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) CSRID (Computer Science Research and Its Development Journal) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) J-SAKTI (Jurnal Sains Komputer dan Informatika) Buletin Sistem Informasi dan Teknologi Islam Room of Civil Society Development DIPANEGARA KOMPUTER TEKNOLOGI INFORMATIKA (DIPAKOMTI) DIPANEGARA KOMPUTER SISTEM INFORMASI (DIPAKOMSI) Room of Civil Social Development
Komang Aryasa
Universitas Dipa Makassar
Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Languange, Linguistic, Communication & Media Social Sciences Other

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Journal : J-SAKTI (Jurnal Sains Komputer dan Informatika)

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Analisis Prediksi Curah Hujan Bulanan Wilayah Kota Sorong Menggunakan Metode Multiple Regression Yusuf, Muhammad; Setyanto, Arief; Aryasa, Komang
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.455

Abstract

Currently, climate change in Indonesia, which is a tropical region, is always uncertain and makes it difficult to predict weather conditions. Weather conditions can be influenced by temperature, air pressure, wind speed, humidity and rainfall. Rainfall is a climate parameter that has a high level of diversity due to climate anomalies. There are several factors that influence the characteristics of the diversity of rainfall, namely geographical, orographic, topographical, orientation and structure of the islands. These factors cause the distribution pattern of rainfall to be uneven between one area and another. For that we need a method that can solve the problem of predicting rainfall both daily, monthly and yearly. Prediction of rainfall with a statistical approach can be done through the Multiple Linear Regression method. Where in this study, rainfall is the dependent variable, while temperature and humidity are independent variables. The results obtained from the WEKA Application with a total of 60 data from 2017 to 2021, the correlation coefficient value is 0.8175, and from the evaluation results using Linear Regression, the MAE error rate is 78.8695 and the RMSE is 95.1982. It can be concluded that the effect of temperature and air on the occurrence of rainfall is 81.75%
Co-Authors A.Muh.Fadhil A.Muh.Fadhil Aldi Susanto Ardimansyah Ardimansyah Arief Setyanto Asran Asran Cucut Susanto David Brilian Theonardi Edwin Tri Alfriady Erfan Hasmin Flora Flora Harlina, Sitti Jimmy H Moedjahedy kasmawaru kasmawaru Marsellus Oton Kadang Michael Gibran Yusuf Dani Mike Fitriani Muhammad Furqan Rasyid Muhammad Syukri Mustafa Muhammad Syukri Mustafa, Muhammad Syukri Muhammad Yusuf Nurul Maria Lisanty AD Rahma Rahma Rifky Prirendi Risnawati Risnawati Rudy Donny Likliwatil Rudy Donny Lillikwatil Sadly Syamsuddin Santi Santi Sapriadi Sapriadi Turahman, Tazkira Wa Ode Dwiki Bella Avista Wilem Musu Willem Musu, Willem Yesaya Tommy Paulus Yosep Yosep