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Irma Nurmaulida
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering

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Penggunaan Naïve Bayes Dalam Implementasi Prediksi Tingkat Curah Hujan Zaenur Rozikin; Irma Nurmaulida
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Precipitation forecasting has been one of the most challenging scientific and technological problems worldwide in the last century. Rain is an event where water drops fall from the sky to the surface of the earth. Rain is also the water cycle on planet earth. Another definition of rain is an event of precipitation (the fall of liquid originating from the atmosphere that is liquid or frozen to the earth's surface) in the form of liquid. Rain requires the presence of a thick layer of the atmosphere in order to meet temperatures above the melting point of ice near and above the surface of the Earth. Throughout the year, rainfall has an erratic pattern making it difficult to predict manually. The amount of rainfall that is large enough cannot be determined with certainty, but this can be estimated. Thus, data mining allows machines to recognize and study complex data patterns. Therefore machine learning can study patterns of rainfall data to make predictions, so a rainfall prediction study was carried out using the Naïve Bayes method and the data used in this study is data taken from the official BMKG Indonesia website which can be accessed by all groups, both among children, adolescents, adults and even parents.
Co-Authors Zaenur Rozikin