Application Of Data Mining Using The Naïve Bayes Classification Method To Predict Public Interest Participation In The 2024 Elections - Marcelina Novi Zarti; Eka Sahputra; Anisya Sonita; Yovi Apridiansyah (Penerbit Jurnal Indonesia, 2023)
A big data processing process using a Data Mining technique that will be used in a study in the Application of Data Mining Using the Naïve Bayes classification to predict the participation of the Public Interest in the 2024 election. The data was obtained from the General Election Commission (KPU). The data was tested using the Naïve Bayes classification method with Weka Tools and 7 predetermined attributes. The dataset was taken as much as 96.67% of 11,406 training data, namely 2014 election data and 99.90% of 11,908 testing data, namely 2020 election data. Results It is known that the number of participants in Central Bengkulu Regency for the 2024 election based on participant data in 2020 and the 2014 election results is likely to increase by up to 3.23%, from 96.67% per 11,406 participants to 99.90% per 11,908 participants and the results predictions are likely to increase.