Prediction of Milenial and Post Milenial Voters in Elections Using The Naive Bayes Algorithm
Prediksi Pemilih Milenial dan Pasca Milenial Di Pemilu Menggunakan Algoritma Naive Bayes
DOI:
https://doi.org/10.21070/ups.981Keywords:
Data Mining, Naive Bayes, SidoarjoAbstract
The main problem in efforts to predict the current elections is related to the fact that many millennials are abstaining throughout Indonesia, especially in the Wonokasian District, as evidenced by the high abstentions between regions. This research will test the classification based on election population data obtained from Wonokasian District in 2019 using the method Naïve Bayes. The results of this study used Weka to make it easier for the village community to find out millennial data between those who abstain and those
who do not abstain. From the classification results on the Naïve Bayes method for classifying attendance status from 100 datasets, the highest result was obtained using manual calculations with a truth level of 76.67. % and an error rate of 23.33%. As for 10% of the 100 datasets, the highest results were obtained using Weka with a truth level of 100% and an error rate of 0%.
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