Naïve Bayes Classifier Algorithm for Predicting Non-Participation of Elections in Lampung Province

Abstract

Several problems related to the DPT (Permanent Voter List) including the KPU (General Election Commission) it is difficult to get the NIK (Population Identification Number) of people who are in correctional institutions or prisoners, beginner voters who do not have an ID card (Kartu Tanda Sipil) who are currently in prison. study in student dormitories, Islamic boarding schools, and others who are outside the city, the number of which is 3-5% of invalid NIK, voters who do not have a resident identity, voters with KTP (Kartu Identity Card)/old Family Card and NIK (Population Identification Number) ) invalid around 7-19% and voters are difficult to find around 5-8% so that the KPU must-visit houses as regulated in the legislation. This could allow not all DPT (Permanent Voters List) to be registered.

Naïve Bayes Classifier is one of the classification methods used in Data Mining which is based on the Bayes theorem. Bayes is a simple probability-based prediction technique based on the application of Bayes' theorem (or Bayes' rule) with strong (naive) independent (independence) assumptions. Naive Bayes is only a method for analyzing, it takes other media to display information that is easy to understand the results of the Naïve Bayes Classifier calculations. Pentaho data integration is a tool that integrates large amounts of data, calls from Excel, MySQL, and provides instructions for existing data. Tableau is an application that will improve, tableau can call data that has been integrated and display the data in the form of diagrams, text, spatial data, and points from locations.

Keywords: Naïve Bayes Classifier, Algorithm, Election Commission