ANALYSIS OF CLASSIFICATION ALGORITHM IN PENSION TYPES OF GOVERNMENT EMPLOYEES
Arif Senja Fitrani*, Mochamad Alfan Rosid
Universitas Muhammadiyah Sidoarjo
Abstract
The concept of data mining in its implementation is used in handling and analyzing data in large capacity - steps to extract information and to gain knowledge in supporting decision making. Data mining, in its implementation, can be used in various sectors of data analysis, namely about the condition of the type of pension. The purpose of this study is to provide information, where a civil servant within the retirement limit is taken normally or earlier. The technique of using the classification method, with the decision tree C4.5 (J48), Naive Bayes and k Nearest Neighbor algorithm. Presentation of assets of 1,316 pension data in 2012 and 2013 from Bukopin Bank customers, which are divided into training data by 65% and data testing by 35%. From the testing of three algorithms, the highest classification was produced, namely Naive Bayes with 91%. The results of the three classifications indicate the quality of attribute determination can affect the results. And the predictive level of the three algorithms shows different results. For classification techniques with better results, improvements are needed to determine attributes and develop existing datasets
Keywords: Data Mining;Classification;Pension Data;Algorithm Classification;Classification;Comparative Analysis
Topic: Computer Science