Application of K-Means Clustering to Analyze Insurance Data at PT AXA Insurance Indonesia

Nayla Azkia; Rizky Feliana Devi; Fajar Hartanto Siswanto; Jerry Heikal

Nayla Azkia Universitas Bakrie
Rizky Feliana Devi Universitas Bakrie
Fajar Hartanto Siswanto Universitas Bakrie
Jerry Heikal Universitas Bakrie

Abstract

The object of this research is the company PT. AXA Insurance Indonesia, with 10 marketing offices in 8 big cities. The data used are 50 general insurance participants with 4 different premiums, namely property, travel, vehicles, and health, in the form of qualitative data that can be calculated as numbers and numerical variables to be used for this research. The aim of this research is to obtain the products and services from the company PT AXA Insurance Indonesia that are most in-demand based on currently available data on insurance participants so that they can develop and market insurance products more widely and on target. Data research uses the K-Means Algorithm which is one of the algorithms in the clustering or grouping function where the data analysis method is carried out by means of Data Mining. From the research results, the 5-cluster analysis concluded that the average data of men aged 25-46 years and over who are married with an income of 10 million prefer property and vehicle insurance products. Then for the average data of women aged 25-35 years who are already married or unmarried with an income of 10 million prefer health insurance products.

Keywords: Data Mining, Insurance, K-Means.

References

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https://axa.co.id/in/tentang-axainsurance

https://axa.co.id/kesehatan-personal

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The Coding Manual for Qualitative Research - Johnny Saldana.