Penerapan Algoritma Apriori untuk Rekomendasi Asuransi pada Nasabah

(Studi Kasus: Asuransi Jasindo Kota Medan)

Authors

  • Amanda Putri Ardana STMIK Kaputama
  • Akim M.H. Pardede STMIK Kaputama
  • Selfira Selfira STMIK Kaputama

DOI:

https://doi.org/10.54066/jptis.v2i3.2379

Keywords:

Data mining, insurance, apriori algorithm

Abstract

Jasindo Insurance Company is one of the insurance companies that receives insurance coverage both directly and indirectly, with ownership of 1 share of dwiwarna series A owned by the Republic of Indonesia and 424,999 shares of Series B owned by PT Bahana Pembinaan Usaha Indonesia (Persero). PT Asuransi Jasa Indonesia has several products and choices in choosing which insurance is needed by customers in agriculture, health, education and many more. Due to the large amount of competition in the business world, it requires management to find the right strategy in increasing the use of Jasindo insurance by knowing the relationship between age, gender, marital status, occupation and the type of Jasindo insurance that is widely chosen by customers. In order to find out the use of insurance that is widely used by the community, it is necessary to analyze the data on the use of insurance using the apriori algorithm method to determine the combination between item-sets of transaction data on Jasindo insurance data. Based on the research conducted after experimenting with the above case with a minimum support = 25%, confidence = 100% so that the results of the rule that meets the support and confidence values are obtained, namely if the gender is male, the marital status is Unmarried, then the type of insurance is jasimdo health and jasindo rainbow then giving value is successful with 25% support, 100% confidence.

 

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Published

2024-08-29

How to Cite

Amanda Putri Ardana, Akim M.H. Pardede, & Selfira Selfira. (2024). Penerapan Algoritma Apriori untuk Rekomendasi Asuransi pada Nasabah: (Studi Kasus: Asuransi Jasindo Kota Medan). Jurnal Penelitian Teknologi Informasi Dan Sains, 2(3), 118–139. https://doi.org/10.54066/jptis.v2i3.2379