Penerapan Algoritma Apriori untuk Rekomendasi Asuransi pada Nasabah
(Studi Kasus: Asuransi Jasindo Kota Medan)
DOI:
https://doi.org/10.54066/jptis.v2i3.2379Keywords:
Data mining, insurance, apriori algorithmAbstract
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.
References
Amna, S, W., Putra, T. A., Wahidin, A. J., Syukrilla, W. A., Wardhani, A. K., Heryana, N., Indriyani, T., & Santoso, L. W. (2023). Data Mining Data mining. In D. Ediana (Ed.), PT Global Eksekutif Teknologi (1st ed., Vol. 1, Issue 1). PT Global Eksekutif Teknologi. https://www.cambridge.org/core/product/identifier/CBO9781139058452A007/type/book_part
Aziz Muslim, M., Prasetiyo, B., Harum M, E. L., Juli H, A., Mirqotussa’adah, Hardiyanti R, S., & Nurzannahputra, A. (2019). Data Mining Algoritma C4.5. In E. Listiana & N. Cahyani (Eds.), ILKOM UNNES (1st ed., Vol. 1, Issue 1). ILKOM UNNES.
Haerani, E., Budianita, E., Nazir, A., & Mahesa, W. (2023). Penerapan K-Means Clustering Pada Data Obat/Alkes di Apotik RSUD Selasih. Seminar Nasional Teknologi Informasi, Komunikasi Dan Industri (SNTIKI), 1(1), 220–229.
Herlin Lutfiannisa, A., Maimunah, & Sukmasetya, P. (2024). Clustering Data Pasien Berdasarkan Usia di Puskesmas Menerapkan Metode K-Means. Journal of Information System Research, 5(2), 639–647. https://doi.org/10.47065/josh.v5i2.4755
Kemensos RI. (2020). Perilaku hidup bersih dan sehat (phbs) penguatan kapabilitas anak dan keluarga. In Kementrian Sosial Republik Indonesia. Kementrian Sosial Republik Indonesia.
Matahari, R., Utami, F. P., & Sugiharti, S. (2013). Keluarga Berencana dan Alat Kontrasepsi. In 1 (Ed.), Keluarga Berencana dan Alat Kontrasepsi (1st ed.). CV. Pustaka Ilmu Group. https://doi.org/10.1300/J153v04n01_13
Maulia, S., Serasi Ginting, B., & Anton, S. (2021). Implementasi Data Mining Pengelompokan Jenis Penyakit Pasien Menggunakan Metode Clustering (Studi Kasus : Puskesmas Sambirejo). Jurnal Informatika Kaputama (JIK), 5(1), 71–80. https://doi.org/10.59697/jik.v5i1.304
Munazilin, A., & Santoso, F. (2021). logika dan algoritma pemrograman (Khumaidi (ed.); 1st ed.). CV. AA. Rizky.
Pane, P. P., Ramadhan Nasution, Y., & Furqan, M. (2024). Implementasi Data Mining dengan K-Means Clustering untuk Memprediksi Pengadaan Obat. Journal of Computer System and Informatics (JoSYC), 5(2), 286–296. https://doi.org/10.47065/josyc.v5i2.4920
Relita Buaton, Zarlis, M., Efendi, S., & Yasin, V. (2019). Data Mining Time Series (Vol. 1, pp. XIV–235). WADE GROUP.
Sariani, D. S. R. S. I. G. (2022). Pengelompokan Data Pengguna Narkoba Yang Melakukan Program Rehabilitasi Rawat Jalan Menggunakan Metode Clustering. Informasi Dan Informatika, 11, 8–13.
Sianturi, R. N., Sihombing, M., & ... (2023). Data Mining Grouping the Feasibility of Applying for Credit To Customers Using the K-Means Algorithm Method on Cv. Motorbike …. … of Mathematics and …, 2(2), 49–60. http://journal.binainternusa.org/index.php/matech/article/view/145%0Ahttp://journal.binainternusa.org/index.php/matech/article/download/145/106
Yulia, N., Saragih, R., & Ambarita, I. (2021). Data Mining Pengelompokan Anak Stunting Berdasarkan Usia , Penyebab dan Pekerjaan Orang Tua Dengan Menggunakan Metode Clustering ( Studi Kasus : Dinas Kesehatan Kabupaten Langkat ). Seminar Nasional Informatika (SENATIKA)Prosiding SENATIKA 2021, 2(1), 12. http://www.ejournal.pelitaindonesia.ac.id/ojs32/index.php/SENATIKA/article/view/1174/661