Analisis Faktor Calon Nasabah PT. Bank Central Asia dalam Pembuatan Rekening Online menggunakan Metode K-Means Clustering Studi Kasus Wisma Asia BCA
DOI:
https://doi.org/10.35870/jtik.v6i1.391Keywords:
Clustering, Data Mining, Pemol Marketing, K-MeansAbstract
The purpose of this study is to obtain the results of the analysis of factors that make prospective customers who want to open an account at a branch switch to opening an online account. This study uses the K-Means method and uses the age factor, the time period in opening an account as a parameter. The data collection technique is in the form of data collection by questionnaire. The subject of this research is marketing who are members of PT Dika in collaboration with PT Bank Central Asia. Based on the research conducted by the author using the K-Means Clustering method and the rapidminer application, the researchers drew the following conclusions; 1) Of the three clusters, the age factor that has the most value is at age 21 in cluster 3 as many as 3 people. As for the age of 22 to 26 in the three clusters, the three clusters are not much different, 2) Of the three clusters, the most income factors are in group 3 as many as 4 people in cluster 2, namely earning around 1.500.000 – 3,000,000, 3) Of the three cluster, the distance factor from home to the nearest BCA Bank is at most at distance 1 as many as 3 people in cluster 3 and at distance 3 as many as 3 people in cluster 2, 4) Of the three clusters, the processing time factor is mostly in group 1 as much as 3 people in cluster 1, group 2 as many as 3 people in cluster 3 and group 3 as many as 3 people in cluster 3, and 5) From the three clusters, the factor of moving from opening an account at a branch to opening an online account (pemol) is because it's faster, in cluster 1 as many as 3 people, in cluster 2 as many as 2 people and in cluster 3 as many as 3 people.
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