Fitri Marisa, Sharifah Sakinah Syed Ahmad, Zeratul Izzah Mohd Yusof, Tubagus Mohammad Akhriza, Wiwin Purnomowati, Rakesh Kumar Pandey
Business capital and revenue are not only the decisive of the health of SMEs but also they must be balanced. In general, customers find their benefit from the flexible payment methods while on the other hand the SMEs should get their benefit too. So that, it needs to be studied whether it is necessary for SMEs to get their profit in accordance to this situation. One of the methods that suitable to be applied is by applying customer groupings based on revenue and payment namely the K-means clustering method since it can raise several groups that have not been known before. This information is useful for SMEs to be utilized based on their needs. Data in this study were gathered from customer attributes, number of transactions, and payment methods. The number of centroids was 3. The grouping results were stopped at the 5th iteration. The finding showed that the ratio value of the 4th iteration and the 5th iteration having the same ratio value, 0.07393. From the results of the iterations can be found; first, based on the customers' number, the groups can be classified into three C1(18%), C2 (45%), C3 (36%). Second, based on the average number of transactions, post-paid payments was in the first rank (12.7 / week). From the results, it can be analyzed that this situation is burdensome for SMEs because the more the number of transactions, the more investment must be prepared for accounts receivable. © Published under licence by IOP Publishing Ltd.
Faculty of Information and Communication Technoloy, Universiti Teknikal Malaysia Melaka, Jl. Hang tuah jaya, durian tunggal Melaka, 76100, Malaysia; Informatics Engineering Department, Widyagama University of Malang, Jl. Borobudur no 35, Malang Jawa Timur, Indonesia; Department of Infermatics Engineering, Pradnya Paramita School of Informatics and Management, Malang, Indonesia; Kirori Mal College, University of Delhi North Campus, Delhi, 110007, India; Department of Science Technology (DST) under Airtf Program -RTF/2018/000033, India
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