The Implementation of Data Mining Method Using K-Means Algorithm to Analyze Study Interest of High School Students


  • Dadang Sudrajat STMIK IKMI Cirebon
  • Arif Rinaldi Dikananda STMIK IKMI Cirebon
  • Abrar Hiswara Universitas Bhayangkara Jakarta Raya
  • Rinovian Rais Unindra PGRI Jakarta
  • Amat Suroso Universitas Bani Saleh



Students, Data Mining, Cluster, K-Means, Algorithm


At present, the school is experiencing difficulties processing the results of student academic achievement for the specialization process for high school students. The currently running student interest process still uses a manual system by calculating the subject value of each student and then grouping the results of the calculation of each student's value into science or social studies interest groups in accordance with the requirements imposed by the school. For that, we need a solution that can overcome these difficulties. The author develops the application using the Rapid Application Development (RAD) method, which consists of the requirements planning phase, the design phase, the construction phase, and the implementation phase. At the construction stage, the K-Means algorithm is implemented in data mining technology to classify student academic achievement results into science and social studies interest groups. The results of making this application are intended for the school, especially the homeroom teacher, so that it can be an alternative solution or advice in making decisions for student specialization.


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How to Cite

Sudrajat, D., Dikananda, A. R., Hiswara, A., Rais, R., & Suroso, A. (2023). The Implementation of Data Mining Method Using K-Means Algorithm to Analyze Study Interest of High School Students. Jurnal Sistim Informasi Dan Teknologi, 5(1), 90–95.