Data Mining Dengan Algoritma Naive Bayes Untuk Klasifikasi Minat Bakat Anak Pada Pusat Pengembangan Anak (PPA) Di Kota Medan

Abstract

Child Development Centers (PPA) have an important role in helping children develop their potential, interests, and talents optimally. However, the process of identifying children's interests and talents at PPA often faces challenges, such as large volumes of evaluation data, subjectivity in assessment, and difficulty in determining appropriate development programs. To overcome these problems, this study developed a data mining-based system using the Naive Bayes algorithm for classifying children's interests and talents. The Naive Bayes algorithm was chosen because of its ability to analyze data and produce accurate classifications based on probability. The designed system uses child evaluation data, such as activity observations, and teacher assessments, to group children into interest and talent categories, such as music, sports, academics, technology and skills. The results of the implementation of this system show that the Naive Bayes algorithm is able to classify children's interests and talents with a high level of accuracy. This system not only helps reduce the subjectivity of assessment, but also supports PPA in determining development programs that are more focused and in accordance with the needs of individual children. Thus, this system is expected to be an effective solution to improve the quality of services at PPA