Classification of Labor Using Support Vector Machine in North Sumatera - Ritonga, Anggiat P; Adithya, Andri Ramadhan; Agustina, Idri; Limbong, Tonni; Sinambela, Marzuki (Jurnal Teknik Informatika UNIKA Santo Thomas, 2019)
Labor markets in Indonesia are key challenges and policy issues. Balai Besar Pengembangan Latihan Kerja (BBPLK) Medan is a services unit to develop and implementation of labor to increase skill and knowledge. The classification of labor in North Sumatera is very interesting to evaluate the performance of the labor in North Sumatera. In this case, we compute the labor data to classify and evaluate the model and performance of the dataset. The computation of the dataset using the support vector machine (SVM) as a model in machine learning or probabilistic approach by training and test data. The data was collected from Badan Pusat Statistik (BPS) Sumatera Utara for 2018 samples. Labor force dataset in North Sumatera had been computed and shown the result, indicates the support vector machine classifier is the good algorithm for this classification problem, offering good values in terms of accuracy, for describe the labor force in North Sumatera and can be recommended to BBPLK to add more development and implementation.