SPK Penerima Bantuan Sosial Menggunakan Metode BWM-SAW dengan Metodologi Team Data Science Process (TDSP) - Mahendra, Gede Surya (SINTECH (Science and Information Technology) Journal, 2022)
This study aims to be able to perform manual calculations using the BWM-SAW method in determining social assistance recipients. The economic crisis triggered by COVID-19 creates a need to improve the social assistance system that has been implemented so far. The socialization process, data verification and other problems often create problems in determining the recipients of social assistance. To solve this problem, DSS can be one of the solutions in determining the recipients of social assistance. This study uses 3 criteria with 10 sub-criteria with 5 alternatives. This study uses the TDSP model which is the development of the CRISP-DM model. This study succeeded in performing manual calculations well. The weighting of the criteria is very important to give a good preference value. The grouping of sub-criteria helps decision makers to more easily provide comparisons between criteria. Alternative-1 is the best candidate in receiving social assistance with a score of 0.9519