Integration of Fuzzy C-Means and SAW Methods on Education Fee Assistance Recipients


 Every year, UMTAS gets a quota for KIP tuition fee assistance provided by KEMDIKBUD. This program is intended high school / vocational/equivalent graduates from poor and vulnerable families. The evaluation results of its implementation have problems, including the number applicants exceeding given KEMDIKBUD some coming well-off research uses fuzzy c-means method data clustering SAW ranking. grouping using obtained first cluster (C1) 72 second (C2) 119 data. Group C1 closer to provisions aid recipients (eligible) compared group C2 (ineligible) because Data consists 100% DTKS recipients, 50% KKS card owners, parental income <750,000, 40.28% dependents >=2 people 29.17% with achievements. registrant included in are then ranked technique get weights, 30 highest weight will be used as decision on KIP-Kuliah Education according provided. optimization Fuzzy C-Means methods selecting education objective right target.