Multi-Criteria Prediction Framework for the Prioritization of Council Candidates based on Integrated AHP-Consensus and TOPSIS Methods

Predicting the council candidate becomes difficult due to large number of criteria that must be known and identified. The best should chosen from among candidates because he or she will play an important role in organization institution. It is critical find right these days people see judge outcome a short time with help social media. Perhaps institution require they manage organize community around them. This study focuses on how prioritize using Analytic Hierarchy Process (AHP) for determine Technique Order Preference by Similarity Ideal Solution (TOPSIS) student candidate. proposed framework based Multi-Criteria Decision Making (MCDM) used recommend assist students selecting council. three were grade point average (GPA), Age, Semester. Based results questionnaire review literature, developed. then most criterion AHP weight criteria. TOPSIS was select qualified findings show GPA candidate, support findings.