Analysis of the effect of the lecturer satisfaction with the Naive Bayes Data Mining technique on institutional performance
Siti Aulia Aisyah, Preddy Marpaung, Wiwin Aprinai, Komda Saharja, I Made Yuda Suryawan, Bekti Taufiq Ari Nugroho, Amin Nurbaedi, Hasrul Azwar Hasibuan, Bernadetha Nadeak, Ahmad Tohir · Journal of Physics Conference Series · 2021
Abstract The study aimed to analyze the effect on institutional performance of lecturer satisfaction with data extraction techniques. The solution is the technique of Naive Bayes, where data is obtained through interviews and questionnaires conducted in one of the private institutions in the north-sumatra of Medan. The evaluation criteria are readiness, compassion, reliability and accountability. The tests indicate that the level of accuracy is 85.48% with 81.08% precision, and 93.75% recall value. The Naïve Bayes method can also be recommended to predict the degree of satisfaction of the lecturer with institutional performance based on the results of tests using fast miner software.