ANALISIS KLASIFIKASI KEPUASAN MAHASISWA TERHADAP PENYELENGGARAAN PELAYANAN AKADEMIK FMIPA UNIVERSITAS HALU OLEO MENGGUNAKAN ALGORITMA RANDOM FOREST - Auni Tiftazani; Andi Tenriawaru; Gusti Arviana Rahman (AnoaTIK: Jurnal Teknologi Informasi dan Komputer, 2024)
Student satisfaction with academic services is an important indicator for assessing the performance of higher education institutions. This research aims to measure the level of satisfaction of Halu Oleo University FMIPA students with the academic services provided. It is hoped that the results of this research can help universities improve inadequate services and maintain or improve the quality of services that are already good. This research uses quantitative methods with a survey approach. Data was obtained through a questionnaire filled out by 91 FMIPA students at Halu Oleo University. Data analysis was carried out with the Random Forest algorithm using R Studio software. The analysis process includes data cleaning, dividing data into training data and test data, as well as classification using Random Forest. Model evaluation was carried out with a confusion matrix and k-fold cross-validation to ensure the accuracy and reliability of the classification results. The research results show that the Random Forest algorithm can classify student satisfaction levels with 94% accuracy. The factors that most influence student satisfaction are assurance (guarantee), tangibles (physical evidence), reliability (reliability), responsiveness (responsiveness), and empathy (empathy).