CLASSIFICATION ANALYSIS OF STUDENT SATISFACTION WITH THE IMPLEMENTATION OF ACADEMIC SERVICES FMIPA HALU OLEO UNIVERSITY USING THE RANDOM FOREST ALGORITHM
ANALISIS KLASIFIKASI KEPUASAN MAHASISWA TERHADAP PENYELENGGARAAN PELAYANAN AKADEMIK FMIPA UNIVERSITAS HALU OLEO MENGGUNAKAN ALGORITMA RANDOM FOREST
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).
Bahasa Indonesia
Kepuasan mahasiswa terhadap layanan akademik adalah indikator penting untuk menilai kinerja institusi pendidikan tinggi. Penelitian ini bertujuan untuk mengukur tingkat kepuasan mahasiswa FMIPA Universitas Halu Oleo terhadap layanan akademik yang diberikan. Hasil dari penelitian ini diharapkan dapat membantu universitas dalam memperbaiki layanan yang kurang memadai serta mempertahankan atau meningkatkan kualitas layanan yang sudah baik. Penelitian ini menggunakan metode kuantitatif dengan pendekatan survei. Data diperoleh melalui kuesioner yang diisi oleh 91 mahasiswa FMIPA Universitas Halu Oleo. Analisis data dilakukan dengan algoritma Random Forest menggunakan perangkat lunak R Studio. Proses analisis meliputi pembersihan data, pembagian data menjadi data latih dan data uji, serta klasifikasi menggunakan Random Forest. Evaluasi model dilakukan dengan confusion matrix dan k-fold cross-validation untuk memastikan akurasi dan keandalan hasil klasifikasi. Hasil penelitian menunjukkan bahwa algoritma Random Forest dapat mengklasifikasikan tingkat kepuasan mahasiswa dengan akurasi 94%. Faktor yang paling mempengaruhi kepuasan mahasiswa adalah assurance (jaminan), tangibles (bukti fisik), reliability (keandalan), responsiveness (daya tanggap), dan empathy (empati).
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