Identifikasi Pola Kepuasan Mahasiswa Terhadap Proses Pembelajaran Menggunakan Algoritma K-Means Clustering.

Student satisfaction levels with the learning experience at higher education institutions often exhibit variability. This study aims to comprehend the varying degrees of student satisfaction at Institut Agama Islam Negeri (IAIN) Syekh Nurjati Cirebon. Employing the K-Means clustering method, this research categorizes students based on their satisfaction levels. The survey data analyzed includes 20 dimensions of Service Quality criteria evaluated by students, with these 20 dimensions grouped into five key aspects of Service Quality assessment: tangible, reliability, responsiveness, assurance, and empathy. The analysis reveals three distinct groups of students with differing satisfaction levels: neutral/fair (class 1), agree/good (class 2), and strongly agree/excellent (class 3). Comparisons among these groups highlight the diversity of student perceptions. Furthermore, an examination of the distribution of evaluations within each class uncovers differing priorities in assessment criteria. These research findings offer insights into the spectrum of student satisfaction levels and pinpoint areas warranting further attention in each class. Such insights can inform the development of policies and strategies aimed at enhancing the quality of learning experiences at IAIN Syekh Nurjati Cirebon.

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Publication Details

Journal
Jurnal Informatika Jurnal Pengembangan IT
Published
2024-08-29
DOI
https://doi.org/10.30591/jpit.v9i2.6740
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Identifikasi Pola Kepuasan Mahasiswa Terhadap Proses Pembelajaran Menggunakan Algoritma K-Means Clustering.

Lia Farhatuaini, Heru Purnomo Kurniawan
Jurnal Informatika Jurnal Pengembangan IT
Data Mining and Machine Learning Applications
article

Identifikasi Pola Kepuasan Mahasiswa Terhadap Proses Pembelajaran Menggunakan Algoritma K-Means Clustering.

Lia Farhatuaini, Heru Purnomo Kurniawan
article en

Abstract

Student satisfaction levels with the learning experience at higher education institutions often exhibit variability. This study aims to comprehend the varying degrees of student satisfaction at Institut Agama Islam Negeri (IAIN) Syekh Nurjati Cirebon. Employing the K-Means clustering method, this research categorizes students based on their satisfaction levels. The survey data analyzed includes 20 dimensions of Service Quality criteria evaluated by students, with these 20 dimensions grouped into five key aspects of Service Quality assessment: tangible, reliability, responsiveness, assurance, and empathy. The analysis reveals three distinct groups of students with differing satisfaction levels: neutral/fair (class 1), agree/good (class 2), and strongly agree/excellent (class 3). Comparisons among these groups highlight the diversity of student perceptions. Furthermore, an examination of the distribution of evaluations within each class uncovers differing priorities in assessment criteria. These research findings offer insights into the spectrum of student satisfaction levels and pinpoint areas warranting further attention in each class. Such insights can inform the development of policies and strategies aimed at enhancing the quality of learning experiences at IAIN Syekh Nurjati Cirebon.

Jurnal Informatika Jurnal Pengembangan ITVol. 9(2)
IAIN Syekh Nurjati Cirebon
Quality Education
Openalex Percentile: Top 78%
Data Mining and Machine Learning Applications
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Identifikasi Pola Kepuasan Mahasiswa Terhadap Proses Pembelajaran Menggunakan Algoritma K-Means Clustering. — Lia Farhatuaini, Heru Purnomo Kurniawan · Jurnal Informatika Jurnal Pengembangan IT (2024) | TGRS Research Map | TGRS