IMPLEMENTASI K-MEANS CLUSTERING UNTUK MENGANALISIS FAKTOR KETERLAMBATAN PENYELESAIAN STUDI MAHASISWA PRODI TEKNIK INFORMATIKA DI STMIK WIDYA CIPTA DHARMA

Sukma, Nur Fadilah Putri Sukma (2025) IMPLEMENTASI K-MEANS CLUSTERING UNTUK MENGANALISIS FAKTOR KETERLAMBATAN PENYELESAIAN STUDI MAHASISWA PRODI TEKNIK INFORMATIKA DI STMIK WIDYA CIPTA DHARMA. S1 Teknik Informatika thesis, STMIK Widya Cipta Dharma.

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Abstract

Keterlambatan penyelesaian studi menjadi salah satu permasalahan signifikan dalam dunia pendidikan tinggi karena berdampak terhadap akreditasi dan mutu program studi. Di STMIK Widya Cipta Dharma, lebih dari separuh mahasiswa Program Studi Teknik Informatika angkatan 2017–2021 tidak berhasil menyelesaikan studi tepat waktu, sehingga diperlukan analisis yang mendalam terhadap faktor-faktor yang memengaruhi kondisi tersebut. Penelitian ini bertujuan untuk menganalisis faktor dominan dan pola keterlambatan penyelesaian studi mahasiswa dengan menerapkan metode K-Means Clustering. Data yang digunakan terdiri dari faktor akademik seperti IPK, IPS, jumlah SKS yang telah diambil, serta SKS yang diulang; dan faktor non-akademik seperti kendala keuangan, status pekerjaan, keaktifan organisasi, dan jarak tempat tinggal ke kampus. Seluruh proses analisis mengikuti tahapan CRISP-DM dan diimplementasikan menggunakan Python melalui platform Jupyter Notebook. Hasil dari penelitian ini menunjukkan bahwa mahasiswa yang terlambat studi dapat dikelompokkan ke dalam beberapa cluster dengan karakteristik yang berbeda. Pada sisi akademik, perbedaan utama antar cluster ditentukan oleh kombinasi total SKS yang telah ditempuh dan SKS yang belum diselesaikan. Pada sisi non-akademik, variasi paling menonjol dipengaruhi oleh status pekerjaan, tingkat keaktifan organisasi, dan jumlah jam kerja. Temuan ini menegaskan bahwa keterlambatan studi tidak hanya terkait progres akademik, tetapi juga dipengaruhi aktivitas di luar perkuliahan, sehingga pemantauan kedua aspek tersebut penting untuk deteksi dini dan tindak lanjut pembinaan. ============================================================ Study completion delays are a significant issue in higher education, as they impact accreditation and the overall quality of academic programs. At STMIK Widya Cipta Dharma, more than half of Informatics Engineering students from the 2017 to 2021 cohorts failed to graduate on time, indicating the need for an in-depth analysis of the factors contributing to this condition. This study aims to analyze the dominant factors and patterns behind delayed graduation using the K-Means Clustering method. The data includes academic variables such as GPA, semester performance (IPS), total credits earned, and repeated courses; as well as non-academic factors including financial constraints, employment status, organizational involvement, and distance from home to campus. The entire analysis follows the CRISP-DM framework and is implemented using Python within the Jupyter Notebook environment. The results of this study show that students who experience delayed graduation can be grouped into several clusters with distinct characteristics. On the academic side, the main differences between clusters are determined by a combination of total completed credits and the number of credits yet to be taken. On the non-academic side, the most notable variations are influenced by employment status, level of organizational involvement, and the number of working hours. These findings highlight that delays in study completion are not solely related to academic progress but are also significantly affected by extracurricular activities. Therefore, monitoring both academic and non-academic aspects is essential for early detection and effective academic intervention.

Item Type: Thesis (S1 Teknik Informatika)
Additional Information: Pembimbing 1 : Wahyuni, S.Kom., M.Kom Pembimbing 2 : Eka Arriyanti, S.Pd., M.Kom
Uncontrolled Keywords: clustering, keterlambatan kelulusan mahasiswa, faktor akademik, faktor non-akademik, CRISP-DM.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Teknik Informatika
Depositing User: Ms Sukma Nur Fadilah Putri
Date Deposited: 08 Aug 2025 07:43
Last Modified: 08 Aug 2025 07:43
URI: http://repository.wicida.ac.id/id/eprint/6241

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