Maulidiati, Amelia Nur (2026) Pemodelan Sistem Rekomendasi Pemilihan Program Studi Mahasiswa Baru STMIK Widya Cipta Dharma dengan Klasifikasi Naive Bayes. S1 Teknik Informatika thesis, STMIK Widya Cipta Dharma.
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Abstract
Pemilihan program studi merupakan salah satu keputusan penting bagi calon mahasiswa karena akan memengaruhi proses pembelajaran dan pengembangan kompetensi selama masa perkuliahan. Namun, masih banyak calon mahasiswa yang menentukan pilihan program studi berdasarkan pertimbangan subjektif sehingga berpotensi tidak sesuai dengan minat dan kemampuan yang dimiliki. Penelitian ini bertujuan memodelkan dan membangun sistem rekomendasi pemilihan program studi bagi calon mahasiswa baru STMIK Widya Cipta Dharma berbasis web menggunakan algoritma Naive Bayes sebagai pendukung pengambilan keputusan. Penelitian ini menggunakan metode pengembangan sistem Waterfall. Data penelitian diperoleh melalui penyebaran kuesioner kepada 123 mahasiswa STMIK Widya Cipta Dharma. Sebelum proses klasifikasi dilakukan, atribut nilai Bahasa Indonesia, Bahasa Inggris, dan Matematika dikonversi menjadi data kategorikal melalui tahap preprocessing. Selanjutnya, algoritma Naive Bayes digunakan untuk mengklasifikasikan seluruh data responden. Hasil klasifikasi kemudian dievaluasi menggunakan Confusion Matrix dengan membandingkan hasil prediksi terhadap kelas aktual sehingga diperoleh nilai Accuracy, precision, Recall, dan F1-Score. Hasil penelitian menunjukkan bahwa sistem berhasil memberikan rekomendasi program studi berdasarkan nilai probabilitas tertinggi yang dihitung menggunakan algoritma Naive Bayes. Evaluasi model menggunakan Confusion Matrix menghasilkan nilai Accuracy sebesar 84,55%, precision sebesar 84,71%, Recall sebesar 84,55%, dan F1-Score sebesar 84,30%. Selain menghasilkan rekomendasi program studi, sistem juga mampu menampilkan proses perhitungan algoritma Naive Bayes, menyimpan riwayat rekomendasi, serta menghasilkan laporan dalam format PDF dan Excel. Hasil tersebut menunjukkan bahwa algoritma Naive Bayes dapat diterapkan sebagai metode rekomendasi program studi bagi calon mahasiswa baru STMIK Widya Cipta Dharma. ============================================================ Choosing a study program is one of the most important decisions for prospective university students because it influences their learning process and competency development throughout their academic journey. However, many prospective students still choose a study program based on subjective considerations, which may not align with their interests and abilities. This research aims to model and develop a web-based study program recommendation system for prospective new students at STMIK Widya Cipta Dharma by applying the Naive Bayes algorithm as a decision support method. This research employed the Waterfall software development model. The research data were collected through questionnaires distributed to 123 students of STMIK Widya Cipta Dharma. Before the classification process, the Indonesian Language, English Language, and Mathematics scores were converted into categorical data during the preprocessing stage. The Naive Bayes algorithm was then used to classify all respondent data. The classification results were evaluated using a Confusion Matrix by comparing the predicted labels with the actual class labels to obtain the values of Accuracy, precision, Recall, and F1-Score. The results show that the system successfully provides study program recommendations based on the highest posterior probability calculated using the Naive Bayes algorithm. The model evaluation using the Confusion Matrix on the classification results of all respondents achieved an Accuracy of 84.55%, a precision of 84.71%, a Recall of 84.55%, and an F1-Score of 84.30%. In addition to providing study program recommendations, the system is capable of displaying the Naive Bayes calculation process, storing recommendation histories, and generating reports in PDF and Excel formats. These findings indicate that the Naive Bayes algorithm can be effectively applied as a study program recommendation method for prospective students at STMIK Widya Cipta Dharma.
| Item Type: | Thesis (S1 Teknik Informatika) |
|---|---|
| Additional Information: | Pembimbing 1 : Hanifah Ekawati, S.Pd., M.Pd. Pembimbing 2 : Siti Lailiyah, S.Kom., M.Kom. |
| Uncontrolled Keywords: | Naive Bayes, sistem rekomendasi, program studi, klasifikasi, Flask |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Teknik Informatika |
| Depositing User: | Ms Amelia Nur Maulidiati |
| Date Deposited: | 06 Aug 2026 06:06 |
| Last Modified: | 06 Aug 2026 06:06 |
| URI: | http://repository.wicida.ac.id/id/eprint/6381 |
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