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All Journal JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA Joined Journal (Journal of Informatics Education Media Aplikom INCODING: Journal of Informatics and Computer Science Engineering Jurnal Teknologi Informasi Cyberku Jurnal HUMMANSI (Humaniora, Manajemen, Akuntansi) International Journal of Computer Technology and Science
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Evaluasi Prestasi Akademik Mahasiswa Melalui Keaktifan dan Kuis: Analisis Regresi Linear Berganda Rosa Ratri Kusuma Hariningsih; Diwahana Mutiara Candrasari
Joined Journal (Journal of Informatics Education) Vol 7 No 2 (2024): Volume 7 Nomor 2 (2024)
Publisher : Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/joined.v7i2.3586

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh keaktifan dan nilai kuis terhadap nilai Ujian Tengah Semester (UTS) pada mata kuliah Matematika Diskrit di Stikom Yos Sudarso Purwokerto menggunakan model regresi linear berganda. Dalam konteks mata kuliah Matematika Diskrit, nilai Ujian Tengah Semester (UTS) menjadi tolok ukur untuk mengevaluasi pemahaman mahasiswa terhadap materi yang telah diajarkan. Keaktifan mahasiswa selama proses belajar dan hasil kuis yang diperoleh dianggap sebagai faktor penting yang dapat memengaruhi pencapaian nilai UTS. Data yang digunakan dalam penelitian ini mencakup nilai UTS sebagai variabel dependen, sementara keaktifan dan nilai kuis sebagai variabel independen. Model regresi linear berganda diterapkan untuk mengevaluasi kontribusi masing-masing variabel terhadap nilai UTS. Hasil analisis menunjukkan bahwa baik keaktifan maupun nilai kuis berpengaruh positif dan signifikan terhadap nilai UTS. Sementara uji F mengindikasikan bahwa model regresi yang dihasilkan valid secara keseluruhan. Hasil menunjukkan bahwa meningkatkan keaktifan mahasiswa dalam kelas dan memberikan kuis secara teratur dapat meningkatkan pencapaian nilai UTS. Oleh karena itu, dapat dilakukan pembelajaran interaktif dan menerapkan evaluasi berkala untuk mendukung proses belajar yang lebih efektif.
Analisis Perbandingan Naive Bayes, Regresi Logistik Biner, dan Support Vector Machine untuk Prediksi Kasus Demam Berdarah di Purwokerto Ratri Kusuma Hariningsih, Rosa; Diwahana Mutiara Candrasari; Endang Setyawati; Syamsu Wahidin; Jevon Nataniel Putra5
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol. 12 No. 3 (2025): Jurnal Derivat (Desember 2025)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/j.derivat.v12i3.8408

Abstract

Dengue Hemorrhagic Fever (DHF) remains a significant public health issue in Purwokerto, with the increasing number of cases influenced by environmental factors such as temperature, humidity, rainfall, and population density. Accurate and adaptive predictive methods are essential to anticipate the spread of DHF, one of which involves the application of machine learning algorithms. This study aims to compare the performance of three algorithms, namely Naïve Bayes, Binary Logistic Regression, and Support Vector Machine (SVM), in predicting DHF risk in Purwokerto. Secondary data were obtained from the Health Office, Meteorology Agency (BMKG), and Statistics Bureau (BPS), covering DHF case records and environmental factors. The analysis was conducted using a quantitative predictive approach, employing 5-Fold Cross Validation and evaluation metrics including accuracy, precision, recall, and F1-score. The results indicate that the SVM model demonstrated the highest performance with an accuracy of 82% and a high recall rate for the positive class, making it effective for DHF risk mapping. The Naïve Bayes model showed adequate sensitivity but lower precision, while the Binary Logistic Regression model produced the lowest overall performance. This study recommends SVM as the most effective algorithm to support early warning systems and risk mitigation for DHF based on environmental data in Purwokerto.
Co-Authors Abdul Syukur Adhi Wibowo Adhi Wibowo Anggi Anggi Anggraini Anggi Anggraini Endang Setyawati Hadion Wijoyo Jevon Nataniel Putra Jevon Nataniel Putra5 Kusuma Indah Lestari Moch Arief Soeleman Ratri Kusuma Hariningsih, Rosa Roberto Martins Rosa Ratri Kusuma Hariningsih Suyudi Suyudi Suyudi Suyudi Syamsu Wahidin Thomas Kristian Jeriko Wahyu Eka Mulatsari Yosita Lianawati