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All Journal Jurnal Ilmu Komputer dan Teknologi (IKOMTI)
Arif Dennis Walidein
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Computer Science & IT

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Prototype Penggabungan Fuzzy Dan Naive Bayes dalam Analisis Citra Dokumen Untuk Penilaian Margin Laporan Praktikum UINSU Hafiz Aryanda; Randy, Muhammad Randy Fachrezi; Arif Dennis Walidein; Dimas Aqila Aptanta; Alwi Syahputra
Jurnal IT UHB Vol 6 No 2 (2025): Jurnal Ilmu Komputer dan Teknologi
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/ikomti.v6i2.1854

Abstract

Manual assessment of practicum report margins often faces challenges due to variations in document layout and the large number of reports that must be reviewed, resulting in an inefficient and subjective evaluation process. Therefore, this study aims to develop a prototype that serves as a guideline for automated practicum report assessment. The proposed research introduces a hybrid model integrating Fuzzy Logic and Naive Bayes. Evaluation results show that the model without fuzzy achieved an accuracy of 73.33% but exhibited bias toward the majority class, with low recall for the "Rejected" class. In contrast, the Fuzzy Naive Bayes model improved accuracy to 80% and produced more balanced classification performance, with significant increases in recall and F1 Score for the minority class. The integration of fuzzy logic effectively enhances the detection of margin non-compliance.
Co-Authors Alwi Syahputra Dimas Aqila Aptanta Hafiz Aryanda Randy, Muhammad Randy Fachrezi