Prototype Penggabungan Fuzzy Dan Naive Bayes dalam Analisis Citra Dokumen Untuk Penilaian Margin Laporan Praktikum UINSU
DOI:
https://doi.org/10.35960/ikomti.v6i2.1854Keywords:
compliance of margins, image analysis, evaluation, fuzzy, naive bayesAbstract
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.
References
[1] U. P. Pengaraian, “Penulisan skripsi,” 2022, [Online]. Available: https://pbio.uinsu.ac.id/
[2] B. Bataineh, “A Comprehensive Review on Document Image (DIBCO) Database,” A Compr. Rev. Doc. Image Bin., vol. 557, no. 1, pp. 1–30, 2025, doi: 10.1088/1757-899X/557/1/012006.
[3] D. T. Anggraeni, “Perbaikan Citra Dokumen Hasil Pindai Menggunakan Metode Simple, Adaptive-Gaussian, dan Otsu Binarization Thresholding,” Expert J. Manaj. Sist. Inf. dan Teknol., vol. 11, no. 2, p. 71, 2021, doi: 10.36448/expert.v11i2.2170.
[4] M. K. Gibran, M. I. Rifki, A. H. Hasugian, A. T. A. A. Siahaan, A. Sahputra, and R. Ong, “Sentiment Analysis of Platform X Users on Starlink Using Naive Bayes,” vol. 15, no. June, pp. 113–119, 2024, [Online].
[5] F. Azmi, M. K. Gibran, A. Ridwan, and A. Saleh, “Enhancing Water Potability Assessment Using Hybrid Fuzzy-Naïve Bayes,” Indones. J. Comput. Sci., vol. 12, no. 3, pp. 1032–1043, 2023, doi: 10.33022/ijcs.v12i3.3232.
[6] T. P. Negara, “PENERAPAN IMPLEMENTASI NAÏVE BAYES CLASSIFIER DAN METODE FUZZY AHP DALAM PENENTUAN BUKU LAYAK TERBIT MENGGGUNAKAN ANDROID Teguh,” Semin. Nas. Teknol. Inf. dan Komun. (SeNTIK STI&K), 2024.
[7] D. C. M. Wijaya, B. Rahmat, and E. Y. Puspaningrum, “Sistem Pendukung Keputusan Berbasis Interval Type-2 Fuzzy Sugeno Pada Kendali pH Air,” InComTech J. Telekomun. dan Komput., vol. 12, no. 3, p. 226, 2022, doi: 10.22441/incomtech.v12i3.15453.
[8] T. Tundo and S. Saifullah, “Fuzzy Inference System Mamdani dalam Prediksi Produksi Kain Tenun Menggunakan Rule Berdasarkan Random Tree,” J. Teknol. Inf. dan Ilmu Komput., vol. 9, no. 3, pp. 443–452, 2022, doi: 10.25126/jtiik.2022924212.
[9] R. Riskaputra, Implementasi logika fuzzy mamdani dalam optimasi harga jasa distribusi produk (studi kasus: Kantor Konsultan Marketing RnD Enterprises). 2023. [Online]. Available: https://repository.uinjkt.ac.id/
[10] P. S. Saputra, “Perbandingan Algoritma Fuzzy C-Means Dan Algoritma Naive Bayes Dalam Menentukan Keluarga Penerima Manfaat (Kpm) Berdasarkan Status Sosial Ekonomi (Sse) Terendah,” JST (Jurnal Sains dan Teknol., vol. 10, no. 1, pp. 1–8, 2021, doi: 10.23887/jstundiksha.v10i1.23340.
[11] A. S. Putra, S. Budiprayitno, and L. P. Rahayu, “Perancangan Sistem Kontrol pH dan Suhu Air Menggunakan Metode Fuzzy dan Terintregasi dengan Internet of Things (IoT) pada Budidaya Ikan Hias,” J. Tek. ITS, vol. 10, no. 2, pp. 444–449, 2021, doi: 10.12962/j23373539.v10i2.74902.
[12] A. Fadhli Rachman and Nuryuliani, “Analisis Tingkat Kepuasan Karyawan terhadap Aplikasi Service Desk menggunakan Metode Fuzzy Service Quality (Studi Kasus: Perusahaan Kliring di Jakarta) Analysis of Employee Satisfaction Levels with Service Desk Applications using the Fuzzy Service Quality,” J. Bina Komputer), vol. 4, no. 1, pp. 23–32, 2022.
[13] A. Saleh, A. Ridwan, and M. K. Gibran, “Machine Learning and Fuzzy C-Means Clustering for the Identification of Tomato Diseases,” Indones. J. Comput. Sci., vol. 12, no. 5, pp. 2401–2413, 2023, doi: 10.33022/ijcs.v12i5.3379.
[14] J. Saputra, Y. Sa, V. Yoga Pudya Ardhana, and M. Afriansyah, “RESOLUSI : Rekayasa Teknik Informatika dan Informasi Klasifikasi Kematangan Buah Alpukat Mentega Menggunakan Metode K-Nearest Neighbor Berdasarkan Warna Kulit Buah,” Media Online, vol. 3, no. 5, pp. 347–354, 2023, [Online]. Available: https://djournals.com/resolusi
[15] D. T. Anggraeni and C. Wibawa, “Perbaikan Citra Tanda Tangan Digital Menggunakan Metode Otsu Thressholding dan Sauvola,” J. Ilm. Matrik, vol. 25, no. 1, pp. 28–34, 2023, doi: 10.33557/jurnalmatrik.v25i1.2324.
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Copyright (c) 2025 Hafiz Aryanda, Muhammad Randy Fachrezi Randy, Arif Dennis Walidein, Dimas Aqila Aptanta, Alwi Syahputra (Author)
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