Perbandingan Algoritma Logistic Regression dan K-Nearest Neighbor Dalam Klasifikasi Kematangan Buah Pepaya
DOI:
https://doi.org/10.47065/bulletincsr.v5i4.550Keywords:
Fruit Ripeness Classification; GLCM; Logistic Regression; K-Nearest NeighborAbstract
Visual assessment of papaya ripeness often leads to inconsistent and low accuracy results. To address this, the study applies Logistic Regression and K-Nearest Neighbor (K-NN) algorithms for automatic classification using digital image processing. The initial dataset consisted of 300 images, which were expanded to 1,200 through preprocessing and augmentation. Features were extracted using the Gray Level Co-occurrence Matrix (GLCM) method, and the data was split into 80% for training and 20% for testing. The study aims to compare the performance of both algorithms and understand their classification mechanisms. Results show that K-NN with k=1 achieved an accuracy of 87%, while Logistic Regression with L2 regularization reached 73%, indicating that K-NN outperforms Logistic Regression in classifying papaya ripeness levels.
Downloads
References
E. Tanadi, S. Palimbong, and K. B. Lewerissa, “Potensi Pemanfaatan Buah Pepaya dalam Produk Es Krim,” Applicable Innovation of Engineering and Science Research (AVoER), pp. 1–8, 2020.
R. Kurniawan, “Klasifikasi Tingkat Kematangan Buah Pepaya Berdasarkan Warna Kulit Menggunakan Sensor Warna TCS3200,” Journal ICTEE, vol. 4, no. 1, pp. 1–13, 2023.
F. M. Fathoni, C. A. Putra, and A. L. Nurlaili, “Klasifikasi Penyakit Daun Anggur menggunakan metode k-nearest neighbor Berdasarkan Gray level co-occurrence matrix,” Biner: Jurnal Ilmiah Informatika dan Komputer, vol. 3, no. 1, pp. 8–15, 2024.
R. A. Saputra, D. Puspitasari, A. Supriyatna, D. F. Saefudin, R. A. Purnama, and K. Ramanda, “Hyperparameter Optimization in CNN Algorithm for Chili Leaf Disease Classification” ICAISD, 2023
C. Suryanti and M. G. Rohman, “Klasifikasi Kualitas Buah Apel Berdasarkan Warna dan Bentuk Menggunakan Metode KNN,” Generation Journal, vol. 8, no. 1, pp. 34–41, 2024.
S. Raysyah, V. Arinal, and D. I. Mulyana, “Klasifikasi tingkat kematangan buah kopi berdasarkan deteksi warna menggunakan metode knn dan pca,” JSiI (Jurnal Sistem Informasi), vol 8, no 2, pp. 88–95, 2021.
Z. Zulkifli and R. Fajri, “Klasifikasi Tingkat Kematangan Buah Strawberry Menggunakan Algoritma Logistic Regression,” Data Sciences Indonesia (DSI), vol. 4, no. 2, pp. 50–59, Dec. 2024, doi: 10.47709/dsi.v4i2.4850.
H. P. Hadi and E. H. Rachmawanto, “Ekstraksi Fitur Warna Dan GLCM Pada Algoritma KNN Untuk Klasifikasi Kematangan Rambutan”, JIP (Jurnal Informatika Polinema), vol. 8, no. 3, 2022
K. A. Pratama, W. Priyo Atmaja, and V. Lusiana, “Klasifikasi Tingkat Kematangan Buah Kersen Menggunakan Citra HSI Dengan Metode K-Nearest Neighbor (KNN),” Jurnal Orang Pintar Komputer, vol. 11, no. 1, 2022, doi 10.30591/smartcomp.v11i1.3171
A. Rahmat, M. Syafiih, and M. Faid, “Implementasi Klasifikasi Potensi Penyakit Jantung Dengan Mengunakan Metode C4.5 Bberbasis Websute ( Studi Kasus Kaggle.Com ),” INFOTECH journal, vol. 9, no. 2, pp. 393–400, Jul. 2023, doi: 10.31949/infotech.v9i2.6295.
Adi Rizky, Ayu Ratna, Tohirin, “Klasifikasi Daging Sapi Berdasarkan Ciri Warna Dengan Metode Otsu dan K-Nearest Neighbor”, Techno Explore Jurnal Ilmu Komputer dan Informasi, Vol.6, No 1, 2021
N. Mega Saraswati, R. Cipta Sigitta Hariyono, and D. Chandra, “Face Recognition Menggunakan Metode Haar Cascade Classifier Dan Local Binary Pattern Histogram.”, Jurnal Media Elektrik, Vol.20, No.3, 2023
J. Khatib Sulaiman, N. Pramesti Aprilia, T. Herlina Rochadiani, and U. Pradita, “Image Captioning untuk Gambar Rambu Lalu Lintas Indonesia Menggunakan Pretrained CNN dan Transformer,” Indonesian Journal of Computer Science, Vol 13, No 3, 2024.
N. Mukaromah, S. Mulyono, and U. Islam Sultan Agung, "Implementasi Stable Diffusion Dan Fine-Tuning Low Rank Adaptation Untuk Pembuatan Logo," Jurnal Rekayasa Sistem Informasi dan Teknologi, No 3-Februari, 2025
Ni luh, Nyoman, Made, “Klasifikasi Jajanan Khas Bali Untuk Preservasi Pengetahuan Kuliner Lokal Menggunakan Arsitektur VGG-16”, Journal Sintech, vol 7, No.1-April 2024. Available: https://doi.org/10.31598
Fadli, Lucky, Lisnawita, “Klasifikasi Buah Pinang Berdasarkan Tingkat Kematangan Menggunakan Metode Naïve Bayes”, Journal Semaster, Vol 3, No 1, 2024.
I. Putu, C. Jumariana, and P. Sugiartawan, “Identifikasi Pengenalan Pola Daun Kelor Kering Dengan Yolo V8,” IJEIS (Indonesian Journal of Electronics and Instrumenations Systems, vol. 14, no. 1, pp. 91–100, 2024, doi: 10.22146/ijeis.94871.
J. C. Lapendy, A. A. C. Resky, H. Makmur, A. B. Kaswar, D. D. Andayani, and F. Adiba, “Klasifikasi rasa jeruk siam berdasarkan warna dan tekstur berbasis pengolahan citra digital,” JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), vol. 9, no. 2, pp. 756–767, 2024.
W. Shinta Sari and C. Atika Sari, “Klasifikasi Bunga Mawar Menggunakan KNN dan Ekstraksi Fitur GLCM dan HSV,” SKANIKA: Sistem Komputer dan Teknik Informatika, vol. 5, no. 2, pp. 145–156, 2022.
T. Pusdita and V. Lusiana, “JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal homepage: https://jurnal.stkippgritulungagung.ac.id/index.php/jipi Deteksi Motif Sarung Tenun Goyor Botolan Kabupaten Pemalang Menggunakan Metode KNN,” vol. 10, no. 1, pp. 473–481, 2025, doi: 10.29100/jipi.v10i1.5778.
N. D. Azzahra, A. Ambarwati, A. Desiani, S. I. Maiyanti, and I. Ramayanti, “Perbandingan Algoritma K-Nearest Neighbor Dan Logistic Regression Dalam Klasifikasi Penyakit Kanker Serviks,” Energy?: Jurnal Ilmiah Ilmu-Ilmu Teknik, vol. 14, no. 1, pp. 1–8, May 2024, doi: 10.51747/energy.v14i1.1843.
T. Nurmayanti, D. Hartini, T. Rohana, S. A. P. Lestari, and D. Wahiddin, “Comparison of K-Nearest Neighbors and Convolutional Neural Network Algorithms in Potato Leaf Disease Classification,” Jurnal Sistem Informasi dan Ilmu Komputer, vol. 8, no. 1, pp. 360–372, 2024.
I. M. A. A. Pramana, I. W. Sudiarsa, and P. G. S. C. Nugraha, “Penerapan Algoritma Naïve Bayes Untuk Prediksi Penjualan Produk Terlaris Pada CV Akusara Jaya Abadi,” JATISI (Jurnal Teknik Informatika dan Sistem Informasi), vol. 10, no. 4, 2023, doi: https://doi.org/10.35957/jatisi.v10i4.6498
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Perbandingan Algoritma Logistic Regression dan K-Nearest Neighbor Dalam Klasifikasi Kematangan Buah Pepaya
ARTICLE HISTORY
How to Cite
Issue
Section
Copyright (c) 2025 Wildan Amin Wiharja, Tohirin Al Mudzakir, Hilda Yulia Novita, Jamaludin Indra
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
