Implementation of KNN algorithm in classifying diabetic ulcers in patients with diabetes mellitus
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Published:
Aug 30, 2023
Keywords:
Classification, Data Science, Diabetes Mellitus, Diabetic Ulcer, K-Nearest Neighbour
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Computer Science
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Abstract
The rapid development of the times, humans face various types of diseases that exist, even some of these types of diseases can be fatal and even death, one of the most famous diseases is diabetes mellitus. Diabetic ulcers are caused by diabetes mellitus. The risk of people with diabetes mellitus is 29 times that there will be diabetic ulcer complications, and the potential to experience diabetic ulcers is 15-25% during their lifetime and within 5 years has a recurrence rate of 50-70%. This research uses the K-Nearest Neighbor algorithm with the Gray Level Co-Occurrence model which is the extraction of image or texture features from images. Using the calculate_glcms(image) function to calculate some features of the GLCM matrix given an image as input. GLCM: greycomatrix(image,[1], [0, np.pi/4, np.pi/2,3 np.pi/4], levels=256, symmetric=True, normed=True) calculates the GLCM matrix of the image with pixel distance 1 and angle 0, np.pi/4, np.pi/2, and3 np.pi/4. Conclusion of this research is the test result matrix, the accuracy is 0.94 (94%), precision 0.928, recall 0.905, F-1 Score 0.907 and support of 66.
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Siregar, S. D., Ginting, Y. U. R., Sintami, N. ., Butar-Butar, H. S. . and Simanjuntak, R. M. . (2023) “Implementation of KNN algorithm in classifying diabetic ulcers in patients with diabetes mellitus”, Jurnal Mantik, 7(2), pp. 691-701. doi: 10.35335/mantik.v7i2.3928.
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Sarimole, F. M., & Syaeful, A. (2022). Classification of Durian Types Using Features Extraction Gray Level Co-Occurrence Matrix (Glcm) and K-Nearest Neighbors (Knn). Journal of Applied Engineering and Technological Science, 4(1), 111–121. https://doi.org/10.37385/jaets.v4i1.959
Shakya, D. S. (2020). Analysis of Artificial Intelligence based Image Classification Techniques. Journal of Innovative Image Processing, 2(1), 44–54. https://doi.org/10.36548/jiip.2020.1.005
Shidiq, F. (2021). Penerapan Metode K-Nearest Neighbor (KNN) Untuk Menentukan Ikan Cupang Dengan Ekstraksi Fitur Ciri Bentuk Dan Canny. Innovation in Research of Informatics (INNOVATICS), 3(2), 39–46. https://doi.org/10.37058/innovatics.v3i2.3093
Subhannur Rahman, Yumi Baida Rahmah. (2020). Literature Review: Kebutuhan Spiritual Pada Pasien Dengan Ulkus Diabetik. Nursing Science Journal (NSJ), 1(2), 6–11. https://doi.org/10.53510/nsj.v1i2.25
Syarifah, A., Riadi, A. A., & Susanto, A. (2022). 417-1274-1-Pb. 7(1), 27–35.
Utia Detty, A., Fitriyani, N., Prasetya, T., & Florentina, B. (2020). Karakteristik Ulkus Diabetikum Pada Penderita Diabetes Melitus The Characteristics of Diabetic Ulcer in Patients with Diabetes Mellitus. Juni, 11(1), 258–264. https://doi.org/10.35816/jiskh.v10i2.261
Fauzi, A. A., Utaminingrum, F., & Ramdani, F. (2020). Road surface classification based on LBP and GLCM features using KNN classifier. Bulletin of Electrical Engineering and Informatics, 9(4), 1446–1453. https://doi.org/10.11591/eei.v9i4.2348
Haesri, B., Fitriyah, H., Hannats, M., & Ichsan, H. (2022). Klasifikasi Kesiapan Panen Tanaman Hidroponik Bayam Hijau menggunakan Metode Pengolahan Citra dan K-Nearest Neighbours berbasis Raspberry Pi. 6(12), 5931–5939.
Harahap, M., Anjelli, S. K., Sinaga, W. A. M., Alward, R., Manawan, J. F. W., & Husein, A. M. (2022). Classification of diabetic foot ulcer using convolutional neural network (CNN) in diabetic patients. Jurnal Infotel, 14(3), 196–202. https://doi.org/10.20895/infotel.v14i3.796
Huang, T. Y., Zhan, S. Q., Chen, P. J., Yang, C. W., & Lu, H. H. S. (2021). Accurate diagnosis of endoscopic mucosal healing in ulcerative colitis using deep learning and machine learning. Journal of the Chinese Medical Association, 84(7), 678–681. https://doi.org/10.1097/JCMA.0000000000000559
Ikhsan, D., Utami, E., & Wibowo, F. W. (2020). Metode Klasifikasi Mutu Greenbean Kopi Arabika Lanang Dan Biasa Menggunakan K-Nearest Neighbor Berdasarkan Bentuk. Jurnal Ilmiah SINUS, 18(2), 1. https://doi.org/10.30646/sinus.v18i2.456
Khorasani, H. M., Usefi, H., & Peña-Castillo, L. (2020). Detecting ulcerative colitis from colon samples using efficient feature selection and machine learning. Scientific Reports, 10(1), 1–9. https://doi.org/10.1038/s41598-020-70583-0
Kurnaiwan, Muhamand Reinaldi Purnamasari, R., & Fuadah, R. Y. N. (2021). Sistem Klasifikasi Sel Darah Putih Berbasis Pengolahan Citra Digital dan Jaringan Saraf Tiruan White Blood Cell Classification System Based on Digital Image Processing and Neural Network. E-Proceeding of Engineering?:, 8(1), 1–6.
Laia, M., Hondro, R. K., & Zebua, T. (2021). Implementasi Pengolahan Citra dengan Menggunakan Metode K-Nearest Neighbor Untuk Mengetahui Daging Ayam Busuk dan Daging Ayam Segar. 8(2), 39–49. https://doi.org/10.30865/jurikom.v8i2.2818
Larijani, M. R., Asli-Ardeh, E. A., Kozegar, E., & Loni, R. (2019). Evaluation of image processing technique in identifying rice blast disease in field conditions based on KNN algorithm improvement by K-means. Food Science and Nutrition, 7(12), 3922–3930. https://doi.org/10.1002/fsn3.1251
Liantoni, F. (2016). Klasifikasi Daun Dengan Perbaikan Fitur Citra Menggunakan Metode K-Nearest Neighbor. Jurnal ULTIMATICS, 7(2), 98–104. https://doi.org/10.31937/ti.v7i2.356
Mardisa, R., Nasution, I. S., & Siregar, K. (2022). Klasifikasi Kualitas Fisik Kopi Beras Arabika Menggunakan Pengolahan Citra Dengan Metode K-Nearest Neighbor (K-NN). Jurnal Ilmiah Mahasiswa Pertanian, 7(2), 514–522. http://www.jim.unsyiah.ac.id/JFP/article/view/19896%0Ahttp://www.jim.unsyiah.ac.id/JFP/article/download/19896/9640
Masker, D., & Wajah, P. (2022). Principal Component Analysis … (Krismawan & Rachmawanto). 12(1), 382–389.
Muhammad, D. I., Ermatita, E., & Falih, N. (2021). Penggunaan K-Nearest Neighbor (KNN) untuk Mengklasifikasi Citra Belimbing Berdasarkan Fitur Warna. Informatik?: Jurnal Ilmu Komputer, 17(1), 9. https://doi.org/10.52958/iftk.v17i1.2132
Of, L., & Of, M. (n.d.). SVM V S KNN FOR C LASSIFICATION OF H ISTOPATHOLOGICAL I MAGES. 3(2), 19–28.
Pawening, R. E., Shudiq, W. J., & Wahyuni, W. (2020). KLASIFIKASI KUALITAS JERUK LOKAL BERDASARKAN TEKSTUR DAN BENTUK MENGGUNAKAN METODE k-NEAREST NEIGHBOR (k-NN). COREAI: Jurnal Kecerdasan Buatan, Komputasi Dan Teknologi Informasi, 1(1), 10–17. https://doi.org/10.33650/coreai.v1i1.1640
Puspita, R., & Widodo, A. (2021). Perbandingan Metode KNN, Decision Tree, dan Naïve Bayes Terhadap Analisis Sentimen Pengguna Layanan BPJS. Jurnal Informatika Universitas Pamulang, 5(4), 646. https://doi.org/10.32493/informatika.v5i4.7622
Reddy, S. S., Mahesh, G., & Preethi, N. M. (2021). Exploiting Machine Learning Algorithms to Diagnose Foot Ulcers in Diabetic Patients. EAI Endorsed Transactions on Pervasive Health and Technology, 7(29), 1–14. https://doi.org/10.4108/eai.24-8-2021.170752
Saputro, W., Sumantri, D. B., Tinggi, S., Komputer, I., & Karya Informatika, C. (2022). Implementasi Citra Digital Dalam Klasifikasi Jenis Buah Anggur Dengan Algoritma K-Nearest Neighbors (Knn) Dan Data Augmentasi Digital Image Implementation in Grape Classification With K-Nearest Neighbors (Knn) Algorithm and Augmentation Data. Journal of Information Technology and Computer Science (INTECOMS), 5(2), 248–253.
Sarimole, F. M., & Syaeful, A. (2022). Classification of Durian Types Using Features Extraction Gray Level Co-Occurrence Matrix (Glcm) and K-Nearest Neighbors (Knn). Journal of Applied Engineering and Technological Science, 4(1), 111–121. https://doi.org/10.37385/jaets.v4i1.959
Shakya, D. S. (2020). Analysis of Artificial Intelligence based Image Classification Techniques. Journal of Innovative Image Processing, 2(1), 44–54. https://doi.org/10.36548/jiip.2020.1.005
Shidiq, F. (2021). Penerapan Metode K-Nearest Neighbor (KNN) Untuk Menentukan Ikan Cupang Dengan Ekstraksi Fitur Ciri Bentuk Dan Canny. Innovation in Research of Informatics (INNOVATICS), 3(2), 39–46. https://doi.org/10.37058/innovatics.v3i2.3093
Subhannur Rahman, Yumi Baida Rahmah. (2020). Literature Review: Kebutuhan Spiritual Pada Pasien Dengan Ulkus Diabetik. Nursing Science Journal (NSJ), 1(2), 6–11. https://doi.org/10.53510/nsj.v1i2.25
Syarifah, A., Riadi, A. A., & Susanto, A. (2022). 417-1274-1-Pb. 7(1), 27–35.
Utia Detty, A., Fitriyani, N., Prasetya, T., & Florentina, B. (2020). Karakteristik Ulkus Diabetikum Pada Penderita Diabetes Melitus The Characteristics of Diabetic Ulcer in Patients with Diabetes Mellitus. Juni, 11(1), 258–264. https://doi.org/10.35816/jiskh.v10i2.261
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