Implementasi Algoritme Modified K-Nearest Neighbor (MKNN) Untuk Mengidentifikasi Penyakit Gigi Dan Mulut - Muhammad Reza Ravi; Indriati Indriati; Sigit Adinugroho (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Teeth and mouth are the most important parts of the human body that must be maintained and cared for. But the problem of dental and oral diseases in Indonesia still needs attention. There are several types of dental and oral diseases. The most common diseases suffered by the people of Indonesia are cavities, dental caries and periodontitis. The causes of dental and oral disease are poor hygiene of the teeth, eating foods and drinks that contain high carbohydrates, smoking, consuming alcoholic beverages, brushing teeth incorrectly and also growing imperfect gums. It has symptoms, among others, the teeth become more sensitive, the emergence of an erratic pain, and often feel pain or pain when biting something. In this study, identification of the types of dental and oral diseases determined from symptoms experienced using the classification method Modified K-Nearest Neighbor (MKNN). The MKNN method is the development method of the NNC, there are differences from MKNN and KNN namely MKNN there is a process of calculating validity and Weight Voting. This study used 6 classes which included Pulpitis, Gingivitis, Dental Caries, Periodontitis, Deposits, and Pulp Necrosis. This study proves that in the training data as many as 70 and 30 test data and K = 60, the MKNN method can identify the types of dental and oral diseases by reaching 86.6%. This study also proves that the MKNN method tends to be more accurate compared to the KNN method where the MKNN method has an accuracy rate of 76.66% while the KNN is 43.33%. this is caused by the calculation of the validity value which will affect the Weight Voting and also the accuracy.