System to Diagnose Periodontics Disease (Gum Disease) Using K-Nearest Neighbour Alghoritms - Ahmad Fitri Boy; Amrullah; Egi Affandi (Institute of Computer Science (IOCS), 2020)
A Technological Growth has occurred rapidly at this time.not only in the fields of information,industrial or education but also in the agricultural fields. Therefore the sophistication of the technology was also utilized in order to getting an information about Periodontics (gum disease).Periodontics caused by poor oral hygiene condition.in this problem, a technique that used to diagnose Periodontics disease to be able to helping the doctors and citizens about the disease is really necessary. Therefore the author will design and developing a desktop-based application expert sytem to diagnose Periodontics disease using K-Nearest Neighbor method.Systems will analyze someone based on the previous data of the patients.as a user,patients will insert a data based to their symptomps in order to generate not only an identification of the probabilities accuracy data but also the solution about this disease.this expert system was developed with K-Nearest Neighbor methods for measuring a certainty value from the new hypothesis of new facts based on the previous consultation data records of the patient.the calculation of K-Nearest Neighbor methods has been generated 0.72 or 72% of trust value from one Periodontics disease based on the result of consultation.