Sistem Pakar Untuk Diagnosa Penyakit Hewan Sapi Menggunakan Metode Promethee

Abstract

Expert systems are part of artificial intelligence. Expert systems can be used to diagnose cow disease from the symptoms experienced by using the knowledge of experts and veterinarians. The data for this study include symptom data, disease data, and rule data using the Promethee (Preference Ranking Organization Methods for Enrichment Evaluations) method. As a decision-making tool by comparing the weight of each symptom between one disease and another by using the value of preference criteria. Cow farming is a promising business, caution must be taken when running a livestock business regarding diseases that attack cows. The expert system is able to diagnose livestock disease results quickly and accurately for primary treatment before being handled directly by veterinarians. In this expert system for diagnosing cow diseases using the Promethee method, the main process is to add up the paired comparison deviation values ​​for each disease and add up the ranking values ​​in the form of Entering Flow, Leaving Flow, and Net Flow. At the output of the system as many as 42 test data produces an accuracy rate of 90.47% and is declared feasible and works well. The difference in the level of accuracy for each type of preference affects the determination of the weight of each symptom and the determination of the limit value and trend value in the calculation. The results of the questionnaire from 14 users using the System Usability Scale (SUS) testing method 84% said that the usability of the system evaluated was above average (good).