Implementasi Metode Naïve Bayes pada Sistem Pakar Kalkulator Genetik Leopard Gecko Berbasis Web (Studi Kasus: Arie Gecko Farm)

Abstract

Leopard gecko (Eublepharis Macularius) is an ornamental reptile with various morph determined by the genetic combination of its parent. Predicting offspring morph is commonly performed manually, making the process time-consuming and highly dependent on the breeder’s experience. This study aims to develop a web-base Leopard Gecko genetic calculator expert system using the Naïve Bayes method to automatically predict offspring morph. The system was developed using the System Development Life Cycle (SDLC) with the waterfall model, consisting of requirements analysis, system design, development, implementation, testing, and maintenance. The application was built using the Laravel framework, PHP programming language, and MySQL database. Research data were collected through observation, documentation, and literature review, while the classification process utilized training data based on the Naïve Bayes algorithm. The result indicate that the system is capable of generating offspring genetic features, calculating prior, likelihood,, and posterior probabilities, and predicting the most probable morph management, training data management, prediction history, and role-based user access. Black Box testing showed that all major system functions operated as expected. Therefore, the developedexperd system can assist Leopard Gecko breeders in predicting offspring morph more efficiently, systematically, and accurately through a web-based application.