Case-Based Reasoning System to Determine the Types of Fish Farming Based on Water Quality
Hindayati Mustafidah, SUWARSITO SUWARSITO, Ekky Puspitasari · 2020 Fifth International Conference on Informatics and Computing (ICIC) · 2020
Case-based reasoning (CBR) is a method of developing artificial intelligence, undoubtedly its ability to help solve problems based on experience. In cases where freshwater fish farmers find it difficult to determine the right type of fish, they need tools to increase their cultivation yield. Fish can live in quality water media. The incompatibility of water conditions with the kinds of fish being cultivated results in less than optimal. These caused fish has different environmental characteristics and nutritional needs. Therefore a CBR system was developed to help fish cultivators to obtain information on the types of fish that are under the existing water quality conditions. The input variables in this study were water quality parameters, namely: temperature, pH, ammonia (NH3), nitrite (NO2), dissolved oxygen (DO), carbon dioxide (CO2), and salinity. There are 28 types of freshwater fish used in this system as a case-based solution. These types of fish are commonly cultivated in Indonesia. The user enters the water quality parameter feature to be used as a reference by CBR in determining a solution, namely the suitable freshwater fish species. The solution obtained is based on the highest level of similarity between user input variables and case-based data. Thus, the CBR system can be used as a reference for determining the types of freshwater fish that will be cultivated by fish farmers.