Prediction of Successful Harvest of Vaname Shrimp Pond at PT FEI With Machine Learning Approach

Abstract

The demand for shrimp from Indonesia continues to increase every year, thus creating greater interest in the shrimp farming industry. Although shrimp is relatively easy to farm, many variables affect the success of the harvest. The harvest in shrimp farming is calculated using % SR (Survival Rate). In our research, we used machine learning approaches, namely decision tree (DT) and k-Nearest Neighbor (KNN). DT and KNN will be used to predict whether we will have a successful harvest. From these predictions, we also provide suggestions for business improvements to utilize data. The expected result of such advice is that the business can improve its performance and get more consistent results.