Prediction of Rice Field Planted Area with CRISP-DM Using Classification and Regression Tree (Cart) Algorithms : Prediksi Luas Tanam Sawah dengan CRISP-DM Menggunakan Algoritma Classification and Regression Tree (Cart) - Elfina Novalia; Apriade Voutama; Garno (Universitas Singaperbangsa Karawang, 2023)
Every year the area of paddy fields in Karawang Regency has increased and decreased due to land conversion. Climate change also causes changes in the amount of rain and rain patterns that cause shifts in the beginning of the season and the planting period. If the decrease in planting area will be affected, then the price of rice will increase and farmers will maintain the area and not convert their rice fields to function, therefore a study was conducted to predict the rice planting area in order to know the description of the area of rice planted in Karawang Regency will increase. , decreased or stabilized. So the search for information on the data on the area of rice planting in Karawang Regency was carried out. A total of 180 data were processed using data mining techniques so that they could mine information from the data. Data mining is a technique of extracting or new discoveries from large data and then extracting the data into information that can later be used. Experiments were carried out using the CART algorithm and cross validation using the Weka tools. The results of the evaluation carried out can be concluded that the CART algorithm using different K values provides different evaluation results. The performance of the algorithm is seen from the accuracy, precision, recall and F-Measurement, thus providing different performance values for each result. The value of k=8 has the highest accuracy value, which is 90% with precision 0.918%, recall 0.906% and F-measure 0.949%.