Determination of the right food crops needs to be done to improve the community's economy in the agricultural sector. The use of traditional cropping patterns needs to be changed by utilizing information technology. The utilization of data from local governments can be used to assist in providing recommendations for types of food crops by processing them with several data mining methods. This method can extract information to find patterns and knowledge from the data. The classification method approach is used as a grouping of data based on data attachment to sample data. This study uses several classification methods, namely Naïve Bayes, Decision Tree, Support Vector Machine (SVM), Neural Network, Random Tree, Random Forest, dan K Nearest Neighbor (KNN). These methods were successfully compared to find out which method is the best to help recommend appropriate and accurate food crops based on the results of the classification performance of each method. Random Tree was chosen as the best method for the results of this performance comparison using discretization and normalization methods at the pre-processing stage of the data. It can be seen based on the results of the Accuracy, Precision, Recall, and F1-Score values on the use of discretization of 98%, respectively. Meanwhile, normalization showed that the results of the Accuracy, Precision, Recall, and F1-Score values are 99%, respectively.

Logika fuzzy salah satu komponen pembentuk soft computing yang digunakan sebagai cara untuk memetakan masalah dari input ke output yang diharapkan. logika fuzzy memiliki beberapa kelebihan seperti mudah dimengerti karena memiliki konsep matematis yang sederhana, fleksibel untuk digunakan, terdapat toleransi pada data-data yang tidak tepat, mampu memodelkan fungsi-fungsi non-linear yang sangat kompleks, dapat menerapkan pengalaman pakar secara langsung tanpa proses pelatihan, dapat bekerja sama dengan teknik-teknik kendali secara konvensional, dan didasarkan pada bahasa alami. Logika fuzzy memiliki banyak peran di industri seperti bidang Kesehatan, Ilmu Ekonomi, Psikolog, dan Teknologi yang dapat membantu manusia dalam memecahkan suatu masalah dalam kehidupan. Dalam penerapan logika fuzzy terdapat beberapa proses, salah satunya yaitu sistem inferensi. Sistem inferensi merupakan kerangka komputasi yang didasarkan pada teori himpunan fuzzy, aturan fuzzy berbentuk IF-THEN, dan penalaran fuzzy. Manfaat dari inferensi fuzzy yaitu sebagai alat untuk mewakili pengetahuan yang berbeda tentang suatu masalah, serta untuk memodelkan interaksi. Dengan menggunakan metode penelitian studi literatur dari beberapa sumber, ditemukan banyak produk yang dikembangkan dari logika fuzzy seperti pengambilan keputusan, penentuan atau penilaian hasil, perangkat kendali jarak jauh, alat ukur, dan sistem pakar.

Final Judgment is a process of consideration to declare a student has met the academic and administrative requirements to hold a scholarship academic degree from the college. The Final Judgment management process business in universities involves many processes and stakeholders. Based on the result of observations and interviews, it is known that Final Judgment Management at the Informatics Faculty of ITTP is currently done manually by filling out the registration form and takes a long time for its processing. This study aims to develop Information Systems using User-Centered Design (UCD) methods that can meet the users' needs in implementing and managing Final Judgment processes. The developed system was tested for usability using a questionnaire to users with the Nielsen Attribute Usability (NAU) method. The method consists of five criteria, they are Learnability, Memorability, Efficiency, Errors, and Satisfaction. Usability test results showed: Learnability rate of 3.60, Memorability of 3.35, Efficiency of 3.90, Errors of 3.12, and Satisfaction of 3.63. Therefore, the average usability level of the Final Judgment system is 3.52. The user agrees that the developed Final Judgment information system has met the expected functional needs and is considered more effective and efficient.