Prediksi Tingkat Pemahaman Siswa terhadap Data Nominatif Menggunakan Metode Monte Carlo

Abstract

Kerinci Regency which was established on November 10, 1957 from the results of the division of 3 provinces, namely West Sumatra Province, Riau Province, Jambi Province. The district which is nicknamed the City of Sakti Alam Kerinci has a population of 253,258 people with an area of ​​3,808 km and consists of 16 sub-districts. So that training, technology, and improving Maunisa Resources are needed in various aspects of Kerinci society. Determine the level of accuracy of the Monte Carlo method simulation between the simulation results and the real data. In this study, the main data used were data for 2017, 2018 and 2019. The variable used in this study was the frequency of student scores in participating in learning. The value data will be processed using the Monte Carlo method assisted by Microsoft Excel for manual search. Student grade data for 2017 is used as trial data to predict in 2018, data for 2018 is used as trial data to predict the number of 2019, and data for 2019 will be used to predict the number in 2020 later. Where the highest prediction result is 96% where there are several competencies that have the same value. So that the average resulting from the predicted accuracy is 95% of the 7 competencies. The test results have clearly formed the boundaries. With an accuracy rate of 95%, it can be recommended to help the UPTD Kerinci District Work Training Center in predicting the level of understanding of students.