A STRATEGI MEMPREDIKSI TINGKAT KELULUSAN MAHASISWA UNIVERSITAS MUHAMMADIYAH PONOROGO DENGAN TEORI FUZZY TSUKAMOTO - Ranti Kurniasih; Annafi Awantagusnik; Muhammad Zia Alghar (MUST: Journal of Mathematics Education, Science and Technology, 2024)
The purpose of this research is to create a mathematical model related to fuzzy logic to predict student graduation rates starting in 2024. This type of research is applied research. The method used is the tsukamoto method in fuzzy analysis and checking the accuracy of forecasting with MAPE. Data collection techniques are carried out by collecting primary data and secondary data. The primary data used is data on new student admissions, many graduates, and many graduates from Muhammadiyah Ponorogo University in 2021, 2022, and 2023. Secondary data is obtained from books, articles, and documents relevant to Tsukamoto fuzzy. The results of the Tsukamoto fuzzy analysis with MAPE testing show that the fuzzy model built is at a percentage of 5.3%. This means that the fuzzy system has excellent forecasting capabilities in predicting student graduation rates in 2021, 2022, and 2023 and can be used to predict many graduates in 2024.