Perbandingan Peramalan Kasus Katarak Menggunakan Metode ARIMA dan Fuzzy Time Series di Rumah Sakit - Arifin, Zainal ARIFIN (Jurnal Manajemen Kesehatan Yayasan RS.Dr. Soetomo, 2025)
ABSTRAKMetode ARIMA (Autoregressive Integrated Moving Average) dan metode Fuzzy Time Series merupakan metode peramalan yang dapat diterapkan untuk meramalkan jangka pendek, menengah, dan panjang serta memiliki tingkat akurasi yang baik. Kedua metode ini akan digunakan untuk meramalkan kasus katarak di RS. Mata Undaan. Tujuan dari penelitian ini adalah untuk mengetahui hasil peramalan jumlah kasus katarak di RS. Mata Undaan pada tahun 2024 berdasarkan data kasus katarak sejak Januari 2012 sampai Desember 2023. Penelitian ini bersifat kuantitatif deskriptif dengan menggunakan software Minitab 19 untuk mengimplementasikan metode ARIMA dan PHP Source Code untuk Fuzzy Time Series model Chen. Hasil penelitian menunjukkan, bahwa pada penghitungan MAD, nilai ARIMA (1,1,1) sebesar 44,57, ARIMA (2,1,2) sebesar 45,54 dan Fuzzy Time Series model Chen sebesar 96,66. Hasil penghitungan MSE, nilai ARIMA (1,1,1) sebesar 3.098,11, ARIMA (2,1,2) sebesar 4.404,96 dan Fuzzy Time Series model Chen sebesar 9.406,75. Hasil penghitungan MAPE, nilai ARIMA (1,1,1) sebesar 7,68%, ARIMA (2,1,2) sebesar 8,02% dan Fuzzy Time Series model Chen sebesar 16,16%. Kesimpulan yang dapat diambil adalah metode ARIMA memiliki tingkat akurasi yang lebih baik jika dibandingkan dengan metode Fuzzy Time Series model Chen dalam meramalkan kasus katarak. ABSTRACTThe ARIMA (Autoregressive Integrated Moving Average) method and the Fuzzy Time Series method are forecasting methods that can be applied to short, medium, and long-term predictions and have a good level of accuracy. These two methods will be used to predict cataract cases in hospitals. Undaan's eyes. The purpose of this study is to find out the results of predicting or forecasting the number of cataract cases in hospitals. Undaan's eyes in 2024 based on data on cataract cases from January 2012 to December 2023. This research is quantitative descriptive by using Minitab 19 software to implement the ARIMA method and PHP Source Code for the Fuzzy Time Series Chen model. The results of the study show that in the MAD calculation, the value of ARIMA (1,1,1) is 44.57, ARIMA (2,1,2) is 45.54 and the Fuzzy Time Series model of Chen is 96.66. The results of the MSE calculation showed that the value of ARIMA (1,1,1) was 3,098.11, ARIMA (2,1,2) was 4,404.96 and the Fuzzy Time Series of the Chen model was 9,406.75. The results of the MAPE calculation showed that the value of ARIMA (1,1,1) was 7.68%, ARIMA (2,1,2) was 8.02% and the Fuzzy Time Series model of Chen was 16.16%. The conclusion that can be drawn is that the ARIMA method has a better level of accuracy when compared to the Fuzzy Time Series method of the Chen model in the implementation of cataract case prediction. Key words : ARIMA, Fuzzy Time Series, Chen, MAD, MSE, MAPE