id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-2051	Ekowati, Ch. Krisnandari ; Garak, Siprianus Suban ; Madu, Aleksius ; Rimo, Imelda Hendriani Eku ; Halim, Fransiska Atrik 	Time series data analysis to forecast the percentage of on-time graduates at Nusa Cendana university	2024	19	.pdf	application/pdf	9506	581	60	The results show that the combination of machine learning algorithms and ARIMA models is a valid model for predicting student status (Karl Ferdinand Loder, 2023). The general form of the AR model with order p (AR(p)) or ARIMA model (p,0,0) is as follows (Adi Soetrisno et al., 2019): 𝑋𝑡 = 𝑎1𝑋𝑡−1 + 𝑎2𝑋𝑡−2 +⋯+ 𝑎𝑃𝑋𝑡−𝑃 + 𝜀𝑡 , 𝑡 ∈ 𝑍 (3) where Xt is the observation value at time t, ai for i=1,2, ..., p is the AR model parameter, and εt is the error at time t. (e).	cache/easat-2051.pdf	txt/easat-2051.txt