Prediksi Pajak Pertambahan Nilai pada Penyediaan Jasa dengan Metode Fuzzy Time Series Model Chen - Lestari, Sri; Yurinanda, Sherli (Universitas Negeri Gorontalo, 2023)
For companies, tax is a burden or fee that must be paid to the state as a taxpayer. The taxes that must be paid by the company can affect the profits earned. Therefore, efforts are needed to reduce or minimize the tax burden. Efforts to minimize the tax burden include tax planning. Tax planning that is often used by companies is tax planning on Value Added Tax (VAT), because all production activities are closely related to the VAT burden. Tax planning for VAT can be done by maximizing the amount of input VAT. To be able to identify the amount of input VAT in the next period, predictions can be made on the input VAT value. The uncertain VAT value and limited data collection make it possible to predict the VAT value using the fuzzy time series method. One model that can be used in fuzzy time series is the Chen model, because it has better accuracy values than the Song and Chissom models. Based on this research, it can be seen that the results of the prediction of the VAT value for the provision of services at PT Pertamina Hulu Rokan Zone 1, for the period July 2023 using the fuzzy time series Chen model method in second order obtained IDR 1,455,000,000 with a forecasting accuracy of 82.1%. In this way, PT PHR Zone 1 can maximize input VAT of IDR 1,455,000,000 so that the goal of minimizing the tax burden is achieved.