ANALYSIS FORECASTING OF OPERATIONAL EXPENSES OF PT. BANK TABUNGAN NEGARA TBK
DOI:
https://doi.org/10.32493/sm.v3i2.10110Keywords:
Forecasting, Operating Expenses, Least SquareAbstract
One of the strategic aspects of Bank BTN is meeting customer needs by providing quality services to compete in the banking industry. Therefore, it is necessary to have the ability to understand and deal with uncertainty to predict future business conditions so that the company can take appropriate steps or reduce risks in dealing with this uncertainty. This article aims to discuss the analysis of forecasting Bank BTN operating expenses. Forecasting is done by using the time series method by calculating the error rate (the difference between the results of the events and the research results). This article’s type of time series method is the least-squares method based on past data, while MAD and MAPE are used to calculate forecast errors. The research data used is included in secondary data, namely BTN operating expenses data obtained from the BTN website from 2013 to the 2nd quarter, to 2020 in the 3rd quarter. Forecasting data analysis shows that using the least square method to predict the operational expenses of the BTN bank in the third quarter of 2021 is Rp. 5,029,126.61, with an error obtained from the calculation, namely MAD Rp. 1,348,106 and MAPE 57.7%.References
Bank BTN. Laporan Keuangan Triwulan Tahun 2013-2019. Accessed on November 05, 2020. https://www.btn.co.id/Investor-Relation-Home.
Bank BTN. Tentang Kami. Accessed on November 10, 2020.https://www.btn.co.id/id/Tentang-Kami.
Khair, U., Fahmi, H., Al Hakim, S., & Rahim, R. (2017, December). Forecasting error calculation with mean absolute deviation and mean absolute percentage error. In Journal of Physics: Conference Series (Vol. 930, No. 1, p. 012002). IOP Publishing.
KHUSNA, A. (2016). Pengaruh biaya operasional dan pembiayaan bermasalah terhadap profitabilitas pada Lembaga Keuangan syariah Asri tulungagung.
Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2015). Introduction to time series analysis and forecasting. John Wiley & Sons.
Purwanto, S. (2016). Statistika Untuk Ekonomi Dan Keuangan Modern Edisi 3 Buku 2. Jakarta. Salemba Empat.
Rachman, R. (2018). Penerapan Metode Moving Average Dan Exponential Smoothing Pada Peramalan Produksi Industri Garmen. Jurnal Informatika, 5(2), 211-220.
Rahmawita, M., & Fazri, I. (2018). Aplikasi Peramalan Penjualan Obat Menggunakan Metode Least Square Di Rumah Sakit Bhayangkara. Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi, 4(2), 201-208.
Ratningsih, R. (2017). Forecasting Penjualan Rumah Dengan Menggunakan Metode Trend Moment Pada Pt. Rumakita Prima Karsa.
Sadli, M., & Safwandi, S. (2017). Implementasi Sistem Cerdas Least Square dalam Meramalkan Pemenuhan Kebutuhan Stok Listrik di Kota Lhokseumawe. Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering), 4(2), 21-29.
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