Akurasi Analisis Time Series Dengan Metode Rmse Pada Forecasting Harga Saham Bank Syariah Yang Ada Di BEI

Hikmah Nur Yashinta, Agus Aklis, Fitria Berliana Sari, Mu'arifatin Nuril Ula

Abstract


Objective: to determine the accuracy of time series analysis using the RMSE method used in forecasting the monthly stock price of BRIS on the IDX for 5 months. Findings: The results of the RMSE prediction accuracy were obtained with a total of 215,812. Results: From the calculation of RMSE data from January to May, the results obtained are: (1) January of 7,018, (2) February of 144,589, (3) March of 35,218, (4) April of 26,179, (5) May of 2,808 with a total of 215,812. then the total of the total share prices from January to May is entered into the RMSE formula by dividing the total by n (amount of data) so as to get a result of 207.7558. Implications: based on the results of the discussion of this study, the implication is that the accuracy of time series analysis combined using the RMSE method is very suitable for forecasting Islamic banking stock prices. If this forecast continues to be developed, investors will not have to worry about calculating the stock price of a company. So that investors and the general public can easily see the movement of a company's stock price.


Keywords


Time Series Analysis, Financial Reports/data, Implementation, Forecasting/Forecasting, Stocks.

Full Text:

PDF

References


Andika, L. I. (2019). Usulan Perencanaan Safety Stock & Forecasting Demand Dengan Metode Time Series Produksi Keran Air Di Pt Kayu Perkasa Raya. Journal Industrial Engineering, 8(3), 19. https://ejournal3.undip.ac.id/index.php/ieoj/article/view/24295

Anggito, Albi. Setiawan, Johan. 2018. Metoologi Penelitian Kualitatif. Jawa Barat: CV Jejak.

Cokrodiharjo, V. R., Chalid, D. A., Bisnis, E., & Indonesia, U. (n.d.). Jpmb 61. 3(1), 6174.

Deny Nusyirwan, A. (2019). Jurnal Ilmiah Pendidikan Teknik Kejuruan ( JIPTEK ). Jurnal Ilmiah Pendidikan Teknik Kejuruan, 101(2), https://jurnal.uns.ac.id/jptk.

Fauzi, Ahmad. 2019. Forecasting Saham Syariah Dengan Menggunakan LSTM.

Handini, Sri dan Astawinetu, Erwin Dyah. 2020. Teori Portofolio Dan Pasar Modal Indonesia. Jawa Timur : Scopindo Media Pustaka.

Hery. 2015. Praktis menyusun laporan keuangan: cepat dan mahir menyajikan informasi keuangan. Jakarta: Grasindo.

Indriastuti, T. (2013). Analisis Time Series Untuk Meramalkan Jumlah Penjualan Pada Yamaha Mataram Sakti Kebumen Dengan Metode Tren. Journal of Chemical Information and Modeling, 53(9), 16891699.

Junaidi, Muksan dan Achmadi, Fuad. 2019. Analisis Prediksi Kinerja Perusahaan Menggunakan Rasio Profitabilitas Time Series Dan Algoritma Neuro-Fuzzy. Jurnal Ilmiah Pendidikan Teknik Kejuruan (JIPTEK). Vol 12 No 1.

Kurniasari Arni Astuti, dkk. 2021. Aplikasi Peramalan Harga Saham Perusahaan LQ45 Dengan Menggunakan Metode Arima. Journal Sistem Informasi.

Prasetya, B. D., Pamungkas, F. S., & Kharisudin, I. (2020). Pemodelan dan Peramalan Data Saham dengan Analisis Time Series menggunakan Python. PRISMA, Prosiding Seminar Nasional Matematika, 3, 714718. https://journal.unnes.ac.id/sju/index.php/prisma/ ISSN

Puspitaningtyas, Zarah. 2015. Prediksi Risiko Investasi Saham. Yogyakarta: Griya Pandiva.

Saputra, Andep. dkk. 2018. Fuzzy Time Series Sebagai Metode Peramalan Indeks Harga Gabungan Pasar Modal.

Sudarsono, Heri. 2012. Bank dan Lembaga Keuangan lainnya. Yogyakarta: Ekonisia.

Widajanto, G. R. T., Ediwarman, & Desmintari. (2021). Analisis Harga Saham Perbankan yang Terdaftar Di Bursa Efek Indonesia. Konferensi Riset Nasional Ekonomi Manajemen Dan Akuntansi, 2(1), 13071322. https://conference.upnvj.ac.id/index.php/korelasi/article/view/111




DOI: https://doi.org/10.30596/almuhtarifin.v1i1.8980

Refbacks

  • There are currently no refbacks.