WIBOWO, DENI RAMADHAN (2022) PREDIKSI HARGA SAHAM SEKTOR KONSUMER DI BURSA EFEK INDONESIA MENGGUNAKAN METODE DOUBLE EXPONENTIAL DAN ALGORITMA KELELAWAR (STUDI KASUS SAHAM ICBP, MYOR, UNVR, STTP, ULTJ). Skripsi thesis, UNIVERSITAS BHAYANGKARA SURABAYA.
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Abstract
Investors buy stocks because they expect the maximum rate of return on investments made in the absence of a meaningful risk for which investors need various considerations in decision making by collecting various relevant information needed, especially related to the dynamics of stock prices in order to be able to make decisions about the company's shares that are worth buying that can provide the most optimal provit. This research was conducted because the stock price in consumers is fluctuating every day, so the risk of investing in stocks is very high. This study was created to predict stock prices in the consumer sector in Indonesia using the Double Exponential Smoothing method and to optimize it using a bat algorithm. Double Exponential Smoothing is a method that repeats continuously using the latest data. This method is based on the calculation of the average smoothing of previous data exponentially and for Bat algorithms is a metaheuristic algorithm and belongs to the swarm intelligence. The Bat Algorithm is one of the many mathematical optimization methods used to solve optimization problems. The stocks that will be tested in this researcher are consumer sector stocks such as Indofood CBP Sukses Makmur (ICBP), Unilever (UNVR), Mayora (MYOR), Ultra Jaya (ULTJ) and Siantar TOP (STTP). In the Mayora Stock test, 2019 was a predictable year with the smallest error value with an average MSE value of 1056.23 and an MAE of 32.48. Indofood Stock testing was obtained, 2019 was a predictable year with the smallest error value with an average MSE value of 40372.7 and an AVERAGE MAE of 200.8 In the Unilever test, 2018 was a predictable year with the smallest error value with an average MSE value of 19490.5 and a MAE of 138.8. The results of ultrajaya stock testing obtained in 2017 was a predictable year with the smallest error value with an average MSE value of 3936.45 and AN MAE of 59.46.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Investors, Stocks, Double Exponential Smoothing, Forecasting, Optimization, Algorithms bat |
| Subjects: | 000 - COMPUTER SCIENCE, INFORMATIONS & GENERAL WORKS > 000 Computer science, information & general works > 005 Computer programming, programs & data > 005.3 Programs 000 - COMPUTER SCIENCE, INFORMATIONS & GENERAL WORKS > 000 Computer science, information & general works > 005 Computer programming, programs & data > 005.3 Programs |
| Depositing User: | Perpus Ubhara Surabaya |
| Date Deposited: | 13 Jan 2025 04:50 |
| Last Modified: | 13 Jan 2025 04:51 |
| URI: | http://eprints.ubhara.ac.id/id/eprint/2849 |
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