PREDIKSI HARGA PENUTUPAN SAHAM DENGAN METODE FUZZY TIME SERIES RUEY CHYN TSAUR

RIFQI, MUHAMMAD and Samsuryadi, Samsuryadi and Marieska, Mastura Diana (2021) PREDIKSI HARGA PENUTUPAN SAHAM DENGAN METODE FUZZY TIME SERIES RUEY CHYN TSAUR. Undergraduate thesis, Sriwijaya University.

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Abstract

Stock are proof of ownership of the value of a company. In general, stock are traded on the capital market through the stock exchange. The rise and fall of stock prices is a challenge for investors in stock transactions. Using the Fuzzy Time Series Ruey chyn Tsaur method, research will be carried out in predicting stock prices to demonstrate the process of predicting stock prices and knowing the accuracy of this method in predicting stock prices. In this research, test data used is the LQ45 index closing stock price for the period of January 2011-December 2020 where predictions will be done with two test configurations, i.e the methods for determining the length of the intervals. The level of accuracy measured by the Mean Absolute Percentage Error (MAPE) method. From this research, it was found that the test using Average-Based Length method produced the best accuracy rate of 98,17%, while the use of Distribution-Based Length method produced accuracy rate of 98,13%. So it can be concluded that the Average-Based Length method provide the best result on predicting time series data. Also, based on the two result of configuration, it can be concluded that Fuzzy Time Series Ruey Chyn Tsaur method is a good method to use for the error rate produced by the test are below two percent.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Stock, Ruey chyn Tsaur, Distribution-Based Length, Average-Based Length
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76 Computer software T Technology > T Technology (General) > T57-57.97 Applied mathematics. Quantitative methods
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Rifqi
Date Deposited:	14 Jul 2021 03:31
Last Modified:	14 Jul 2021 03:31
URI:	http://repository.unsri.ac.id/id/eprint/49835

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