GENETIC ALGORITHM FOR FUZZY TIME SERIES OPTIMIZATION IN THE DEVELOPMENT OF DOMESTIC TOURISTS VISIT AMOUNT IN BALI

RIZKY, MEGA and Efendi, Rusdi and Miraswan, Kanda Januar (2019) GENETIC ALGORITHM FOR FUZZY TIME SERIES OPTIMIZATION IN THE DEVELOPMENT OF DOMESTIC TOURISTS VISIT AMOUNT IN BALI. Undergraduate thesis, Sriwijaya University.

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Abstract

The tourism industry has an important role in socializing the cultures of Indonesia. As time goes by, tourists amount will increase or decrease and causing a decline in the sector of local communities income. One of the algorithms that can make a prediction based on time series data is Fuzzy Time Series. Fuzzy Time Series is a method has forecasting or prediction concept consisting of data collection or object based on time range. While forecasting, Fuzzy Time Series method will optimized using Genetic Algorithm. Optimization was done by determining the interval value of Fuzzy Time Series method in order to get the error rate value result called Mean Absolute Percentage Error which better than just using conventional Fuzzy Time Series.Based on the results of the tests of the tourist visit amounts in Bali using conventional Fuzzy Time Series method obtained the Mean Absolute Percentage Error 20.7211% with training time for 746.517ms and testing time for 80.40652ms, on the other hand, after optimization using Genetic Algorithm with 200 parameter number of iteration, 150 population number, using probability combination crossover rate 0.65 and mutation rate 0.4 obtained the Mean Absolute Percentage Error 20.4257% with training time for 2043995.47111ms and testing time for 1.03686ms

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: tourist visits amount, fuzzy time series, genetic algorithm
Subjects: T Technology > T Technology (General) > T10.5-11.9 Communication of technical information
T Technology > T Technology (General) > T58.6-58.62 Management information systems
T Technology > T Technology (General) > T58.6-58.62 Management information systems > T58.62 Decision support systems Cf. HD30.213 Industrial management
Divisions: Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Mega Rizky
Date Deposited: 29 Jul 2019 07:27
Last Modified: 29 Jul 2019 07:27
URI: http://repository.unsri.ac.id/id/eprint/1107

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