PENERAPAN FUZZY TIME SERIES DAN FUZZY C-MEANS CLUSTERING UNTUK PREDIKSI NILAI TUKAR RUPIAH TERHADAP US DOLLAR

EGAMO, BOYCASITO and Efendi, Rusdi and Yunita, Yunita (2018) PENERAPAN FUZZY TIME SERIES DAN FUZZY C-MEANS CLUSTERING UNTUK PREDIKSI NILAI TUKAR RUPIAH TERHADAP US DOLLAR. Undergraduate thesis, Sriwijaya University.

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Abstract

The prediction of the Rupiah exchange rate against US Dollar is the result of the analysis from data processing that obtained online using API from fixer.io website based on three types of data are data daily, weekly and monthly. This research aims to apply the Fuzzy Time Series as a method to predict the Rupiah exchange rate against US Dollar and automate in determining the number and length of effective intervals using the Fuzzy C-Means method. Results of testing the application of Fuzzy Time Series showed that the most common data types affect the accuracy with the results accuracy of daily data type of 0.13%, weekly data 0.40% and monthly data 1.32%. The application of the Fuzzy C-Means can be used to automate in determining the number and length of the interval and produce predict quite well.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Prediksi Nilai Tukar Rupiah, Fuzzy Time Series, Fuzzy C-Means Clustering
Subjects:	T Technology > T Technology (General) > T61-173 Technical education. Technical schools > T173.8 Technological innovations T Technology > T Technology (General) > T173.2-174.5 Technological change > T173.8 Technological innovations T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Mr Halim Sobri
Date Deposited:	13 Sep 2019 03:01
Last Modified:	13 Sep 2019 03:01
URI:	http://repository.unsri.ac.id/id/eprint/7306

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