KOMPARASI METODE FUZZY NAIVE BAYES DAN DEEP NEURAL NETWORK UNTUK KLASIFIKASI INDEKS HARGA SAHAM GABUNGAN (IHSG) BURSA EFEK INDONESIA TAHUN 2012-2022

ANTOFA, FITRIANA and Resti, Yulia and Kresnawati, Endang Sri (2023) KOMPARASI METODE FUZZY NAIVE BAYES DAN DEEP NEURAL NETWORK UNTUK KLASIFIKASI INDEKS HARGA SAHAM GABUNGAN (IHSG) BURSA EFEK INDONESIA TAHUN 2012-2022. Undergraduate thesis, Sriwijaya University.

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Abstract

This research aims to compare the results of the 2012-2022 composite stock price index classification using fuzzy naïve bayes method and deep neural network. The data analyzed is daily data on the Indonesian composite stock price index taken from 2 January 2012 to 28 October 2022 totaling 2628 days excluding weekends and public holidays sourced from the yahoo finance.com website. Composite stock price index data is reflected in the candlestick which consists of predictor variables, which is the opening price (open), the highest share price (high), the lowest share price (low), the number of shares sold (volume) and the response variable which is the closing price (close), divided into descending and ascending classes. The results of the research using the fuzzy naïve bayes method obtained an average accuracy of 57.32%, while the deep neural network method was 86.05%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Indeks Harga Saham Gabungan, Himpunan Fuzzy, Naïve Bayes, Neural Network.
Subjects:	Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Fitriana Antofa
Date Deposited:	11 Apr 2023 01:23
Last Modified:	11 Apr 2023 01:23
URI:	http://repository.unsri.ac.id/id/eprint/93737

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