Skripsi

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

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Penilaian

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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%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307004136	T93737	T937372023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T937372023

Publisher

Indralaya : Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2023

Collation

xv, 78 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

511.307

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Fuzzy
Jurusan Matematika

Specific Detail Info

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Statement of Responsibility

PITRIA

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