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KLASIFIKASI ARAH PERGERAKAN INDEKS HARGA SAHAM GABUNGAN DI BURSA EFEK INDONESIA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM)

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The Indonesian stock market as a strategic investment instrument with high volatility requires an accurate prediction system to minimize investor losses and increase profits. The technical and fundamental analysis methods that have been used have limitations, such as reliance on historical data and lack of consideration for external factors. With technological advancements, machine learning algorithms such as Support Vector Machine (SVM) have become an option to improve prediction accuracy. Therefore, a classification model for the movement direction of the Composite Stock Price Index (IHSG) on the Indonesia Stock Exchange will be developed using the SVM algorithm, which is chosen to overcome the limitations of the aforementioned technical and fundamental analysis methods in order to produce more optimal predictions. This research tests the best parameter combination from three parameters: C, γ, and number of iterations to produce the best model. From the results of the experiment, the best parameter combination was obtained with values of C = 0.1, γ = 1, and number of iterations = 200, resulting in a model with an accuracy of 91.79%. The results of this study show that SVM can be an effective tool in predicting the movement direction of IHSG

Availability
Inventory Code Barcode Call Number Location Status
2507004320T179611T1796112025Central Library (Reference)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1796112025
Publisher
Indralaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya.,
Collation
xvi, 125 hlm.; ilus.; tab.; 29 cm.
Language
Indonesia
ISBN/ISSN
-
Classification
004.07
Content Type
Text
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Teknik Informatika
Specific Detail Info
-
Statement of Responsibility
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