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Image of PENERAPAN MACHINE LEARNING DALAM INVESTASI PEMERINTAH: PERBANDINGAN UNIVARIATE LONG SHORT-TERM MEMORY, MULTIVARIATE LONG SHORT-TERM MEMORY DAN RANDOM FOREST

Text

PENERAPAN MACHINE LEARNING DALAM INVESTASI PEMERINTAH: PERBANDINGAN UNIVARIATE LONG SHORT-TERM MEMORY, MULTIVARIATE LONG SHORT-TERM MEMORY DAN RANDOM FOREST

WICAKSANA, LAZUARDI ZULFIKAR - Personal Name; ROKHIM, ROFIKOH - Personal Name;

Penelitian ini meneliti bagaimana teknik pembelajaran mesin, khususnya model Random Forest dan Long Short-Term Memory (LSTM), secara univariat dan multivariat menggunakan variabel indikator analisis teknikal, dapat memprediksi harga saham, terutama penurunan harga saham untuk mengelola risiko dalam investasi saham pemerintah. Penelitian ini menggunakan seluruh saham selama periode 2000-2022 dari pasar modal Indonesia. Model LSTM univariat dengan lag 7 hari (n_lag 7), diikuti oleh model Random Forest, menunjukkan kinerja model prediksi terbaik secara keseluruhan.


Availability
300073257325RLC MM (Rak Tesis)Available
Detail Information
Series Title
-
Statement of Responsibility
Lazuardi Zulfikar Wicaksana
Call Number
7325
Publisher
Salemba, Jakarta : Magister Manajemen FEB UI., 2024
Collation
xiii, 102 p. : ill. ; 30 cm.
Language
Indonesia
ISBN/ISSN
-
Classification
650
Content Type
-
Edition
-
Subject(s)
Manajemen Keuangan
Tesis
Machine Learning
Government Investment
Long Short-Term Memory (LSTM)
Stock Prediction
Random Forest
Drawdown
Specific Detail Info
-
Other version/related

No other version available

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RLC MM FEB-UI
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RLC MM-FEBUI (Library) occupies the right side of the ground floor of the MM FEB UI Building with a reading room capacity of more than 60 people.
 
The MM-FEB UI library service system is closed (closed access); where the user does not have direct access to the collection shelf. Or in other words, users are not allowed to take their own books from the collection shelf

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