Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2022
Optimasi Prediksi Harga Saham MenggunakanAlgoritma Fruit Fly Optimization pada Support Vector Machine.
Dublin Core
Title
Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2022
Optimasi Prediksi Harga Saham MenggunakanAlgoritma Fruit Fly Optimization pada Support Vector Machine.
Optimasi Prediksi Harga Saham MenggunakanAlgoritma Fruit Fly Optimization pada Support Vector Machine.
Subject
Supervised Learning, Regression, Evolutionary Algorithm, Support Vector Regression
Description
Pasar saham adalah kumpulan dari bursa efek dimana investor dan masyarakat membeli dan menjual saham mereka secara publik. Harga saham sangat fluktuatif karena dipengaruhi oleh hukum permintaan dan penawaran. Penelitian ini memiliki tujuan untuk mengetahui jumlah harga saham berdasarkan dataset indeks harga saham yang dikumpulkan melalui yahoo finance. Algoritma yang digunakan merupakan algoritma Support Vector Regression yang merupakan Algoritma Supervised Learning. Parameter pada Support Vector Machine yaitu Kernel, Gamma, Epsilon, dan Regularization dapat dioptimasi menggunakan Evolutionary Algorithm supaya mendapatkan nilai matriks evaluasi yang lebih optimal. Nilai evaluasi model yang akan digunakan pada penelitian ini adalah APE (Absolute Percentage Error) dan RMSE (Root Mean Square Error). Penelitian ini diharapkan mendapatkan nilai matriks evaluasi yang lebih baik dari penelitian sebelumnya.
The stock market is a collection of stock exchanges where investors and the public buy and sell their shares publicly. Stock prices are very volatile because they are influenced by the law of supply and demand. This study aims to determine the number of shares based on the stock price index dataset collected through yahoo finance. The algorithm used is a Support Vector Regression algorithm which is a Supervised Learning Algorithm. Parameters on the Support Vector Machine, Kernel, Gamma, Epsilon, and Regularization can be optimized using Evolutionary Algorithm in order to get a more optimal evaluation value. The value evaluation models that will be used in this study are APE (Absolute Percentage Error) and RMSE (Root Mean Square Error). This research, it is expected to get a better evaluation value than previous research.
The stock market is a collection of stock exchanges where investors and the public buy and sell their shares publicly. Stock prices are very volatile because they are influenced by the law of supply and demand. This study aims to determine the number of shares based on the stock price index dataset collected through yahoo finance. The algorithm used is a Support Vector Regression algorithm which is a Supervised Learning Algorithm. Parameters on the Support Vector Machine, Kernel, Gamma, Epsilon, and Regularization can be optimized using Evolutionary Algorithm in order to get a more optimal evaluation value. The value evaluation models that will be used in this study are APE (Absolute Percentage Error) and RMSE (Root Mean Square Error). This research, it is expected to get a better evaluation value than previous research.
Creator
Ramadhan Ridho Arrohman
Publisher
Universitas Semarang
Date
19 Oktober 2022
Contributor
Sri Wahyuni
Rights
ISSN: 2614-1205
Format
PDF
Language
Indonesian
Type
Text
Coverage
Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2022
Files
Citation
Ramadhan Ridho Arrohman, “Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2022
Optimasi Prediksi Harga Saham MenggunakanAlgoritma Fruit Fly Optimization pada Support Vector Machine.,” Repository Horizon University Indonesia, accessed November 21, 2024, https://repository.horizon.ac.id/items/show/3506.
Optimasi Prediksi Harga Saham MenggunakanAlgoritma Fruit Fly Optimization pada Support Vector Machine.,” Repository Horizon University Indonesia, accessed November 21, 2024, https://repository.horizon.ac.id/items/show/3506.