Perbandingan Hybrid Algoritma Genetika dengan Multilayer Perception dan Geometric Brownian Motion untuk Memprediksi Harga Saham

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Authors

  • Muftiyatul Azizah Sekolah Tinggi Ilmu Ekonomi Indonesia (STIESIA) Surabaya

DOI:

https://doi.org/10.32665/james.v5i2.494

Keywords:

Hybrid Genetic Algorithm and Multilayer Perceptron, Hybrid Genetic Algorithm and Geometric Brownian Motion, Stock, Saham, Hybrid Algoritma Genetika dan Multilayer Perceptron, Hybrid Algoritma Genetika dan Geometric Brownian Motion

Abstract

Saham didefinisikan sebagai tanda kepemilikan investor atas investasi mereka atau sejumlah dana yang diinvestasikan dalam suatu perusahaan. Tujuan perusahaan menerbitkan saham yakni untuk memperoleh tambahan modal dari setiap lembar yang terjual. Semakin banyak saham yang dimiliki oleh para investor maka menunjukkan semakin tinggi tingkat kinerja perusahaan. Hasil prediksi dari pergerakan harga saham sangat penting untuk mengembangkan strategi perdagangan pasar. Prediksi harga saham dapat mengantisipasi kerugian investasi dan memberikan keuntungan optimal bagi para investor. Pada penelitian ini, akan dilakukan prediksi harga saham perusahaan Microsoft menggunakan metode hybrid algoritma genetika dan multilayer perceptron, serta dengan metode hybrid algoritma genetika dan geometric Brownian motion. Nilai MAPE yang dihasilkan dari hybrid algoritma genetika dan geometric Brownian motion adalah sebesar 0.0057139, sedangkan nilai MAPE yang dihasilkan oleh hybrid algoritma genetika dan multilayer perceptron adalah sebesar 0.05164. Nilai MAPE hasil prediksi menggunakan hybrid algoritma genetika dan geometric Brownian motion lebih baik dibandingkan dengan nilai MAPE hasil prediksi menggunakan hybrid algoritma genetika dan multilayer perceptron.

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Published

2022-08-23

How to Cite

[1]
M. Azizah, “Perbandingan Hybrid Algoritma Genetika dengan Multilayer Perception dan Geometric Brownian Motion untuk Memprediksi Harga Saham”, JaMES, vol. 5, no. 2, pp. 101–109, Aug. 2022.

Issue

Vol. 5 No. 2 (2022): Journal of Mathematics Education and Science

Section

Articles

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Abstract View: 216, PDF Download: 183