Optimasi Deep Learning untuk Prediksi Saham di Masa Pandemi Covid-19

Hastomo, Widi; Karno, Adhitio Satyo Bayangkari; Kalbuana, Nawang; Nisfiani, Ervina; Etp, Lussiana

doi:10.26418/jp.v7i2.47411

Cited by 16 publications

(18 citation statements)

References 8 publications

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“…Python is open source so there are still many people who contribute to developing (Pane &;Yogi Aditya Saputra, 2020). Python was chosen as a programming language in this study, because this language has many libraries that make it easy to create programs that involve a lot of vector and matrix manipulation, as well as visual displays of various attractive and easy-to-read graphics (scikit learn matplotlib library, and also heatmaps (seaborn library) to show correlations in the form of color and numerical maps (Hastomo, Karno, Kalbuana, Nisfiani, & ETP, 2021).…”

Section: Pythonmentioning

confidence: 99%

Analysis of Time Series Water Level Data Prediction Using Deep Learning Method at the Water Gate of DKI Jakarta Water Resources Office

Supriyade,

Firmansyah,

Akbar

et al. 2023

JISS

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Indonesia has 2 seasons, namely the dry season and the rainy season. During the rainy season, many points in the DKI Jakarta area experience flooding or inundation. The reason why Jakarta often experiences flooding is caused by several factors, including local rain floods, shipment floods and tidal floods. The DKI Jakarta Water Resources Agency currently does not have a system that can predict future water levels by referring to past and present water level data. Through this background, the author tries to conduct research in one of the floodgates in the northern area of DKI Jakarta in predicting water levels using deep learning methods , namely Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM). The purpose of this research is to analyze the best deep learning models and predict water level time series data. From the results of the analysis carried out, the best deep learning model is Long Short Term Memory (LSTM) using several tests such as n-input, split data with a composition of 90.33% train data and 9.67% test data , as well as testing of different parameters including epoch, batch size, learning rate, dropout , so the results obtained are the lowest error values with RMSE (17.65), MAPE (0.29), MAE (3.37) and the time needed in the process (runtime) is 39 minutes

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Section: Pythonmentioning

confidence: 99%

Analysis of Time Series Water Level Data Prediction Using Deep Learning Method at the Water Gate of DKI Jakarta Water Resources Office

Supriyade,

Firmansyah,

Akbar

et al. 2023

JISS

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“…GRU merupakan sel dengan kandungan 2 gate dan 3 fungsi aktivasi. Gate dan fungsi yang minim ini akan mempercepat proses pengolahan data yang umumnya sangat besar, sehingga kemampuan GRU dirancang untuk menjadi lebih baik dari LSTM terutama untuk dataset yang jumlahnya kecil [14]. Pada MAE, setiap nilai diambil nilai absolutnya, sehingga nilai negatif hilang.…”

Section: B Gated Recurrent Unit (Gru)unclassified

Prediksi Harga Emas Menggunakan Metode LSTM Dan Gru

Tholib,

Agusmawati,

Khoiriyah

2023

JITET

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Prediksi harga emas sangat penting karena menjadi acuan bagi para investor untuk menentukan strategi yang tepat dalam berinvestasi. Tren metode prediksi dalam beberapa tahun terakhir adalah deep learning, yang merupakan subbidang machine learning dan populer dalam menangani masalah prediksi time-series. Dalam penelitian ini, kami membandingkan performa dua model deep learning, yaitu Long Short-Tern Memory (LSTM) dan Gated Recurrent Unit (GRU) dalam memprediksi harga Emas. Hasil dalam penelitian ini menunjukkan bahwa model LSTM memiliki performa lebih baik dibanding model GRU dalam memprediksi harga Emas, dengan hasil perhitungan nilai eror LSTM lebih rendah yaitu nilai MAE sebesar 0.0389, RMSE sebesar 0.0475, dan MAPE sebesar 5.2047%. Dari hasil penelitian ini, kami menemukan bahwa LSTM adalah model yang lebih efektif dan akurat untuk memprediksi harga Emas dibanding LSTM.

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“…As a result, investors who invest in shares in a company also sell the shares they own and that is what makes the stock price plunge freely on all stock exchanges in the world [8]. Stock transactions conducted by novice and professional investors even during the COVID-19 pandemic suffered many losses [9] [10]. Investor panic by withdrawing funds from the stock exchange caused IHSG to plunge free.. Factors other than stock prices, the condition of a company can also be seen from the number of stock transactions traded to certain companies.…”

Section: Introductionmentioning

confidence: 99%

Impact of the Covid-19 Pandemic on the Price and Volume of Stock Transactions in Hospitals in Indonesia

Tarigan

Christelia

Wangsih

et al. 2021

Juremi

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The aim of the study was to look at the comparison between stock prices and hospital transaction volume before and after the announcement of the first COVID-19 pandemic in Indonesia. The population in this study is a hospital listed on the Indonesia Stock Exchange (IDX). Samples in this study used purposive sampling techniques, hospital data obtained by as many as 6 companies listed on the Indonesia Stock Exchange (IDX), this study used paired sample t-test techniques and data process using SPSS version 26. The result of this study is the stock price of hospitals before and after the announcement of COVID-19 cases in Indonesia is very significant with sig value. (2tailed) the result is 0,000 (p < 0.05) meaning that significant changes (mean) and for the Volume of Hospital Transactions before and after the announcement of COVID-19 cases in Indonesia is very significant with sig value. (2 tailed) the result is 0.033 (p < 0.05) meaning a significant change (meaning).

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Optimasi Deep Learning untuk Prediksi Saham di Masa Pandemi Covid-19

Cited by 16 publications

References 8 publications

Analysis of Time Series Water Level Data Prediction Using Deep Learning Method at the Water Gate of DKI Jakarta Water Resources Office

Analysis of Time Series Water Level Data Prediction Using Deep Learning Method at the Water Gate of DKI Jakarta Water Resources Office

Prediksi Harga Emas Menggunakan Metode LSTM Dan Gru

Impact of the Covid-19 Pandemic on the Price and Volume of Stock Transactions in Hospitals in Indonesia

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