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All Journal JISI UMJ (Jurnal Integrasi Sistem Industri UMJ) Prosiding Semnastek Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis Owner : Riset dan Jurnal Akuntansi Jurnal Statistika dan Matematika (Statmat) KANGMAS: Karya Ilmiah Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Formosa (JPMF) Formosa Journal of Science and Technology (FJST)
Panudju, Andreas Tri
Universitas Bina Bangsa Serang
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Journal : Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis

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Prediksi Harga Saham Indonesia pada Masa Covid-19 Menggunakan Regresi Pohon Keputusan Rina Nopianti; Andreas Tri Panudju; Angrian Permana
Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis Vol 6, No 1 (2022): Jurnal Ecodemica: Jurnal Ekonomi, Manajemen dan Bisnis
Publisher : LPPM Universitas BSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (354.204 KB) | DOI: 10.31294/eco.v6i1.11365

Abstract

Stock price prediction is an interesting area of data mining. Many variables affect stock prices. Stock prices fluctuate, especially in the Covid-19 era which has an impact on the economy. This study aims to predict the stock price of Indonesian telecommunications, especially in the covid19 era. The object of this research is the financial statements of companies listed on the Indonesia Stock Exchange, where data related to stock prices of telecommunications companies are used as samples in the data processing of this study. In this study, the regression techniques that will be used are Multiple Linear Regression, Support Vector Regression, Decision Tree Regression, and K-Nearest Regression. The results showed that the fundamental data and stock prices have a relationship. High correlation coefficient resulted from Decision Tree Regression and K-Nearest Regression. Decision Tree Regression produces good results on the Train Test Split and KFold Cross Validation data, 2.99% and 2.98% repeatedly. It can conclude that despite the fact that the pandemic scenario has had a significant impact on the stock market, the study's findings suggest that fundamental data and stock prices have a relationship. Decision Tree Regression and K-Nearest Regression both produced high correlation coefficients.  Keywords: Stock Price, Prediction, Decision Tree, Regression, COVID-19
Co-Authors Angrian Permana, Angrian ASFAR, ANDI HASRYNINGSIH Euis Fajriati Fitri Fauziah Leni Triana Listiawati Listiawati Mochamad Fahru Komarudin Mutmainah Mattjik, Mutmainah Nopianti, Rina Panulisan, Bambang Setyo Prastika Tjeng Suwandi Rani Puspa Tia Fitria Saumi Umi Marfuah Wiwik Sudarwati