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All Journal International Journal of Electrical and Computer Engineering Jurnal Manajemen Teori dan Terapan Management and Economics Journal (MEC-J) eCo-Buss Jurnal Teknik Industri Terintegrasi (JUTIN) Muhammadiyah Riau Accounting and Business Journal International Journal on Social Science, Economics and Art International Journal of Education, Social Studies, And Management (IJESSM) Journal of Indonesian Economy and Business Journal of Islamic Economics Lariba Journal of Artificial Intelligence and Digital Business Prosiding Seminar Nasional Manajemen dan Ekonomi Sharing: Journal Of Islamic Economics, Management And Business Money: Journal of Financial and Islamic Banking CARE: Jurnal Pengabdian Multi Disiplin Dedikasi: Jurnal Pengabdian Pendidikan dan Teknologi Masyarakat Journal of Digital Community Services Journal Of Community Sustainability General Multidisciplinary Research Journal Journal of Financial and Business Journal of Community Service and Empowerment Dedikasi: Jurnal Pengabdian Pendidikan dan Teknologi Masyarakat JES-TM Social and Community Service
Wahyu Febri Ramadhan Sudirman
Univeristas Pahlawan Tuanku Tambusai
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Journal : Jurnal Teknik Industri Terintegrasi (JUTIN)

 1 
Comparison Random Forest Regression and Linear Regression For Forecasting BBCA Stock Price Priyatno, Arif Mudi; Tanjung, Lailatul Syifa; Ramadhan, Wahyu Febri; Cholidhazia, Putri; Jati, Putri Zulia; Firmananda, Fahmi Iqbal
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 6 No. 3 (2023): July 2023
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v6i3.16933

Abstract

Stock trading is a popular financial instrument worldwide. In Indonesia, the stock market is known as the Indonesia Stock Exchange (BEI), and one actively traded stock is PT Bank Central Asia (BBCA). However, predicting stock price movements is challenging due to various influencing factors. Investors use fundamental and technical analyses for decision-making, but results often vary. Machine learning, particularly random forest regression and linear regression algorithms, can be used for stock price forecasting. In this paper, we compares these two machine learning methods to forecast BBCA stock prices, aiming to provide more accurate and effective solutions for investor's investment and trading decisions. The evaluation results of cross-validation mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) for linear regression were 0.12848, 0.35807, 0.29570, and 0.0036%, respectively, while for random forest regression were 27473.76, 158.04, 142.70, and 1.7153%. These findings indicate that linear regression outperforms in forecasting performance.
The Effect of Overconfidence Bias on Investment Decision: Sharia Stock Considerations Sudirman, Wahyu Febri Ramadhan; Nurnasrina, Nurnasrina; Syaipudin, Muhammad; Priyatno, Arif Mudi
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 7 No. 2 (2024): April
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v7i2.26091

Abstract

Investment decisions are a complex process involving risk evaluation, market analysis, and investment return projections. In the decision-making process, investors sometimes show irrational behavior because they have cognitive limitations and previous investment experience so investors are exposed to overconfident behavior. This research used 178 samples consisting of investors who had investment experience of at least 1 year. The research carried out instrument testing and used the common method bias (CMB) testing procedure. The analytical method in the research uses simple linear regression. The results of testing the research hypothesis obtained positive and significant results of overconfidence bias towards irrational investment decisions The moderating role of sharia sharia considerations on the relationship between overconfidence bias and unsupported investment decisions. This research reveals that overconfidence can have a positive influence on irrational investment decision-making. Investors who tend to have excess confidence in their knowledge and skills in analyzing the market tend to make investment decisions that are more impulsive, less rational and sometimes ignore risks significantly. Future research is recommended to further investigate the mechanisms behind the relationship between overconfidence and irrational investment decision-making, as well as involving a wider sample to obtain stronger generalizations.
Co-Authors Adams, Ravi Afrinis, Nur Alfiatun Zahara Amalia, Fazilla Amalia, Nala AMELIA, NUR Andhini, Bunga Andi Irfan, Andi Andini, Bunga Anggun Pratiwi Anggun Pratiwi Arif Mudi Priyatno Aryadi Aryadi Aryadi Aryadi Berliana Putri Bunga Andhini Cahyani, Binda Rahma Cholidhazia, Putri Despira, Despira Diany Mairiza Eti, Eti Faridatus Suhadak Firmananda, Fahmi Iqbal Firmanda, Fahmi Iqbal Hastuty, Milda Hayu Ardina Hermawanti, Sela Hermawati, Sela Hidayat Hidayat Hidayat Hidayat Irmawanti, Irmawanti Izzah, Aqidatul Jati, Putri Zulia Lasepa, Wanda Lismawati, Lismawati M. Zaim Maini, Nur Mardiyah, Suci Maretha Ika Prajawati Maziyah, Putri Maslahatul Mifta Hasda Mohd. Winario Muhammad Arif Muhammad Ikhsan Alif Muhammad Syaipudin Muhammad Zakir Muhammad Zakir Nala Amelia Noranisa, Noranisa Nur Afrinis Nuraziza, Sania Nurnasrina Nurnasrina Raja Joko Musridho Ramadhan, Al Insani Mutiara Ravi Adams Riani Riani, Riani Rifqil Khairi Rinancy, Hariyet Rinda Fithriyana Riski, Muhamamd Rizki, Syafnur Muhammad Rizky, Syafnur Muhammad Rizqi, Eka Roshifita Rizqon Jamil Farhas Rusnedy, Hidayati Saadah , Nila Sagena, Basir Sari, Efti Novita Saru Reza Sasmitandia, Kienna Candra Suci Mardiya Suci Mardiyah Supardi Supardi Syafiq, M Rizan Syaipudin, Muhamamd Tanjung, Lailatul Syifa USWATUN KHASANAH Yusup Yusup Zahara, Alfiatun Zahrah, Alfiatun Zubaidah Assyifa