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All Journal Jurnal EMT KITA International Journal of Social Science and Business International Journal Software Engineering and Computer Science (IJSECS) International Journal of Management Science and Information Technology (IJMSIT) Jurnal Manajemen dan Teknologi
Sulistyawati, Upik Sri
Institut Teknologi Dan Bisnis Muhammadiyah Bali
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences Other

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Stock Portfolio Analysis with Machine Learning Algorithmic Approach for Smart Investment Decisions Munawir; Upik Sri Sulistyawati
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.2606

Abstract

This study investigates the application of machine learning algorithms in stock portfolio analysis within the Indonesia Stock Exchange (IDX) and their impact on investment decision-making. By engaging 500 respondents from diverse market segments, including retail investors, institutional investors, and stock traders, the research provides a comprehensive overview of adopting and utilising machine learning technologies in the Indonesian stock market. The findings reveal that over 80% of respondents have integrated machine learning algorithms into their investment strategies. The algorithms are applied in various capacities: 45% of respondents use them for portfolio risk analysis, 30% for stock price prediction, and 25% for identifying new investment opportunities. Preferences for specific algorithms vary, with regression, Support Vector Machines (SVM), and Random Forest emerging as the most used tools. The integration of machine learning was strongly associated with improved investment decisions, as more than 60% of respondents reported enhanced portfolio performance and greater accuracy in their decision-making. These results highlight the transformative potential of machine learning algorithms in enabling more innovative and more adaptive investment strategies.
Analysis of Financial Decision-Making with a Behavioral Economics Approach: Perspectives on Capital Market Investors Ahmad Rizani; Rizky Zakariyya Rasyad; Lina Budiarti; Upik Sri Sulistyawati
International Journal of Management Science and Information Technology Vol. 3 No. 2 (2023): July - December 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v3i2.1471

Abstract

This study aims to analyze the financial decision-making of investors in capital markets using the approach of behavioral economics. Behavioral economics studies how psychological and emotional factors influence financial decision-making. This study involves analyzing various aspects of investor behavior including loss aversion, information framing, overconfidence, herd behavior, and demographic factors. The results show that investors tend to fear losses more than profits, which affects prudent decision-making. The way information is presented also influences investment decisions, where the formation of a positive or negative frame can affect perceptions of risk and opportunities for profit. Overconfidence also plays a role in investment decision-making, with overconfident investors tend to underestimate risk. Herd behavior is also seen in this study, where investors tend to follow market trends without in-depth analysis, which can increase market volatility. Demographic factors such as age, gender, education, and investment experience also play a role in investment strategy and risk preference. This research provides important insights to investors and market participants about the psychological factors that influence financial decision-making. With a better understanding of investor behavior, it is hoped that investors will be able to make more informed and informed decisions, as well as reduce the impact of psychological biases in the future. financial decision-making in capital markets.
Holistic Strategy in Building Competitive Advantage in the Digital Era and Market Disruption Wahyu Sri Handono; Yulianto Umar Rofi’i; Upik Sri Sulistyawati
International Journal of Management Science and Information Technology Vol. 4 No. 2 (2024): July - December 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v4i2.3320

Abstract

This study aims to analyze the effect of a holistic strategy on a company's success in maintaining competitive advantage in the digital transformation era. The holistic strategy includes technology adoption, human resource development, business model innovation, customer orientation, and risk management. This study uses a quantitative approach with a survey method through a closed questionnaire distributed to managers and executives in 100 companies spread across various industrial sectors, including technology, manufacturing, services, and retail. Respondents were selected based on their company's involvement in digital transformation initiatives for at least two years. The collected data were analyzed using descriptive statistics and linear regression to evaluate the relationship between the independent (holistic strategy) and the dependent (competitive advantage) variables. The study results show that technology adoption, especially AI, big data, and IoT, significantly affects company performance and strengthens its competitive advantage. In addition, employee digital skills development, innovation in business models, and a focus on improving customer satisfaction have also been shown to play an important role in driving business growth. Effective risk management helps companies deal with market disruption and economic uncertainty to maintain their operations' sustainability. These findings emphasize the importance of integrating various elements in a holistic strategy to ensure a company's success in the era of dynamic digital competition. This research provides theoretical and practical contributions for business managers in formulating adaptive and sustainable strategies amidst technological disruption. The implications of these findings suggest that companies need to accelerate their digital transformation by strengthening the synergy between technology, human resources, innovation, and risk management to maintain their competitiveness in the global market.
Co-Authors Afrizal Ahmad Rizani Alfina Andrijanni Bahruni Bahruni Bahruni Caroline Dedi Sufriadi Edi Susilo Lina Budiarti Muhammad Jamil Munawir Munawir Munawir Munawir Nazaruddin, Erizal Purwoko, Agus Rizky Zakariyya Rasyad Sufriadi, Dedi Syamsul Rizal Wahyu Sri Handono Yulianto Umar Rofi’i