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All Journal Journal of Social Research International Journal of Management Science and Application
Oktavianus Yusan, Budi
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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Portfolio Optimization: Application and Comparison of Markowitz Model and Single Index Model on LQ45 Stocks in Indonesia Stock Exchange Oktavianus Yusan, Budi; Riyadi, Selamet
International Journal of Management Science and Application Vol. 3 No. 1 (2024): ijmsa
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijmsa.v3i1.210

Abstract

This paper examines the optimization of an Indonesian stock portfolio using two models: the Markowitz Model (Mean-Variance Model) and the Single Index Model. The data comprises historical returns of LQ 45 stocks from January 2016 to December 2021. The focus is on selecting stocks for the portfolio and determining their weights based on the two models. The study compares the performance of both optimized portfolios with the LQ45 Index benchmark, IHSG market, and each other using Sharpe and Treynor measurements. The paper tests whether the stock composition of the optimized portfolio from both models successfully and consistently generates a better performance in the future (1 January 2022 – 31 December 2022) and (1 January 2023 – 31 December 2023) compared to both LQ45 and IHSG. The results reveal a notable contrast in portfolio performance between 2022 and 2023. In 2022, both the Markowitz and Single Index portfolios exhibited remarkable returns, surpassing LQ 45 and IHSG. However, in 2023, both portfolios experienced substantial underperformance, with negative returns and unfavorable risk-adjusted metrics. These findings underscore the dynamic nature of financial markets and the need for continuous portfolio monitoring and adaptation. Investors are encouraged to reevaluate their portfolio strategies in response to changing market conditions. The study contributes valuable insights into the temporal variability of optimized portfolios and their sensitivity to evolving market dynamics.
Factors Influencing Purchase Intention for Electric Motorcycles in Indonesia: An Integrated Theory of Planned Behavior–Technology Acceptance Model Approach Oktavianus Yusan, Budi; Susan, Marcellia; Nurbasari , Anny
Journal of Social Research Vol. 5 No. 4 (2026): Journal of Social Research
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/josr.v5i4.3107

Abstract

This study examines Indonesian consumers' intention to purchase electric motorcycles by identifying the factors that influence it, using an integrated Theory of Planned Behavior (TPB)–Technology Acceptance Model (TAM) framework. A cross-sectional survey (n = 143) was conducted, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The measurement model showed acceptable reliability and validity. The findings revealed that attitude was the strongest direct predictor of purchase intention (? = .353), followed by subjective norms (? = .315) and perceived behavioral control (? = .214), explaining 54.7% of the variance in intention (R² = .547). Technology beliefs influenced intention indirectly through TPB pathways: perceived usefulness strongly predicted attitude (? = .709), while perceived ease of use positively predicted perceived behavioral control (? = .490), supporting both mediation effects. The model also demonstrated predictive relevance in cross-validation. Theoretically, the study extends TPB–TAM evidence to Indonesia's two-wheeler context by showing that TAM beliefs operate through attitude and control. Practically, the findings suggest three levers to raise purchase intention: quantified value communication (e.g., total cost of ownership, reliability, daily convenience), friction reduction (test rides, charging and service enablement), and social-proof activation (peer/community endorsement).
Co-Authors Marcellia Susan Nurbasari , Anny Selamet Riyadi