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All Journal International Journal of Quantitative Research and Modeling International Journal of Mathematics, Statistics, and Computing
Benedicta, Hellena
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Mathematics Physics

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Analysis of Investment Decision Assessment Using the Net Present Value (NVP) Method at PT Bank Mandiri (Persero) Tbk Muqtashida, Amalia Aura; Benedicta, Hellena; Suhaimi, Nurnisaa Binti Abdullah
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 3 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i3.121

Abstract

This paper explores the fundamental elements of a robust business management strategy, essential for sustained success in the dynamic business landscape. It delves into crucial components such as investment decision-making, comprehensive planning, business development, and judicious risk-taking. These strategic decisions not only influence immediate financial performance but also contribute to long-term benefits such as market growth and heightened competitiveness. Focusing on the banking sector, the paper acknowledges the potential for substantial returns juxtaposed with inherent risks. Emphasizing that these risks are manageable, particularly in the stock market, it advocates for a meticulous approach to investment decision analysis. The strategic choices made in this process play a pivotal role in maximizing returns while minimizing the impact of stock market risks. With a preference for the Net Present Value (NPV) method highlighted in the literature review, the paper underlines the significance of comprehensive investment decision analysis.
Comparative Analysis of the Altman Z-Score and Springate Models in Predicting Bankruptcy of Pharmaceutical Companies in Indonesia Rahma, Yenita Indahyana; Benedicta, Hellena; Novita, Gaby
International Journal of Quantitative Research and Modeling Vol. 6 No. 4 (2025): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i4.1120

Abstract

The pharmaceutical industry is an important sector that not only focuses on making profit but also has a social responsibility to support public health. During the COVID-19 pandemic, this industry became much more active, especially in importing raw materials and producing medicines and health supplements. However, this growth also came with a large increase in debt, which raised the risk of financial problems. To deal with this, several bankruptcy prediction models have been developed, such as the Altman Z-Score and Springate models. These models are often used as early warning systems in many industries. Even so, research on bankruptcy prediction in Indonesian pharmaceutical companies is still limited. Therefore, this study aims to compare the two models in predicting bankruptcy in Indonesian pharmaceutical firms. The results show that the Altman Z-Score model is more suitable for long-term prediction, while the Springate model works better for short-term prediction.
Co-Authors Muqtashida, Amalia Aura Novita, Gaby Rahma, Yenita Indahyana Suhaimi, Nurnisaa binti Abdullah