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              <text>An Intelligent Decision Support System to Aid Profit Planning in Manufacturing Companies</text>
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              <text>Break-Even Analysis; Management Accounting; Market Demand; Multi-product Break Even Point; Profit Planning</text>
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              <text>In order to assure accuracy in profit planning and decision-making, this study uses an intelligent decision support system to investigate an appropriate approach for calculating the "Break-Even" point in multi-product segments while taking into account the implications for contribution margin, demand, and capacity. The research's methodology and findings may be used to propose new projects, grow businesses, and make decisions in processes that focus on many products. Data are used to illustrate the advanced level of break-even analysis and application, and a description of the convenient and system-generated method of computation is given. A mathematical approach has been used based on actual data to show how to determine the break-even point without sacrificing the influencing aspects such as contribution margin, capacity, product mix, and demand for each. The researchers have created a good system application-oriented platform to make it simple to calculate the break-even point, which will be crucial for decision-making and profit planning even with more than 500 SKU (Stock Keeping Unit). This research evaluated the data and created formulas for actual data structure-based analysis. The study's conclusions have a significant influence on those companies that need to determine the true break-even threshold. The challenge area of concern might be the applicability of this activity for other sectors and other countries as this research was centred on the plastic bag industry in Malaysia. Future research can also analyse other important factors like start-up and semi-variable costs as they are not included in the current study. The identified break-even threshold can still be used effectively given the current market demand and the product's capacity.  2023, Ismail Saritas. All rights reserved.</text>
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              <text>Thasan S.; Rahman A.; Subramanian P.; Williams M.J.</text>
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              <text>International Journal of Intelligent Systems and Applications in Engineering, Vol-11, No. 4s, pp. 345-356.</text>
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              <text>Ismail Saritas</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="" target="_blank" rel="noreferrer noopener"&gt;&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161368879&amp;amp;partnerID=40&amp;amp;md5=c8d2479715084f14df3cb0363b46ab0e" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161368879&amp;amp;partnerID=40&amp;amp;md5=c8d2479715084f14df3cb0363b46ab0e&lt;/a&gt;</text>
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              <text>ISSN: 21476799</text>
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              <text>Thasan S., Faculty Of Business and Accounting, Linton University College, Malaysia; Rahman A., Faculty of Business and Communications, INTI International University, Malaysia; Subramanian P., School of Business Management, Christ University, Lavasa, Pune, India; Williams M.J., Sri Krishna Arts and Science College, India</text>
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