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All Journal Journal of Applied Science, Engineering, Technology, and Education
Iwan Adhicandra
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Other

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Prioritizing Online Learning Platforms Based on Student Needs: A TOPSIS Analysis Enos Lolang; Muthia Mutmainnah; Hafni Hafsah; Iwan Adhicandra; Ernie C Avila; Rahim, Robbi
Journal of Applied Science, Engineering, Technology, and Education Vol. 5 No. 1 (2023)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci1587

Abstract

The proliferation of online learning platforms has made it increasingly difficult for students to choose a platform that best meets their needs. This study aims to prioritize online learning platforms based on student needs using the Multiple Criteria Decision Analysis (MCDA) Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The criteria used in the analysis were ease of use, variety of courses, cost, and reputation of instructors. The results of the analysis indicate that edX is the most suitable online learning platform for students based on the criteria and weights used in the study. Coursera, Udemy, and LinkedIn Learning were also evaluated in the analysis and may be suitable for students with specific priorities or preferences. The MCDA TOPSIS method provides a transparent and objective approach to evaluating the alternatives and offers insights into the strengths and weaknesses of each platform. The results of this study can help students make more informed decisions and choose a platform that best meets their individual needs. However, the choice of criteria and weights may vary depending on the preferences and priorities of different students, and the results should be interpreted accordingly
Evaluating Location Alternatives for a New Manufacturing Plant using Weighted Sum Model Method Dikky Suryadi; Warkianto Widjaja; Muchamad Sobri Sungkar; Kraugusteeliana, Kraugusteeliana; Iwan Adhicandra; Sujito, S.
Journal of Applied Science, Engineering, Technology, and Education Vol. 5 No. 1 (2023)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci1661

Abstract

This study uses the Weighted Sum Model to analyze location possibilities for a new manufacturing plant based on six variables, including transportation cost, labor cost, taxes, utilities cost, closeness to suppliers, and proximity to customers. The data was collected and normalized using the min-max method, and weight values were assigned to each criterion based on their relative importance. The Weighted Sum Model formula was then used to determine the weighted sum for each alternative location, and City B was identified as the best location for the new manufacturing plant, followed by City A and lastly City C. The Weighted Sum Model provides an objective and systematic approach to evaluating location alternatives, allowing decision-makers to weigh the importance of each criterion and consider multiple factors in making informed decisions. The strategy is versatile and can be modified to numerous decision-making scenarios, making it a helpful tool for firms wishing to make location decisions based on data-driven approaches. In conclusion, the Weighted Sum Model is a useful tool for analyzing location possibilities for a new manufacturing plant and can help firms make informed and data-driven decisions regarding the optimum location for their operations
Co-Authors Dikky Suryadi Enos Lolang Ernie C Avila Hafsah, Hafni Kraugusteeliana Kraugusteeliana Muchamad Sobri Sungkar Mutmainnah, Muthia Robbi Rahim S. Sujito Widjaja, Warkianto