Wibowo, Adinda Ramadhani and Permana, Angga Aditya and Khaeruzzaman, Yaman (2023) DESIGN AND BUILD A MICRO INFLUENCER RECOMMENDATION SYSTEM AS A SOCIAL MEDIA PROMOTION TOOL USING A SIMPLE ADDITIVE WEIGHTING ALGORITHM. Journal of Theoretical and Applied Information Technology. ISSN 1817-3195
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DESIGN AND BUILD A MICRO INFLUENCER RECOMMENDATION SYSTEM AS A SOCIAL MEDIA PROMOTION TOOL USING A SIMPLE ADDITIVE WEIGHTING ALGORITHM.pdf Download (2MB) | Preview |
Abstract
Social media usage globally has change marketing strategy. It has become an important marketing strategy to build business. One of the social media is promotion through influencers on Instagram. Customers probably made decision as a result of watching influencers on social media. Business owners who promote their business using social media often feel confused about choosing the right micro influencer to promote their business. Micro influencer is the level of influencer who has followers ranging from 1,000 to 100,000. However, choosing the right micro influencers is not easy task because more people gaining number of followers in social media. Finding the right micro influencer becomes crucial, therefore we proposed a website to choose the right micro influencer according to their preferences. Decision support system to facilitate micro influencer decision making process was named a micro-influencer recommendation system using the Simple Additive Weighting algorithm. This algorithm Simple Additive Weighting was chosen to determine the weight value of each criterion that will select the best alternative from a number of alternatives and the assessment will be more precise because it is based on predetermined criteria values and preference weights. Testing has been carried out to ensure that the algorithm used runs as it should. User testing has also been carried out and has a final satisfaction value of 87.41 % using the End User Computing Satisfaction method.
| Item Type: | Article |
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| Keywords: | End User Computing Satisfaction, Micro-Influencer, Simple Additive Weighting, Recommendation System Website |
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 10 May 2023 07:46 |
| Last Modified: | 10 May 2023 07:46 |
| URI: | https://kc.umn.ac.id/id/eprint/25296 |
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