WEB-BASED DECISION SUPPORT SYSTEM FOR GUEST STAR DETERMINATION IN E-MARKETPLACE USING WEIGHTED PRODUCT METHOD
Submitted : 2020-11-08, Published : 2020-12-01.
Abstract
At an event, the event organizer usually requires guest stars as performers. Event organizers often find it difficult to find a guest star that suits their needs for their event. The purpose of this research is to build an e-marketplace application as a web-based decision support system that can be used to find alternative decisions to choose guest stars according to the criteria using product weighting methods. The weighted product method is one of the methods that can be applied to web-based decision support system applications for determining guest stars in e-marketplaces. There are three criteria used to determine guest stars in this e-marketplace, these criteria are the type of show, price and location. As for the alternatives that were tested, there were nine alternatives consisting of guest stars in Yogyakarta. Functionality testing is carried out using the black box method and the result is that all functions and validation buttons on the e-marketplace can function properly. The result of calculation using the weighted product method is the guest star with the highest yield is Frengki Sermadi with a value of 0.135234, while the guest star with the lowest result is Sanggar Titik Dua with a value of 0.083222.
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