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dc.contributor.advisorHardi, Sri Melvani
dc.contributor.advisorManik, Fuzy Yustika
dc.contributor.authorAzhari, Rizky Ayu
dc.date.accessioned2024-08-27T05:14:03Z
dc.date.available2024-08-27T05:14:03Z
dc.date.issued2024
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/96153
dc.description.abstractTeachers are professional educators whose main task is to educate, teach, guide, train and evaluate students. High school teachers themselves are the second parents for high school students. A teacher at the secondary education level is responsible for teaching subjects that suit his knowledge. Meanwhile, the best teachers are teachers who have the ability to carry out and successfully complete each of their tasks. The aim of giving rewards as the best teacher is to motivate teachers to continue to improve their competence and performance professionally in carrying out their duties at school and focus on carrying out their duties as teachers. As time goes by, the selection of the best teachers, which has been done manually and directly selected by the school principal, also does not pay attention to assessment criteria such as attendance, discipline, responsibility, teaching ability and attitude so that the decisions taken are less than satisfactory and do not provide alternative solutions. . Based on the explanation above, a decision support system is needed for selecting the best teachers by determining the weight of the criteria in each assessment. WASPAS is a multi-criteria analysis method used in decision support systems (DSS) to solve the problem of selecting the best alternative. WASPAS is a combined method consisting of the WP method and the SAW method. This WASPAS method is expected to provide better results in helping determine the best teacher selection decision support system. This method can be applied in selecting the best teachers by determining the relevant criteria and their weights. Presentation of the conformity of the final ranking results of the system with the ranking determined by the school principal is 86,95%.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectTeacheren_US
dc.subjectDecision Support Systemen_US
dc.subjectWASPASen_US
dc.subjectSDGsen_US
dc.titlePenerapan Metode Weight Aggregated Sum Product Assesment (WASPAS) dalam Sistem Pendukung Keputusan Pemilihan Guru Terbaik (Studi Kasus : SMA Negeri 1 Barumun)en_US
dc.title.alternativeApplication of Weight Aggregated Sum Product Assessment(WASPAS) Method in Decision Support System for Selecting The Best Teacher (Case Study: SMA Negeri 1 Barumun)en_US
dc.typeThesisen_US
dc.identifier.nimNIM171401045
dc.identifier.nidnNIDN0101058801
dc.identifier.nidnNIDN0115108703
dc.identifier.kodeprodiKODEPRODI55201#Ilmu Komputer
dc.description.pages61 Pagesen_US
dc.description.typeSkripsi Sarjanaen_US


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