SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SEKOLAH MENENGAH ATAS (SMA) SWASTA TERBAIK DI KOTA PALEMBANG MENGGUNAKAN METODE WEIGHTED PRODUCT (WP)

ULFA, NURUL and Ruskan, Endang Lestari (2021) SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SEKOLAH MENENGAH ATAS (SMA) SWASTA TERBAIK DI KOTA PALEMBANG MENGGUNAKAN METODE WEIGHTED PRODUCT (WP). Undergraduate thesis, SRIWIJAYA UNIVERSITY.

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Abstract

The rapid development of education, especially in Palembang city makes competition between schools even greater. The existence of important criteria that schools have creates intense competition that occurs between schools, especially for private SHS. However, the large number of existing schools makes it difficult for parents and students to choose the best private senior high school because of the lack of information that can help in comparing which school are suitable. During this time, the way to select a school is to get information by asking everyone, do surveys from searching for information on the internet or go directly to the location of the school that will take a lot of time and costs. So from the problem, we can conclude that we needed a system to provide recommendations of the best private SHS with the desired criteria quickly and appropriately using the weighted product method by doing the multiplication process to connect attribute values and performed an increase in attribute values first with the weight of the attribute in question. This method is known to be more efficient because the time it takes is faster. The selection process of the best private senior high school (SHS) uses important criteria that the school has like an accreditation, facilities, extracurricular, long standing, spp fees, entrance fees, accessibility, location, and distance of school.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Sekolah Menengah Atas, SMA, Swasta, Weighted Product, Sistem Pendukung Keputusan
Subjects:	Q Science > Q Science (General) > Q1-390 Science (General) > Q223.M517 Science -- Information services. Information storage and retrieval systems --Science.
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Nurul Ulfa
Date Deposited:	27 Jul 2021 03:14
Last Modified:	27 Jul 2021 03:14
URI:	http://repository.unsri.ac.id/id/eprint/50462

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