eprintid: 12274
rev_number: 30
eprint_status: archive
userid: 71
dir: disk0/00/01/22/74
datestamp: 2014-04-30 02:20:46
lastmod: 2016-03-11 04:08:25
status_changed: 2014-04-30 02:20:46
type: thesis
metadata_visibility: show
creators_name: MUHAMMAD SIDDIQ AFIANTO,  NIM. 07650055
title: RANCANG BANGUN SISTEM REKOMENDASI GAME
MENGGUNAKAN COLLABORATIVE FILTERING
(STUDI KASUS : TOKO ONLINE KIOSK GAMES)


ispublished: pub
subjects: TB
divisions: jur_tinf
full_text_status: restricted
keywords: Keywords: Collaborative filtering, recommendation systems, online gaming store.



note: Pembimbing :  M. Mustakim, S.T., M.T.

abstract: Kiosk Games is an online store which is sales of PC games. A large number
of games that they sold, making some customers difficulty in determining the choice
of what game they want to buy and match their tastes. That is why it need for a
recommendation system that is able to give recommendations for game titles to
simplify them in choosing games that will be purchased.
This study uses the Collaborative Filtering, where the system will look for
similarity model of purchase (similiar user) only between customers who are logged
in with another customer. Furthermore, the system will look for customer rating
based on the degree of similarity between the purchase order that already exist. The
more similar games that have been purchased, the higher the rating will be. Then, this
rating will be used to provide recommendations on the value of those games that is
fitting with the customer that is being logged in into the system.
The results of a game recommendation system using a collaborative filtering
method is able to make games title recommendations by providing customer value
rating from largest to smallest based on common purchases among customers who are
logged in with another customer.


date: 2013-07-29
date_type: published
institution: UIN SUNAN KALIJAGA
department: FAKULTAS SAINS DAN TEKNOLOGI
thesis_type: skripsi
thesis_name: other
citation:   MUHAMMAD SIDDIQ AFIANTO, NIM. 07650055  (2013) RANCANG BANGUN SISTEM REKOMENDASI GAME MENGGUNAKAN COLLABORATIVE FILTERING (STUDI KASUS : TOKO ONLINE KIOSK GAMES).  Skripsi thesis, UIN SUNAN KALIJAGA.   
document_url: https://digilib.uin-suka.ac.id/id/eprint/12274/1/BAB%20I%2C%20VII%2C%20DAFTAR%20PUSTAKA.pdf
document_url: https://digilib.uin-suka.ac.id/id/eprint/12274/2/BAB%20II%2C%20III%2C%20IV%2C%20V%2C%20VI.pdf