eprintid: 8899
rev_number: 7
eprint_status: archive
userid: 46
dir: disk0/00/00/88/99
datestamp: 2025-01-16 02:26:37
lastmod: 2025-01-16 02:26:37
status_changed: 2025-01-16 02:26:37
type: thesis
metadata_visibility: show
creators_name: Nadira Putri, Salsa
creators_name: Awaliyah Zuraiyah, Tjut
creators_name: Dinar Munggaran Ahmad, Dinar
creators_NPM: 065118203
contributors_type: http://www.loc.gov/loc.terms/relators/THS
contributors_type: http://www.loc.gov/loc.terms/relators/THS
contributors_type: http://www.loc.gov/loc.terms/relators/THS
contributors_name: Nadira Putri, Salsa
contributors_name: Awaliyah Zuraiyah, Tjut
contributors_name: Dinar Munggaran Ahmad, Dinar
contributors_NIDN: 0409017301
contributors_NIDN: 0401129201
corp_creators: Universitas Pakuan
corp_creators: Fakultas Matematika dan Ilmu Pnegetahuan Alam
corp_creators: Program Studi Ilmu Komputer
title: RECOMMENDER SYSTEMS USING
HYBRID DEMOGRAPHIC AND CONTENT-BASED FILTERING
METHODS FOR UMKM PRODUCTS
ispublished: pub
subjects: QK
divisions: sch_ecs
full_text_status: public
abstract: RECOMMENDER SYSTEMS USING
HYBRID DEMOGRAPHIC AND CONTENT-BASED FILTERING
METHODS FOR UMKM PRODUCTS
Salsa Nadira Putri1), Tjut Awaliyah Zuraiyah2), Dinar Munggaran Akhmad3)
1,2,3 Department of Computer Science, Faculty of Mathematics and Natural Science, Pakuan University,
Bogor, West Java, 16143, Indonesia
Abstract
Marketing digitization such as e-commerce is needed by micro, small and medium enterprises
(UMKM) in Bogor City and Regency so that the products are more easily accessible to consumers. One
of the digital marketing that is commonly used by consumers is an e-commerce website. The
Recommendation System is implemented into e-commerce websites to increase consumer convenience
in online shopping. The recommendation systems method applied is Demographic Filtering and
Content-based Filtering. Demographic Filtering uses IMDB Weighted Rating calculations which
generate recommendations globally and give recommendations based on each product's IMDB
Weighted score. Content-based Filtering uses Cosine Distance calculations which generate personal
recommendations and give recommendations based on the score cosine distance of each product in the
form of a presentation of the similarity of products that have been purchased with other products. This
research uses 107 UMKM fashion and craft product data that was obtained from Bogor City Regional
Craft Center which sells various kinds of UMKM products from Bogor City and Regency. Data
preprocessing is then carried out on the raw data, with the Data Cleaning, Data Transforming and Data
Splitting stages which divide the data in a ratio of 80:20. The accuracy of Demographic Filtering
Recommendation System reaches 82.7% and Content-based Filtering Recommendation System reaches
100%.
Keywords: UMKM; Recommender System; Demographic Filtering; Content-based Filtering
date: 2024-07-10
date_type: published
pages: 32
institution: Universitas Pakuan
department: Fakultas Matematika dan Pengetahuan Alam
thesis_type: Skripsi
thesis_name: Sarjana
citation:   Nadira Putri, Salsa and Awaliyah Zuraiyah, Tjut and Dinar Munggaran Ahmad, Dinar  (2024) RECOMMENDER SYSTEMS USING HYBRID DEMOGRAPHIC AND CONTENT-BASED FILTERING METHODS FOR UMKM PRODUCTS.  Skripsi thesis, Universitas Pakuan.   
document_url: http://eprints.unpak.ac.id/8899/1/Laporan%20-%20Salsa%20Nadira%20Putri%20-%20065118203.pdf