The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF

Today, consumers are faced with an abundance of information on the internet; accordingly, it is hard for them to reach the vital information they need. One of the reasonable solutions in modern society is implementing information filtering. Some researchers implemented a recommender system as filter...

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Autores principales:	Muhammad Johari, Arif Laksito
Formato:	article
Lenguaje:	ID
Publicado:	Ikatan Ahli Indormatika Indonesia 2021
Materias:	recommender system indonesian online marketplace hybrid filtering Systems engineering TA168 Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/89a4fde4e174489c810f467f53591456
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spelling	oai:doaj.org-article:89a4fde4e174489c810f467f535914562021-11-16T13:16:11ZThe Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF2580-076010.29207/resti.v5i5.3486https://doaj.org/article/89a4fde4e174489c810f467f535914562021-10-01T00:00:00Zhttp://jurnal.iaii.or.id/index.php/RESTI/article/view/3486https://doaj.org/toc/2580-0760Today, consumers are faced with an abundance of information on the internet; accordingly, it is hard for them to reach the vital information they need. One of the reasonable solutions in modern society is implementing information filtering. Some researchers implemented a recommender system as filtering to increase customers’ experience in social media and e-commerce. This research focuses on the combination of two methods in the recommender system, that is, demographic and content-based filtering, commonly it is called hybrid filtering. In this research, item products are collected using the data crawling method from the big three e-commerce in Indonesia (Shopee, Tokopedia, and Bukalapak). This experiment has been implemented in the web application using the Flask framework to generate products’ recommended items. This research employs the IMDb weight rating formula to get the best score lists and TF-IDF with Cosine similarity to create the similarity between products to produce related items.Muhammad JohariArif LaksitoIkatan Ahli Indormatika Indonesiaarticlerecommender systemindonesian online marketplacehybrid filteringSystems engineeringTA168Information technologyT58.5-58.64IDJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), Vol 5, Iss 5, Pp 977-983 (2021)
institution	DOAJ
collection	DOAJ
language	ID
topic	recommender system indonesian online marketplace hybrid filtering Systems engineering TA168 Information technology T58.5-58.64
spellingShingle	recommender system indonesian online marketplace hybrid filtering Systems engineering TA168 Information technology T58.5-58.64 Muhammad Johari Arif Laksito The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF
description	Today, consumers are faced with an abundance of information on the internet; accordingly, it is hard for them to reach the vital information they need. One of the reasonable solutions in modern society is implementing information filtering. Some researchers implemented a recommender system as filtering to increase customers’ experience in social media and e-commerce. This research focuses on the combination of two methods in the recommender system, that is, demographic and content-based filtering, commonly it is called hybrid filtering. In this research, item products are collected using the data crawling method from the big three e-commerce in Indonesia (Shopee, Tokopedia, and Bukalapak). This experiment has been implemented in the web application using the Flask framework to generate products’ recommended items. This research employs the IMDb weight rating formula to get the best score lists and TF-IDF with Cosine similarity to create the similarity between products to produce related items.
format	article
author	Muhammad Johari Arif Laksito
author_facet	Muhammad Johari Arif Laksito
author_sort	Muhammad Johari
title	The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF
title_short	The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF
title_full	The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF
title_fullStr	The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF
title_full_unstemmed	The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF
title_sort	hybrid recommender system of the indonesian online market products using imdb weight rating and tf-idf
publisher	Ikatan Ahli Indormatika Indonesia
publishDate	2021
url	https://doaj.org/article/89a4fde4e174489c810f467f53591456
work_keys_str_mv	AT muhammadjohari thehybridrecommendersystemoftheindonesianonlinemarketproductsusingimdbweightratingandtfidf AT ariflaksito thehybridrecommendersystemoftheindonesianonlinemarketproductsusingimdbweightratingandtfidf AT muhammadjohari hybridrecommendersystemoftheindonesianonlinemarketproductsusingimdbweightratingandtfidf AT ariflaksito hybridrecommendersystemoftheindonesianonlinemarketproductsusingimdbweightratingandtfidf
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The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF

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