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E-business applications recommendation for SMES using advanced user-based collaboration filtering

Iswari, Ni Made Satvika and Budiardjo, Eko Kuswardono and Hasibuan, Zainal Arifin (2021) E-business applications recommendation for SMES using advanced user-based collaboration filtering. ICIC Express Letters, 15 (5). ISSN 2185-2766

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Official URL: https://scholar.ui.ac.id/en/publications/e-busines...

Abstract

The adoption of e-business for Small and Medium Enterprises (SMEs) shou-ld be easy to use, minimum customization, and not subject to infrastructure procurement. However, each SME has very diverse characteristics, so that one-size-fits-all system is not the right solution. In this study, a recommendation system for e-business applica-tions is proposed for SMEs based on their characteristics. Recommendations are made using advanced user-based collaborative filtering, which is the improvement of the User-based Collaborative Filtering (UCF) algorithm. At UCF, SMEs give the same or similar preferences to an e-business application, and it can be said that SMEs have similar re-quirements. Thus, those SMEs will likely give the same preference to other e-business applications. In the proposed advanced UCF, besides using SMEs preference data it also uses SME characteristic data to produce recommendations. This approach is used by considering that SMEs that have just used the recommendation system do not yet have a historical preference for e-business applications. For this reason, recommendations can be made by considering the characteristics of the organization. Thus, it is expected that SMEs can use e-business applications that are appropriate to the characteristics of the organization. This approach is expected to increase the adoption of e-business in SMEs.

Item Type: Article
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming (Algorithm, Programming Language, Applications, Software, Data Security)
300 Social Sciences > 330 Economics > 338 Production (Agriculture, Business Enterprise, Extraction of Minerals, General Production)
Divisions: Fakultas Teknik Informatika > Program Studi Informatika
Depositing User: mr admin umn
Date Deposited: 14 Oct 2021 13:04
Last Modified: 14 Oct 2021 13:04
URI: http://kc.umn.ac.id/id/eprint/18778

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