TY - JOUR
T1 - E-business applications recommendation for SMES using advanced user-based collaboration filtering
AU - Iswari, Ni Made Satvika
AU - Budiardjo, Eko Kuswardono
AU - Hasibuan, Zainal Arifin
N1 - Publisher Copyright:
© 2021 ICIC International. All rights reserved.
PY - 2021/5
Y1 - 2021/5
N2 - 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.
AB - 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.
KW - Advanced UCF
KW - Collaborative filtering
KW - E-business
KW - Recommendation system
KW - SMEs
UR - http://www.scopus.com/inward/record.url?scp=85104232487&partnerID=8YFLogxK
U2 - 10.24507/icicel.15.05.517
DO - 10.24507/icicel.15.05.517
M3 - Article
AN - SCOPUS:85104232487
SN - 1881-803X
VL - 15
SP - 517
EP - 526
JO - ICIC Express Letters
JF - ICIC Express Letters
IS - 5
ER -