Main Article Content

Abstract

Abstract. Companies should be willing to adopt new technologies and business models to be able to stay competitive in the changing world, both regionally and globally. However, the US forest sector industry, including wood furniture sector seems to be lagging when it comes to implementing digital technologies. This study proposes a design of Point of Interest (POI) recommendation system to enhance the marketing practices to promote wood furniture stores. We produced a personal recommendation design utilising K-Means+ clustering, a combination between K-Means algorithm for spatial data clustering and Davies-Bouldin Index (DBI) methods to determine the optimal K value. This design can assist mobile users who are potential customers to find wood furniture store locations based on other users’ preferences. 

Keywords:  Digitalisation; location-based social networks; user-based collaborative filtering; K-Means+ clustering; DBI method

Keywords

Digitalization location-based social networks user-based collaborative filtering K-Means clustering DBI method

Article Details

Author Biographies

Pipiet Larasatie, Wood Science and Engineering Department, College of Forestry, Oregon State University, USA

Interdisciplinary scholar and social scientist studying competitive marketing and business management strategies of forest products innovation.

Sulis Setiowati, Electrical Engineering Department, Jakarta State Polytechnic, Indonesia

Lecturer with skills in Web Programming, Microsoft Office, Strategic Planning and Data Analyst.
How to Cite
Larasatie, P., & Setiowati, S. (2019). From Fingerprint to Footprint: Using Point of Interest (POI) Recommendation System in Marketing Applications. The Asian Journal of Technology Management (AJTM), 12(2), 118–131. https://doi.org/10.12695/ajtm.2019.12.2.4

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