International Science Community Association Research Journal of Agriculture and Forestry Sciences 2320 - 6063 7 4 2019 10 8 Coffee shop consumer behavior cluster 17 23 EN Hassen Nurhussen 1 Agricultural Economics Department Haramaya University, Ethiopia VPS Arora 2 Agricultural Economics Department Haramaya University, Ethiopia Paunikar S. 1 Northern Regional Centre, Zoological Survey of India, 218, Kaulagarh Road, Deharadun-248 195, Uttarakhand, India Kulkarni N. 2 Forest Entomology Division, Tropical Forest Research Institute, P. O. RFRC, Mandla Road, Jabalpur- 482021, Madhya Pradesh, India and Institute of Forest Productivity (IFP) Gumla, National Highway-23, Lalgutwa, Ranchi – 835303, Jharkhand, India Assya Rahmadhani 1 Faculty of Agriculture Padjajaran University, Bandung, Indonesia Yosini Deliana 2 Faculty of Agriculture Padjajaran University, Bandung, Indonesia > Research Paper 2019 3 26 2019 10 8 The consumption of coffee in Indonesia has been seeing seen an increase for the last 7 years. This phenomenon is supported by the rapid growth of coffee shops in several regions such as the city of Bogor. The large number of businesses in the same sphere has caused tight competition among producers in the coffee shop industry. One of the efforts that need to be done is understanding the consumer behavior of coffee shop customers and appeal based on product and coffee shop attributes. MM café is one of the many cafes in Bogor that is facing stiff competition in the coffee shop industry. The owner is required to assign clusters or grouping to identify customers according to specific sets of characteristics. The aim of this research is to identify characteristics and cluster consumer behavior based on product and coffee shop attributes. The sample selection in this research is based on the systematic random sampling technique on 115 respondents. The analysis is done by descriptive analysis, k-means cluster analysis, and ANOVA hypothesis testing. The results of the research show that there are two consumer clusters visiting MM café based on their evaluation of product and coffee shop attributes: cluster 1 consisting of 58 people are categorized as regular coffee drinkers with a high assessment towards indicators of product and coffee shop attributes, and cluster 2 with a total of 57 people consisting of coffee enthusiasts with an assessment towards indicators of product and coffee shop attributes lower than that of cluster 1. The result of the ANOVA hypothesis testing shows that 12 indicators of product and coffee shop attributes of (p=0,000) <5% significant rate (0,05) have a significant impact in dividing cluster 1 and cluster 2. Copyright@ International Science Community Association