Application of E-Commerce in SMIs to Support Denpasar Smart Cities with Local Culture Insights in Bali Province

Small and Medium Industries (SMIs) in the Proviince of Bali, especially in the city of Denpasar, are still the priority areas of the region as a potential to be developed in the future. SMIs in Denpasar City must be able compete with  similar SMIs products with other regions in the Province of Bali, at the national and international level. To support all that, SMIs Denpasar City is expected to be able to adopt more modern technological innovations, especially in the marketing system that as developed so far through E-Commerce.    

               SMIs as an economics foundation is used as a source of regional government revenue to realize equitable and equitable economic growth. As one of the smart cities, competent and cultured in Indonesia, the city of Denpasar is currently seriously improving towards smart cities to respond to global challenges so far. Supporting the realization of Denpasar as smart city and realizing its vision of being a culture-based creative city  in a balance towards harmony, the SMIs play an important role because  it is related to efforts to increase community weffare, job creation, and increase in people^,s income.

               The objectives of this study are:1) to analize the probability of E-Commerce application on SMIs in Denpasar based on capital, 2) to analyze the probability of E-Commerce application on SMIs in Denpasar based on age, 3) to analyze the probability  of E-Commerce implementation at SMIs in Denpasar based on production, 4) to analize the probability of implementation E-Commerce on SMIs in Denpasar based on income. The population is all SMIs in the city of Denpasar (Bali Provincial Industry and Trade Office, 2018). As many as 4.074 units. With the Slovin formula, using a 7 percent error rate a sample of 194 SMIs was obtained. Each SMIs unit is represented by 1 respondent of SMIs actors who are both business owners in Denpasar City. The sampling methode used is Stratified Random Sampling based on geographic region, namely sub-districts. To determine the sample unit to be interviewed using accidental sampling.