Designing CRM-CAR (Customer Relationship Management -- Computer Aided Recognition) Based on Facial Recognition Technology to Increase Business Competitiveness by Utilizing Artificial Intelligence
DOI:
https://doi.org/10.18502/kss.v9i4.15062Abstract
The development of SMEs is the flagship of the Indonesian state. 90% of the total businesses in Indonesia are SMEs. In addition, SMEs support 60.34% of the entire GDP of the Indonesian state. Starting from basic needs such as food, beverages, clothing, and others, to supporting needs such as technology and information. The product and service sectors were not spared from the development of SMEs. One way to help improve the quality of business services is to utilize a customer database. By utilizing digital applications, a business service can be adapted to historical customer data so that it will improve the quality of service received by customers. This study aims to design, build, and test a CRM application based on facial recognition that utilizes artificial intelligence to improve the quality of business services. In addition, through this research, it is hoped that the current condition of the use of artificial intelligence to improve services will be known. This study uses a research and development approach. The research stage begins with a preliminary study and user needs, followed by the initial preparation of the application. When the application has been compiled, a validation test will be carried out by an expert who will validate whether the compiled application is feasible. It is hoped that the CRM application software based on facial recognition by utilizing artificial intelligence can be helpful and can be utilized by the business as a whole, or SMEs in particular to improve the quality of customer service, which will directly increase business competitiveness. In addition, through this research, it is hoped that the current condition of the use of artificial intelligence to improve services will be known.
Keywords: artificial intelligence, customer relationship management, facial recognition, marketing, SMEs, service quality
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