The rapid growth of the Internet influenced many of our daily activities. One of the very rapid growth area is ecommerce. Generally e-commerce provide facility for customers to write reviews related with its service. The existence of these reviews can be used as a source of information. For examples, companies can use it to make design decisions of their products or services, while potential customers can use it to decide either to buy or to use a product. Unfortunately, the importance of the review is misused by certain parties who tried to create fake reviews, both aimed at raising the popularity or to discredit the product. This research aims to detect fake reviews for a product by using the text and rating property from a review. In short, the proposed system (ICF++) will measure the honesty value of a review, the trustiness value of the reviewers and the reliability value of a product. The honesty value of a review will be measured by utilizing the text mining and opinion mining techniques. The result from the experiment shows that the proposed system has a better accuracy compared with the result from iterative computation framework (ICF) method.

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Rosokku is a technology-based startup that collects and processes waste (paper-based). Rosokku takes paper-based waste based on customer requests. And for this pick-up, there has been an agreement with the customer about the day of the pick-up beforehand. The convenience of this process (people throw away their paper waste and at the same time they get money) has started to rise in demand from the community, especially among college students. Up to this day, Rosokku has used media such as WhatsApp and Instagram to engage with its clients so far. As the number of clients has risen, in deciding the pick-up schedule, rosokku has begun to become overwhelmed. There is a lot of data that is not well documented. The team began to have difficulty tracking their financial transactions as well. Therefore, this research aims to solve these problems by reviewing existing business processes and developing new business processes to improve current business processes (conduct gap analysis). The results of this research are new business processes that will be implemented later on to the application (functional requirement).