<![CDATA[MSMEs are one of the micro businesses that are carried out to improve the prosperity of home industry, the majority of MSMEs still carry out traditional business processes, but in the current era, product sales can be done anywhere, such as running an online business through e-commerce. The ease of this online business helps MSMEs to develop sales globally, so e-commerce is needed which will be aquipped with a recommendation information system for sales development in MSMEs. This research aims to implement a recommendation information system in e-commerce using the collaborative filtering method. This method was chosen because of its advantages in producing more accurate recommendations using MSME data, consumer data, and rating data. From the process carried out, the results show that this system provides product recommendations with the highest predictive value, namely M1 is product RSM with a predictive value of 0,5. M3 is product RPC with a predictive value of 0,03. M4 is product RKK with a predictive value of 1. M6 is product RKC with a predictive value of 0,88 which will be displayed to consumers and provide an effective and efficient marketing platform.]]>
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