Bijikopiku is an application to find selected coffee beans according to the taste preferences of users using a predetermined algorithm. User preferences are based on experience with coffee, taste, and flavor that suits the user. Prioritizing an intuitive user experience that can do shopping before registering an account.

As the full-stack developer of Bijikopiku, I designed and developed an intelligent mobile application that helps users discover coffee beans tailored to their personal taste preferences. The project was built with the goal of merging user experience design and algorithmic recommendation to create a smooth and personalized shopping journey.

My role involved end-to-end development—from defining the user flow and preference logic to implementing the backend system and mobile interface. The recommendation algorithm was designed based on user input such as coffee experience, flavor notes, and taste intensity, producing curated bean suggestions that match each user’s profile.

Technically, I built the mobile application using Kotlin to ensure a native, responsive experience, supported by a backend powered by Node.js and PostgreSQL for managing user data, product catalogs, and preference mapping. The accompanying Next.js web dashboard was developed for administrators to manage coffee bean listings, taste profiles, and analytics insights.

Through Bijikopiku, I aimed to combine technology, design, and sensory experience into a seamless digital platform—bringing personalization to the coffee discovery process and enhancing engagement for enthusiasts and casual drinkers alike.