Astronomy is an interesting field and it has broad scope. Interest for researcher to explore this field is growing as the new emerging technology made everything impossible become possible. Although astronomy study universe beyond Earth, innovation of powerful telescopes such as Atacama Large Millimeter Array (ALMA) allows image on the outer space to be observed clearly. This has caused a research to be carried out and publication happen. However, researcher often faced problem to know which branches in astronomy have been covered by other researchers in their publication papers.

The retrieval of image produced related to topic of interest is also hard to find. Thus, a web-based astronomy database will be developed in order to store data in form of text and astronomical image. The publication paper will be searched and retrieved by analyzing the abstract. Meanwhile, a descriptor will be embedded in the image to retrieve desired image related to user's topic of interest. String matching algorithm will be implemented in this project in retrieving process and data analytic will be performed by using machine learning tools. Clustering technique by using K-Means algorithm is used to group all related publications and images together.

As a result, researcher will know and get visualization which branches have been most explored. Then, the same research topic will not overlap in the future. The expected outcome is to ease process of searching and retrieving publication paper and astronomical image. Plus, researcher will know new suitable research topic to do in the future. In short, this database will provide a new platform for researcher to access, retrieve and have overview summary of publication paper and image in one single place.