Data mining in general is the search for hidden patterns that may exist in large databases. Spatial data mining in particular is the discovery of interesting relationships and characteristics that may exist implicity in spatial database[1]. One of algorithm in data mining is Naive Bayes that can use to predict location's prices enhancement by classifying previous data. Land prices has increase up to 10 times after 19 years. In this final project, author build a system that can predict which location that the price has increase and which is constant. By using NJOP and data from google maps, land prices can be predictable wether increase or not after use previos data as a training data. After the research obtained that the system can predict which location is incrasing and not increasing. The accuracy of this system reach 81%, while its precision reach 81%, recall 74,3%, and f1 - score 72,4%.