In this work, K-partitioning of signed or weighted bipartite graph problem has been introduced, which appears as a real life problem where the partitions of bipartite graph represent two different entities and the edges between the nodes of the partitions represent the relationships among them. A typical example is the set of people and their opinions, whose strength is represented as signed numerical values. Using the weights on the edges, these bipartite graphs can be partitioned into two or more clusters. In political domain, a cluster represents strong relationship among a group of people and a group of issues. In the paper, we formally define the problem and compare different heuristics, and show through both real and simulated data the effectiveness of our approaches.