In this thesis, we present a hypergraph partitioning algorithm that achieves both, fast partitioning with high locality. The idea is simple but effective: the algorithm grows k disjoint subgraphs based on the neighbourhood relation and the degree distribution in the hypergraph. We performed extensive experiments and showed that our algorithm leads to perfectly balanced partitions with improved locality compared to state-of-the-art, while matching the fast runtime of streaming hypergraph partitioners.