<![CDATA[Regional-language digital dictionaries play a strategic role in supporting Tourism 4.0 by enabling communication between local communities and tourists. However, inefficient search mechanisms can substantially degrade their usability, while research on the computational complexity of search algorithms for low-resource languages such as those of Papua remains scarce. This study presents a comparative analysis of three search algorithms binary search, tree-based search, and n-gram search benchmarked against an unoptimized linear search baseline in a Papuan regional-language digital dictionary containing 5,597 lemmas. Each algorithm was evaluated on both time and space complexity through controlled experiments executed on five heterogeneous computing devices. The experimental results show that the tree-based search algorithm achieves the best overall performance, with the lowest average search time of 1.28 seconds and the smallest average memory usage of 3.73 kB. These findings provide an empirical basis for selecting efficient search algorithms in regional-language digital dictionaries and contribute to the Tourism 4.0 digital infrastructure by enabling fast, scalable access to local-language information.]]>
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