<![CDATA[ChatGPT and Perplexity are two applications that can be utilized to develop learning materials. However, no research has measured the completeness of material produced by artificial intelligence. Thus, this research aims to analyze ChatGPT and Perplexity as the material collection tool. The material completeness is measured using Jaccard Similarity which compares objects with intersection. Assuming that material completeness can be measured through the intersection of the same material, Jaccard Similarity is proposed with three material search trials using core competencies, basic competencies, and core materials. It was implemented in the Electrical Power Installation Engineering learning material. Then, Jaccard Similarity is analyzed with teacher validation. The result shows that ChatGPT and Perplexity achieved the highest assessment in core material searching, reaching similarity up to 72.40â„… and 47.67% respectively. Both validations reached 80% and 70% respectively. It was concluded that ChatGPT was superior to Perplexity and the best keywords based on the core material.]]>
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