Perplexity.ai is very helpful in the world of translation. This study aims to analyze the translation errors produced by Perplexity.ai from morphological, syntactic, and semantic aspects. This research is a descriptive qualitative method. The data analysis technique of this research uses a content analysis technique. This study examines the translation errors of CNN Indonesia's news entitled "House of Senior Hamas Commander in West Bank Leveled by Israeli Military" into Arabic through Perplexity.ai application from morphological, syntactic, and semantic aspects. This study shows that the translation from Indonesian into Arabic using Perplexity.ai application is not fully accurate, because there are still many errors in various aspects of the language. Errors in the semantic aspect are the most common, syntactic errors are the least common, and morphological errors are the least common.