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Part of speech (PoS) is one of the features that can be used to improve the quality of statisticalbased machine translation. Typically, language PoS determined based on the grammar of the language or adopted from other languages PoS. This work aims to formulate a model to develop PoS as linguistic factors to improve the quality of machine translation automatically. The model is based on word similarity approach, where we performed word clustering on corpus. The result of word clustering will be defined as PoS set obtained for a given language. The PoS sets resulted by the word clustering were compared to the manually defined PoS set in a machine translation (MT) experiment, the MT experiment employed English as the source language and Indonesian as the target language. [ABSTRACT FROM AUTHOR]