Non-formal affixed word stemming in Indonesian language

Stemming algorithm Nazief & Andriani has been development in terms of the speed and the accuracy. One of its development is Flexible Affix Classification. Flexible Affix Classification improves the accuracy for reduplicated words confix-stripping. In its growth, Indonesian language is used in two ways: formal and non-formal. Non-formal language is commonly used in casual situations such as conversations and social media post (Facebook, Twitter, Instagram, etc.). To get the root of the word of a casual conversation or a social media post, stemming algorithm which can process the non-formal words with affixes is required. Stemming non-formal words can be used in various information retrievals such as sentiment analysis on twitter posts. Therefore, this study modifies Flexible Affix Classification to be able to do stemming on non-formal word. Modifications are made by adding a non-formal affix rule. The result of the research shows that the algorithm made in this research has 73.3% accuracy while the Flexible Affix Classification algorithm has 35% accuracy in processing 60 non-formal affixed words.