Arabic language exhibits a complex but very regular morphological structure that greatly affect its automation.  Current available morphological analysis techniques for the Arabic language are based on heavy computational processes and/or the existence of large amount of associated data. Utilizing existed morphological techniques greatly degrade the efficiency of some natural language applications such as information retrieval system. 

This paper proposed a new Arabic morphological analysis technique.  The technique is based on the pattern similarity of words derived from different roots.  Unique patterns are extended and coded as rules that encode morphological characteristics.  The technique does not require either complex computation or associated data yet adjustable to maintain enough accuracy.  This technique utilizes a very simple parser to scan coded rules and decompose a given Arabic word into its morphological components. 

This paper provides an introduction to Arabic language and its morphological characteristic followed by an overview of currently available morphological techniques.  Explanation of the developed stemmer and its components including rule set and parser were given.  Experimental results and the work conclusion were provided at the end.