This study presents an Arabic letter encoding system for eye-tracking communication, aiding individuals with locked-in syndrome. Utilizing electrooculography (EOG), we translate eye movements into Arabic text, based on an already existing database. The contribution of the proposed approach is to assign specific stroke combinations to Arabic characters, akin to Katakana character formation. The first step is to analyze the specificity of the EOG signal. Then a study of Code-protocol- based eye input systems for Katakana characters is done. Based on these two concepts, first basic strokes for Arabic letters are proposed. followed by a proposition of Arabic letters encoding which is the main contribution of this paper. The second contribution is how to adapt this new encoding to extract corresponding EOG signal. Our system is distinctive in its semantic approach, where similar Arabic letters, having comparable eye-strokes share related eye-strokes, enhancing intuitiveness and ease of learning. The output of our work is a database of 2500 records. It allows researchers in this field to decode the EOG data into accurate Arabic text, demonstrating its potential as a non-verbal communication tool for physically challenge.