An effective decision support system needs to deal with several heterogeneous data sources. Sometimes, the knowledge was explored without integration data sources are wrong. Also, Decision support system is weak in the reusability. To address these challenges, this paper proposes semantic enhancement on the gene expression model (genotype/phenotype system) as an Evolutionary Algorithm to be suitable for "communication decision support system" called Semantic Gene Expression Decision Support System (SGEDSS). The proposed method can solve several mining tasks as association rules and classification through a large volume of heterogeneous data. The proposed method SGEDSS adapts the main components of the genotype/phenotype system by ontology-based to ameliorate the decision support system framework. In thispaper, we use certainly ODSS (Ontology Decision Support System framework), which proposed to enhance DSS. The proposed method simulates somatic mutation on the communication application certainly. That is for accurate simple decision also.