Health promotion system is a key element of health care system to improve public health, increase community care for health, and provide health services that have sustainable access capabilities. This system is realized by providing health services information that acts as personal advisor that equipped with adequate skills in order to improve individuals and communities health quality eventually by encouraging person for implementing healthy behavior in all spheres. To increase public awareness to actively contribute for improving individual health and communities, health promoting system require widely accessible system that able to adapt in environment changing, providing sustainable service that are able to deliver adequate resources to support health system, eliminate financial problems related to the usage of service, provide prevention services, and promote health services as well as advocacy service.
In order to provide high quality health promotion system in the form of knowledge provision to support promote health services and advocacy service capabilities, context modeling system needs to be modeled based on semantic to enable system become accessed sustainable on intelligence environment which environments change rapidly. Contribution of this study is to provide activity modeling using semantic based reasoning to ensure adequacy of the model in supporting health promoting system application to persuade user performed physical activities to improve health live quality.
User activity engaged in health promoting system should be identified using activity theory to capture important context information. From activities list engaged, activity modeling is performed to obtain context of knowledge. Furthermore, those contexts will be developed using ontology and reason using both ontology reasoning represented in RDF Schema and user-defined reasoning using First Order Logic by loading context to the rules created using Jess. The final result of this research is a consistent relationship and adequate model which has proven with the result of user-defined reasoning to deduct user activity perform recently.

Health promotion system is a key element of health care system to improve public health, increase community care for health, and provide health services that have sustainable access capabilities. This system is realized by providing health services information that acts as personal advisor that equipped with adequate skills in order to improve individuals and communities health quality eventually by encouraging person for implementing healthy behavior in all spheres. To increase public awareness to actively contribute for improving individual health and communities, health promoting system require widely accessible system that able to adapt in environment changing, providing sustainable service that are able to deliver adequate resources to support health system, eliminate financial problems related to the usage of service, provide prevention services, and promote health services as well as advocacy service.
In order to provide high quality health promotion system in the form of knowledge provision to support promote health services and advocacy service capabilities, context modeling system needs to be modeled based on semantic to enable system become accessed sustainable on intelligence environment which environments change rapidly. Contribution of this study is to provide activity modeling using semantic based reasoning to ensure adequacy of the model in supporting health promoting system application to persuade user performed physical activities to improve health live quality.
User activity engaged in health promoting system should be identified using activity theory to capture important context information. From activities list engaged, activity modeling is performed to obtain context of knowledge. Furthermore, those contexts will be developed using ontology and reason using both ontology reasoning represented in RDF Schema and user-defined reasoning using First Order Logic by loading context to the rules created using Jess. The final result of this research is a consistent relationship and adequate model which has proven with the result of user-defined reasoning to deduct user activity perform recently.

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