SCREENING SASTRIC PAIN LEVELS USING THE CASE BASED REASONING (CBR) METHOD BASED INTERNET OF THINGS (IoT)

Abstrak

Abstract

Background: The increasing incidence of gastric diseases in adolescents, such as gastritis and GERD, requires innovative solutions to support early detection and appropriate treatment. This research tries to overcome this problem through the development of a prototype based on Internet of Things (IoT) technology. Methods: developed using the Case Based Reasoning (CBR) method. This system is basically designed as an experience-based gastric pain scale screening tool in adolescents, involving four main steps, namely retrieve, reuse, revise, and retain. Qorry's prototype provides early diagnostic features that can help them identify different levels of pain. Results: The Qorry prototype provides a diagnosis page that users can use to identify the level of gastric pain based on the symptom data entered, provide initial results and provide solutions for further prevention. Conclusion: The Qorry prototype has good potential in facilitating access for users and the public to health screening services, especially for technology-based gastric pain. Apart from that, the Qorry prototype research can be further developed in the form of IoT.