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Driven by a spirit of innovation and a deep concern for public health, a group of students from the Information Management Program at the State Polytechnic of Jember (Polije) have developed “Kenali”, a technology-based early stroke risk detection system. Designed as both a web and mobile platform, the application allows users to independently and quickly identify potential stroke risks by simply entering basic health data.
The development team, who call themselves Team A4 SIGAP, includes Eka Setyo Saputra, Ahmad Rizal Habibullah, Farrel Ezza Kusuma, Moch. Rizki Romadhoni, and Abd. Aziz Ramadloni. By integrating machine learning with information technology, they created a digital solution that not only serves as a predictive tool but also as a resource for education, personal health monitoring, and informed medical decision-making.
“Through the Kenali app, we want people to become more aware of the importance of early stroke prevention. Just by entering a few pieces of data, users can quickly gain insight into their health condition,” said Eka Setyo Saputra, representing the team.
He added that the app was designed to be accessible for everyone, even those without a medical background.
Kenali uses a Support Vector Machine (SVM) algorithm in its machine learning system, trained on datasets from stroke patients to recognize input patterns and diagnostic outcomes. Once users input the necessary data, the system processes it and instantly returns a stroke risk prediction, categorized into different levels and displayed through a user-friendly interface.
The system has two core interfaces: a web platform for registration and data management, and a mobile application focused on direct detection and monitoring. The mobile version features a home dashboard, prediction tools, data visualization, news updates, personal profiles, and detection history empowering users to track their health progress over time.
“Our hope is that Kenali can contribute to the development of machine learning in technology and support stroke research in the medical field, while also helping individuals become more proactive about their health,” Eka added.
Beyond its diagnostic function, Kenali is also designed to educate. The app provides curated news and informative articles about stroke and healthy lifestyle practices, helping users take preventative steps in their daily lives.
With a cost-effective development model and broad accessibility, Kenali stands out as a practical digital health solution. It aligns with efforts to transform disease detection and prevention systems in Indonesia through smart technology. This innovation also underscores the vital role of young generations in addressing global health challenges through adaptive and solution-driven approaches. (rda)