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Technology Development in the health sector is one of the main targets in mobile application development today. Sharing knowledge and experience among health workers are challenging to implement because of the lack of a place to exchange their ideas. Based on this background, we built a HelloCare application on the Android platform as an application of knowledge management for health workers. Testing of the application using the System Usability Scale (SUS) to 30 respondents consisting of nurses and physicians, the result of effectiveness is 80.88% as for satisfaction is 96.16%. We also test the application using knowledge management functions and get the average result at score 3.33871 of 5. It means that the HelloCare application is good enough to support knowledge management in the health area. Keywords: knowledge management, mobile application, health workers

Web has evolved into a tool that is not only able to provide information but also to process information. Processing information by utilizing web technology turns web becoming dynamic information media. We could do many things by deploying web, such as building the Helpdesk Ticketing System for a company or institution. Every company has vision, mission, and also programs by utilizing the infrastructure that has been provided by the company. By using a Web-based Helpdesk Ticketing System, solving problems in a company will be faster, precise, accurate, and more effective. The development of a Web-based Helpdesk Ticketing System gives a better impact and efficient than manual monitoring. We use the usability method to test the user satisfaction level toward the system that has results 87.5%.  Keywords: Helpdesk, Ticketing System, Information System, Web.

The COVID-19 pandemic, the growth of smartphones, and the internet have driven the use of technology for monitoring TB patients. Innovation in management of TB patients is needed to improve treatment outcomes. The study was conducted to obtain a predictive model of medication safety and solution model for at-risk patients, and to improve medication safety through mobile applications. The research was conducted in 4 stages, namely qualitative, quantitative (cross-sectional), qualitative, and quantitative (quasi-experimental, post-test group control design). Data were taken at the Public Health Center in Jakarta, Indonesia. Samples were taken by cluster random sampling. For quantitative research, 2nd phase (n = 114) and 4th phase (n = 96) were analyzed using logistic regression. This study analyzed predictors of medication safety to assist in monitoring patients undergoing treatment. At-risk patients were educated using an algorithm programmed in the application.

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