The rapid and dangerous spread of COVID-19 has forced governments in various countries to provide information on patients’ medical records to the public in the context of prevention. Meanwhile, patients’ medical records are vital and confidential because they contain patients’ privacy. Changing and falsifying a patient’s medical record leads to various dangerous consequences, such as mishandling which results in the patient’s death. From these problems, the research introduces a new model with a combination of blockchain technology and the Elliptic Curve Digital Signature Algorithm (ECDSA) to secure the medical records of COVID-19 patients. This model is an improvement from the model and framework proposed by previous researchers. The proposed model consists of two big parts (front and back end). Then, the simulations are carried out to measure and prove the level of security of blockchain technology in securing patient medical records. The research results show that the ECDSA algorithm can protect patients’ medical records from being opened by unauthorized parties. Then, blockchain technology can prevent changes or manipulation of patient medical records because the information recorded on the blockchain network is impossible to change and will be immutable. The research has successfully introduced a new model in securing patient medical records.

COVID-19 is a disease caused by the coronavirus and causes the main symptoms in the form of respiratory problems. One way to overcome the COVID-19 pandemic is through the vaccination process. However, in practice, the public is still not educated about the importance of vaccination in preventing coronavirus infection, so it is necessary to develop a game that provides education to the public to vaccinate. This study chose games as educational media because there are many game enthusiasts and the delivery of education through games is more memorable than on other platforms. This study uses the Game Development Life Cycle (GDLC) method in the game development stage. In addition, to create intelligent coronavirus enemy NPC characters in this study, Finite State Machine (FSM) and Collision Detection methods will be implemented to detect the accuracy of players' shots. The results were obtained in the form of a game "Kill Corona Virus" which is used as a medium of education for the public about the importance of vaccination. Based on the results of the tests carried out, it was found that the implementation of the Collision Detection method in the game in detecting collisions was appropriate and quite accurate and the Finite State Machine method succeeded in creating coronavirus enemy NPCs with appropriate states. In addition, based on the results of processing respondents' answers, it is known that the ”Kill Corona Virus” game that was built can convey vaccination education messages well and make people interested in vaccinating.

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