Computer network security has become an important issue in recent decades, the government and several international organizations have invested in professional education and training for computer network security. In addition, with the increasing incidence of computer network security crimes, the government and several organizations have taken precautions by providing training to students about computer network security. Some parties develop learning models that are suitable for students and find appropriate learning methods to produce professionals in the field of computer network security that is more effective. The purpose of this study is to design a framework-based Learning system in the form of an Adaptive Online Open Course in Computer System Security Subjects for Information Technology (IT) students. The benefits of this framework are to enhance students' skills and abilities in industrial-based computer network security, startup companies and the ability to complete CTF competitions in IT network security. The framework designed is Adaptive in which students learn according to the interests and topics of Computer Network Security. Interest-based on students in completing the pretest per topic. Testing in this study is testing the impact and improvement of students' learning abilities and skills on Computer Security and Security System Competence testing in a small group consisting of 20 students by seeing the success of completing 3 CTF Topics with each topic totaling 100 computer network security problems in the CTF competition, the average validation result was 83.01% and the CTF exam passing rate was 93%
The development of learning technology in industry 4.0 in the last few years was growing rapidly one of which was a virtual application. One of the virtual learning applications developed was a virtual laboratory. The use of virtual laboratories in Revolution 4.0 was very useful especially educational institutions that did not have enough space and equipment. Virtual laboratory research had been carried out in recent years. The development of virtual laboratories developed was the media, models, and materials in virtual laboratories. The existing virtual laboratory was one-way learning. Virtual laboratories had no feedback with users especially the desires and abilities of users in virtual laboratories. Laboratory learning based on user desires and abilities as needed. This learning model was known as personalization. This research developed a virtual laboratory that was personalized by utilizing artificial intelligence. The ability and will of the user were processed by artificial intelligence to determine the model, media, and materials suitable for the user. The results of testing in this virtual laboratory obtained accuracy values according to users based on personalized obtained at 90.8%.
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