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An aircraft is a transportation system that works in conditions according to the standards. When an aircraft technician is aware of a system failure or damage, he must make the right decision to overcome the problems that occur. A relatively high level of accuracy decision making based is a necessary treat. This condition must be anticipated in aircraft vocational education. An integrated landing system is one of the subsystems on an aircraft that requires quick and precise handling if there are problems. A practical method that accommodates various concepts in troubleshooting is proposed to facilitate aircraft technicians’ competence. This method performs standardization of troubleshooting steps in a particular algorithm so that it is more systematic. The appropriate validation and verification steps follow this troubleshooting mechanism to ensure that the system is up to standard.

Wireless sensor networks, as remote monitoring system support or Internet of Things subsystems, require reliability and stability, which greatly influence sensor life spans. Optimization efforts were a breakthrough to obtain these requirements. The optimization carried out in this study is related to the clustering-based localization process. The optimization algorithm used was game theory. Simultaneously, clustering information in an energy availability based sensor node configuration helped the sensor node's tracking process. Optimization in the localization process determined the coalition of anchor nodes, where the selection of nodes as coalition members was conducted through geometric approaches with game theory. This proposed concept was validated using a simulator built on the MATLAB platform. Root Mean Square Error (RMSE) was chosen as a measurement to show accuracy. The simulation results indicated that the number of dead nodes could be delayed by about 1,000 rounds if there are improvements in clustering localization using game theory. The experimental results showed that network performance increased after this cluster-based localization process, which indicated an increase in the number of data packets sent and lifetime of the sensor node. The simulation results for the data delivery test showed a 20% increase in data packets sent.

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At this time aerospace technology is very advanced. This is very closely related to advances in information technology and aerospace, so the learning process in aerospace vocational education also progresses. The learning process that was originally very manual now has used a computer as a support system. Learning methods or content of learning materials are also adjusted. One of them is the next generation of avionics. At this time, many types of aircraft have used electronic flight bags to control the aircraft. This technology is very advanced, using many automatic electronic devices such as sensors, actuators and other sophisticated devices that are connected by wireless networks and applications on computers. Studying the current generation of avionic systems is not easy, it is very complicated and sophisticated. This is a problem whose solution that must be sought to provide approach to learning. Studying theoretically and classically in Avionics will be very difficult and boring. A learning method that approaches the real conditions facilitates the process of understanding, namely utilizing virtual instruments. A teaching technique that is supported by applications on computers that resemble conditions in an aircraft. In this paper, a sub-section of avionics is assisted with computer applications, so the actions taken will have an effect on what the conditions of the aircraft are. The perceived benefit is that learning material is easier to understand and implement. This study will present learning methods using virtual instruments. The general design of virtual instruments related to avionics was proposed in this study in order to facilitate teaching avionics to students.