The government’s physical distancing policy to prevent transmission of the covid19 virus caused changes in learning patterns from face-to-face learning to distance education. The application of distance education at Universitas Negeri Yogyakarta is one of them through e-learning. Measurement of the level of e-learning user satisfaction is an assessment of the success of e-learning itself. The method used to measure students’ level of satisfaction using e-learning is End-User Computing Satisfaction (EUCS). EUCS has five indicators, namely, Content, Accuracy, Format, Ease of Use, and Timelines. The research sample was taken using a random sampling technique. The data collection technique was carried out using a questionnaire. Data analysis uses descriptive statistical analysis and inferential statistical analysis. Based on the analysis results, the content evaluation value is 4.0300, the accuracy evaluation value is 4.0200, the evaluation value is 4.2550, the evaluation value for easy use is 4.0288, and the evaluation value for timeliness is 4.0900. The overall analysis results showed that the students were satisfied with the e-learning course in vocational learning media.

There are obstacles in the delivery of information during pre-engineering activities at the Vocational High School. There needs to be a system that makes it easy to deliver information from schools to students who carry out internship. The purpose of this study was to evaluate the usefulness of the evaluation of the usefulness of the task information learning system and the monitoring of student labor based on the SMS gateway with raspberry pi. The instrument used in usability testing is the Computer Usability Satisfaction Questionnaires: Psychometric Evaluation and Instructions for Use questionnaire developed by IBM for software usability measurement standards. The instrument for testing usability aspects with the Computer System Usability Questionnaires (CSUQ) questionnaire developed by IBM uses a Likert scale as a measurement scale. The data for the trial were 20 respondents consisting of adaptive normative subject teachers, internal engineering committee and smartschool developers. Based on the results of testing the quality of software developed on the usability aspect has a percentage of 85% or has a high quality scale and based on alpha cronbach calculations has a calculation result of 0.851 or has a “good” category. The SMS Gateway system with Raspberry Pi for Internship Assignment and Monitoring meets the usability aspect and is suitable for use.

Load Cell Sensors are transducers (transducers, electronic components that can measure physical quantities into electrical signals) that can convert the pressure by the load into an electrical signal. IC HX711 is a weighing module, which has a working principle of converting the measured changes in resistance changes and converting them into voltage quantities through the existing circuit. Load cell and HX7411 are used to obtain data of weight which will be compared with a commercial digital weight scale that the accuracy has been verified. In collecting data of weight, there are several calculation methods including the mean, modus, and median method. This study aims to provide test results for the three methods with different variations in delay. Delay is used to avoid errors in taking data from the sensor directly and also to provide pauses for the sensor in real time data collection. The test was conducted with four human subjects who have differences in body weight. The variation of delay used is 250ms, 500ms, 750ms, and 1000ms. The test results show that when testing variations in body weight with a delay time of 250ms, the mean method has the best results with a value of nmean = 2. In the 500ms delay test, the median method has the best results with the value nmedian = 3. In the 500ms delay test, the mean and median methods have the same good results with values of nmean = 2 and nmedian = 2. In the 1000ms delay test, the median method has the best results with a value of nmedian = 2. The results of the whole test show that the values of Nmean = 6, Nmedian = 8, and Nmodus = 2 which indicate that the median method is the method that has the best level of precision.

The rotor is one of the vital components of a wind turbine. In the design of the rotor, the expected result is the most optimal power. This purpose study is to optimization of the Horizontal Axis Wind Turbine power of various parameters such as airfoil, angle of attack, and pitch angle. Airfoils (NACA 4412-2412 T.E. mod, NACA 2412-4412 T.E. mod, NACA 4412-2412 L.E. mod, NACA 2412-4412 L.E. mod), angle of attack (0, 2, 4, 6), and pitch angle (0, 1, 2, 3) are the parameter variations used. The simulation method uses BEM (Blade Element Momentum), and the Taguchi for optimization is based on the L16 orthogonal array matrix. The ANOVA has to determine the contribution of each parameter to the HAWT power generated. Simulation and optimization results show that the most optimal parameter was a NACA airfoil 4412-2412 L.E mod, at 0˚ angle of attack and 0˚ pitch angle, with the resulting power reaching 1015780 Watt. The ANOVA analysis shows the airfoil parameter has the greatest contribution to the rotor power of the HAWT compared to the angle of attack and pitch angle.

The rate of transportation accidents is still a major challenge in many countries. Many factors can cause transportation accidents, especially problems with the vehicle’s internal system. Fuel Injection-based vehicles have a centralized electronic system through the ECU as control. The outstanding Engine Diagnostic Tool has several weaknesses, including high price, not plug and play, has limited system support. It is necessary to develop a Prototype Engine diagnostic tool that is easy to use, has an overall carrying capacity, and can be easily applied by middle-class vehicle repair shops. So, the researchers researched the Internet of Things (IoT)-Based Wireless Engine Diagnostic Tool prototype using a Raspberry Pi. This study aims to (1) produce a Prototype of the Wireless Engine Diagnostic Tool Based on the Internet of Things (IoT) Using Raspberry Pi and test the functionality of the Prototype Wireless Engine Diagnostic Tool with Raspberry Pi Technology. The research method used is the Research and Development method. The research aims to produce specific products. The product produced and tested for functionality in this research is a Wireless Engine Diagnostic Tool Based on the Internet of Things (IoT) Using Raspberry Pi. The results show that the function runs 100% on the ECT, IAT, TPS, RPM meter, Oxygen Sensor, and Vehicle Speed Sensor tests.