The purpose of this research is to monitor the temperature by applying arduino pro mini and ESP32 cam using IoT technology which is connected to a web interface. Arduino is used as the main brain of the system where arduino will read data from the MLX90614-ACF temperature sensor. Sensor data will continue to be sent to the server by arduino via the ESP32 cam module. This tool can also take pictures and send images automatically at the same time when measuring temperature. The captured image will automatically be sent to the PC/laptop monitor screen via the website. The website is used to display and monitor the results of temperature measurement data and display the image results from the ESP32 cam. The process of taking photos and measuring body temperature is done automatically. Users can also view data from sensors and photo data sent by arduino and ESP32 cam via the provided web interface. From the test results, this system has been running well where all sensor data is sent and can be displayed on the website. Images and measurement data results are sent to the monitor screen via the website interface with a measurement accuracy of 99.6%.

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COVID pandemic has influenced human life in various sectors. Various attempts were made to reduce the virus transferring by work from home, social distancing, and also including hand hygiene. So far, most of the available hand sanitizers do not operate automatically. This article aims to make an automatic hand sanitizer where soap and water can come out automatically. Besides that, automated hand sanitizer will make notification to the owner, if the liquid has run out to the smartphone. The infrared (IR) will sense the presence of heat and motion of the object with the distance up to 50mm. It send data to the Arduino Nano to activate the pump. If the ultrasonic sensor detect the distance of water to he sensor 35 cm it will send data to node MCU that connect to Blink server. It can transfer the data to the output devices such as smartphones or PC based on the Internet of Things (IoT). The results of the hand sanitizer testing that the system can run smoothly with a minimum detection error of transferring data.

Researchers designed and implementation of thermal body measurement system for Unesa residents when they entered the building. The system design is made using engineering methods. Before body temperature is measured, the object will occupy a position at a predetermined point. At that point installed LDR which functions to turn on the servo motor that will move down and turn on the infrared sensor. At an altitude that has been detected by an infrared sensor, the motor will stop and start the temperature measurement process. The temperature sensor uses MLX 90614 which reads data from the reflection of infrared light in the form of raw data. Then the data is processed by a microcontroller using Arduino to become real data. The processed temperature data is displayed by the LCD and sent to the esp32-cam camera. Then esp32-cam will take photos as documentation. Data that has been processed will be grouped according to the 'condition' group that has been determined. Data that has been obtained in the form of temperature data, condition data and photo documentation, is sent to the webserver for display. All temperature measuring components have shown accurate data with the following test results. Sensor Temperature sensor MLX 90614 can measure temperatures at a distance of 30 cm. The temperature measurement program code on Arduino works well with a temperature value of 37.3oC. Camera image output format esp32-cam is a JPEG that is displayed on the websever. The Body Temperature Measurement System using the MLX 90614 Temperature Sensor for Early Detection of COVID-19 Symptoms can be used with an average error of 0.6% and a standard deviation of 0.078.

The accuracy level of the student determination in a class often has been paid less attention in educational data mining. So, this paper studies how to improve the performance of classification method to reach the higher of level accuracy. Therefore, we optimize logistic regression using equal frequency discretization method. Here, we test the student data by three intervals, four intervals, and five intervals. For logistic regression, we implement two regularization types, namely: lasso, ridge. Furthermore, to evaluate the results, we use the random sampling technique. Additionally, we measure the results by four classifier metrics, namely: F1, precision, accuracy, and recall. The experimental result shows that this method can be applied to optimize the logistic regression. On logistic regression_lasso and logistic regression_ridge, the three intervals achieve the highest of accuracy level. They can improve the accuracy level about 9% - 9.4%, respectively.

The Department of Electrical Engineering, Universitas Negeri Surabaya (Unesa) is developing a laboratory, including a control system laboratory. The control system engineering teaching team prepares themselves by making a PLC training kit to accompany the existing modules. With the aim that students know and understand the application of control systems in industry. This can foster student learning motivation in attending lectures and greatly support student competence before entering the workplace. The study used is development research by producing a product prototype in the form of a fluid mixing process training kit. The steps taken are designing, making tools, integrating software to hardware and validating the tools. The result of the research is that the fluid mixing process training kit has worked according to the instructions given and is suitable for use as a learning medium.

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<div align="center"><table width="645" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="439"><p class="Abstrak"><strong>Abstract:</strong> This research aims to determine the validity and practicality of training kit and PLC learning module as an instructional media for PLC course for students of electrical engineering education at Universitas Negeri Surabaya. That was development research using Thiagarajan’s 4D models, this study only used the first three stages, not up to the disseminating stage, as the researcher only developed the training kit and module. The design of the training kit and module were developed and validated based on the look of the product, the quality of the media, and the suitability of the media for the curriculum and illustrations.  The results of validation and trial process were used to determine the feasibility level of the module that had been developed in terms of validity and practicality. Findings showed that the training kit validation was valid at 85.18%, the module validation was valid at 83.33%. Another finding depicted that students’ responses showed that both the training kit and module were practical with percentages of 85% and 82.17% respectively. So that the training kit and PLC module were feasible to be used in PLC learning process by students of Electrical Engineering Education program at Universitas Negeri Surabaya.</p><p class="Abstrak"><strong>Abstrak:</strong> Penelitian ini bertujuan untuk mengetahui validitas dan kepraktisan training kit dan modul pembelajaran PLC sebagai media pembelajaran mata kuliah PLC bagi mahasiswa pendidikan teknik elektro Universitas Negeri Surabaya. Yaitu penelitian pengembangan menggunakan model 4D Thiagarajan, penelitian ini hanya menggunakan tiga tahap pertama, tidak sampai tahap diseminasi, karena peneliti hanya mengembangkan training kit dan modul. Perancangan perangkat pelatihan dan modul dikembangkan dan divalidasi berdasarkan tampilan produk, kualitas media, dan kesesuaian media untuk kurikulum dan ilustrasi. Hasil proses validasi dan uji coba digunakan untuk mengetahui tingkat kelayakan modul yang telah dikembangkan ditinjau dari validitas dan kepraktisan. Hasil penelitian menunjukkan validasi training kit valid sebesar 85,18%, validasi modul valid sebesar 83,33%. Temuan lain menunjukkan bahwa tanggapan siswa menunjukkan bahwa baik perangkat pelatihan maupun modul praktis dengan persentase masing-masing 85% dan 82,17%. Sehingga training kit dan modul PLC layak untuk digunakan dalam proses pembelajaran PLC oleh mahasiswa program studi Pendidikan Teknik Elektro Universitas Negeri Surabaya.<strong></strong></p></td></tr></tbody></table></div>