JECCOM: International Journal of Electronics Engineering and Applied Science https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas Jeccom: International Journal of Electronics Engineering and Applied Science en-US emadona38@gmail.com (Era Madona) anggara@pnp.ac.id (Anggara Nasution) Fri, 29 Dec 2023 00:00:00 +0000 OJS 3.3.0.7 http://blogs.law.harvard.edu/tech/rss 60 Design of Internet Of Things (IoT) trainer kit with Multi Communication https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/3 <p>Industry 4.0, or the Fourth Industrial Revolution, is a recent technological development that has significantly changed the industrial production process. One of the keys to this change is the Internet of Things (IoT), where the role of humans is likely to diminish and be replaced by machines. Aligning the workforce with IoT is important, but creating a qualified workforce is a challenge. IoT learning modules are needed to help students understand IoT concepts. The purpose of this research is to design an Internet of Things kit module with Radio communication with LoRa SX1278 Ra-02. The research stages start from literature study, hardware design, software design and overall testing. Module testing is done by sending DHT11 sensor data using LoRa SX1278 Ra-02 and monitored in Thingspeak. From the test results that have been carried out, it can be concluded that sending using LoRa (Long Range) technology is influenced by distance and obstacles. At a distance of 40 to 230 metres, communication between the Lora Transmitter and Lora Receiver is successful, which shows that LoRa technology is able to overcome communication distances in that range. However, at a distance of more than 230 metres to 300 metres, data transmission can still be done by the Lora Transmitter, but the data cannot be received by the Lora Receiver, indicating a bottleneck in communication.</p> Era Madona, Efrizon, Anggara Nasution, Rara Yetrisia, Laxsmy Devy Copyright (c) 2023 JECCOM: International Journal of Electronics Engineering and Applied Science https://creativecommons.org/licenses/by-nc-sa/4.0 https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/3 Sat, 30 Dec 2023 00:00:00 +0000 Monitoring and Control System for Electrical Energy Consumption Based on The Internet of Things https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/14 <p>Electrical energy consumption in the household sector is frequently uncontrolled, particularly when electronic devices are used. That is the tendency of users to forget to turn off or unplug the electronic device from the socket. In that case, modifications are made to the socket so that it can be controlled remotely via a smartphone. The hardware design uses the NodeMCU ESP8266 as a microcontroller combined with the PZEM-004T sensor module for electrical magnitude. Relay modules are used to secure the circuit in cases of higher loads. So that in the system, all three sockets can be monitored simultaneously. While the software design uses MIT App Inventor and Thingspeak Platform as servers. The data is saved in CSV format, which can be converted to Google Sheets or Microsoft Excel. Data is stored in the form of the name of the electronic equipment, the time of use, as well as voltage, current, power, cos phi, and electrical energy used. So that users can regulate the use of electrical equipment at home and reduce the waste of electrical energy. The test results showed the average faults for voltage, current, power, cos phi, and energy were 0.06%, 5.32%, 5.67%, 0.7%, and 7%, respectively.</p> Andi Syofian, Yugerita Firmance, Yultrisna Yultrisna Copyright (c) 2024 JECCOM: International Journal of Electronics Engineering and Applied Science https://creativecommons.org/licenses/by-nc-sa/4.0 https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/14 Sat, 30 Dec 2023 00:00:00 +0000 Implementation of LiDAR Sensor for Mobile Robot Delivery Based on Robot Operating System https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/15 <p>Recent research has focused on the development of mobile delivery robots as part of the rapidly evolving autonomous technology. The main focus is on creating mobile robots capable of efficiently delivering goods without human intervention. This involves designing systems, core technologies, and overcoming various challenges. The navigation system of the delivery robot is enhanced by the use of LIDAR (Light Detection and Ranging) sensors. One of the sensors used is the RPLIDAR A1M8 which is capable of detecting nearby objects with a distance reading of 360°. Trials were conducted to evaluate the robot's navigation performance with a load variation of 0 kg to 20 kg. The test results show that RPLIDAR A1M8 can read distances up to 1200 cm with an error rate of about 3.15%, and a minimum distance of 15 cm with an error of 1.45%. The durability of this sensor reading is well maintained, with a presentation error of only 0.4%. Mapping trials in the room produced an average error of 18.57% without tracking, and 5.02% with tracking. The weight of the load carried by the robot affects the speed and travel time. The heavier the load, the robot speed decreases from 0.264 m/s at 0 kg load to 0.127 m/s at 20 kg load. Likewise, the travel time increases with the weight of the load, from 7.6 seconds to 15.6 seconds.</p> Fiqri Ahmad Agung, Herizon herizon, Era Madona, Muhammad Rohfadli, Ja'far Ja'far Copyright (c) 2024 JECCOM: International Journal of Electronics Engineering and Applied Science https://creativecommons.org/licenses/by-nc-sa/4.0 https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/15 Sun, 31 Dec 2023 00:00:00 +0000 Implementation of K-Nearest Neighbor for Fall Position Detection of Dementia Patients Based Microcontroller https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/2 <p>A microcontroller-based detection tool for the presence of patients with dementia has been made using the K-Nearest Neighbor (KNN) method with the help of coordinate points that can be seen via Google Maps. which is based on patient care with a patient-oriented approach. The targets of this research are (a) designing and implementing a fall detection system using the mpu6050 sensor, (b) using the (KNN) method to determine the coordinates of the location of dementia patients using GPS. The research method starts from making a prototype and measuring system performance. The test results on GPS produced an average latitude error of 0.002091% and an average longitude error of 0.000032% in Pauh District, while in Lubuk Kilangan District the average latitude error was 0.002641% and an average longitude error of 0.000150%. The KNN method with the Eucledian distance formula can help supervisors find out the nearest police station to the patient through the coordinate points detected by GPS by taking the smallest value from the comparison of values in the form of degrees between the Pauh police station and the Lubuk Kilangan police station for the patient. Overall the tool can function well.</p> Yulastri, Era Madona, Laxmy Devy, Anggara Nasution, Nur Iksan Copyright (c) 2024 JECCOM: International Journal of Electronics Engineering and Applied Science https://creativecommons.org/licenses/by-nc-sa/4.0 https://elektro1.pnp.ac.id/jeccom1/index.php/ijeeas/article/view/2 Sun, 31 Dec 2023 00:00:00 +0000