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Contact Name
Ismudiati Puri Handayani
Contact Email
iphandayani@telkomuniversity.ac.id
Phone
+6281285658967
Journal Mail Official
iphandayani@telkomuniversity.ac.id
Editorial Address
Jl Telekomunikas 1 Terusan Buah Batu
Location
Kota bandung,
Jawa barat
INDONESIA
JMECS (Journal of Measurements, Electronics, Communications, and Systems)
Published by Universitas Telkom
ISSN : 24777994     EISSN : 24777986     DOI : https://doi.org/10.25124/jmecs.v6i1
Journal of Measurements, Electronics, Communications, and Systems (JMECS) is a scientific open access journal featuring original works on communication, electronics, instrumentation, measurement, robotics, and security networking. The journal is managed by the School of Electrical Engineering and published by Telkom University. The target audience of JMECS are scientists and engineers engaged in research and development in the above-mentioned fields. JMECS publishes full papers and letters bi-annually in June and December with a high standard double blind review process. Review cycles are typically finished within twelve weeks by application of modern electronic communication facilities. All published articles are checked using ithenticate plagiarism checker software. The scopes include: ELECTRONICS (ELEC) Theory and Design of Circuits Biomedics COMMUNICATION SYSTEMS (COMS) Information Theory Source Coding Channel Coding Optical Communications Wireless Communications SIGNAL PROCESSING (SIGN) Signal and System Image Processing AUTOMATION AND ROBOTICS (AUTO) Industrial Automation Control Theory Control Systems INSTRUMENT AND MEASUREMENT (INST) Power systems Renewable energy Smart Building Sensors Acoustics MATERIAL AND DEVICES (MATE) Material for Electronics Nanomaterials Photonics NETWORKING AND SECURITY (NETW) Network Theory Communication Protocols Switching Internet of Things, ANTENNA AND MICROWAVE (ANTE) Antennas Propagations Nanosatellite Radar Remote Sensing Navigation ARTIFICIAL INTELLIGENCES (ARTI) Machine Learning Intelligent Transportation Systems
Articles 5 Documents
Search results for , issue "Vol. 11 No. 1 (2024): JMECS" : 5 Documents clear
The Wearable Band with Electromagnetic Band Gap Antenna for Heart Rate Detection System Sitepu, Karolina; Hafizha, Syahna; Riansyah, Aldi; Salim, Akhmad Raihan; Prabowo, Vinsensius Sigit Widhi; Nur, Levy Olivia; Ryanu, Harfan Hian
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol. 11 No. 1 (2024): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v11i1.7662

Abstract

Wearable antennas are antennas that can be applied to the human body and are made of flexible materials, making them ideal for healthcare technology. The quality of the signal received by the antenna directly affects the accuracy of heart rate detection If the antenna measurements indicate strong, clear signal reception, the heart rate monitor can accurately detect and interpret heartbeats. In this study, a planar monopole antenna was designed and developed using a circular patch with Ultra Wide Band (UWB) characteristics. The FR-4 and copper were utilized for the substrate and the ground plane and patch, respectively. Simulations and measurements were conducted at 2.4 GHz and 5 GHz. The antenna with the added EBG structure showed improved performance compared to the conventional antenna, exhibiting better S11 and VSWR values. Additionally, all radiation patterns were unidirectional.  Applying this antenna to transmit heart rate measurements results in an accuracy of  94.34% compared to conventional onsite heart rate measurement. This study demonstrates that the wearable band provides real-time heart rate monitoring, while the EBG antenna enhances sensitivity and accuracy in detecting heart rate. This research can be enhanced by optimizing the EBG design and conducting additional trials to ensure the device performs well for a variety of users.
IoT-Based System for Pothole Mapping Dwiandharu, Muhammad Andika Naufan; Aulia, Danny; Wisnutama, William Wafi; Pramudita, Aloysius Adya; Ryanu, Harfan Hian; Widhi Prabowo, Vinsensius Sigit
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol. 11 No. 1 (2024): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v11i1.7666

Abstract

Technology development allows various kinds of technology to provide convenience and better services. One of them is the development of technology with the Internet of Things. In this research, we have developed a system to detect and map damaged road conditions to give road users a better experience. The user is expected to use this system to collect data. Detection is done using an accelerometer sensor that estimates the speed of a vehicle. In the process of pothole detection, the accelerometer checks the value of each x, y, and z axis. When data meets the axis value, it is taken by Arduino and sent to the Raspberry Pi. Raspberry Pi, which is an integration of systems, processes data and classificates data. Also, Raspberry Pi enables GPS and camera to collect data in visual form. Data that has been processed, sent to the database to be displayed on the dashboard of application. The system was tested along Jalan Radio Palasari, Bandung Regency. From experiments that have been carried out by collecting 50 data, it is known that the delay in sensor detection is set for approximately one minute with a sending delay to the database of six seconds. The accuracy of data in detecting and mapping only differs by 3-6 meters from the real pothole road.
Interest Classification on Named Data Network Using the Supervised Learning Method Astuti, Sri; Mayasari, Ratna; Asror, Ibnu
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol. 11 No. 1 (2024): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v11i1.8100

Abstract

Named Data Network (NDN) is a next-generation network architecture that shifts the traditional data communications paradigm Unlike conventional networks that rely on IP addresses, NDN delivers content based on data names rather than specific locations. In NDN, consumers express their requests by sending interest packets containing content names. These names are then propagated through the network nodes, which forward them to the appropriate destinations. The forwarding strategy in an NDN network plays a crucial role in ensuring efficient data delivery. This strategy includes a set of rules that determine the next hop for each interest packet. These rules are designed to optimize the forwarding process, minimizing delays and improving network efficiency. However, if the forwarding strategy is implemented without accurately identifying the appropriate face (i.e., the network interface) to forward interests toward the producer or the nearest cache node, it can lead to significant delays and packet drops. This, in turn, negatively impacts Quality of Service (QoS) parameters and the overall performance of the NDN network. This study applies supervised learning to classify consumer-requested interests to overcome this issue. This technique leverages several related variables to accurately classify these interests. The outcomes of the conducted research demonstrated that raw data from the mini-NDN output can be processed and transformed into a usable dataset. This data is then utilized to train a classification model with supervised learning. In a scenario with 9 NDN nodes and varying numbers of interests, distributed both uniformly and according to Zipf's law, the Random Forest model performs effectively, achieving an accuracy rate of 86.2% with an error rate of 14.8%.
REAL-TIME MONITORING OF PLTS USING IOT TECHNOLOGY WEB-BASED supratno, setyo -; Habibie, Burhannudin Yusuf; Sugeng, Sugeng
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol. 11 No. 1 (2024): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v11i1.8146

Abstract

Conventional monitoring systems have several weaknesses, including limitations in acquiring real-time physical parameters, which impact performance. Additionally, human errors often hinder data quality, further compounded by the inability to respond swiftly to rapid changes in physical parameters due to diverse operating conditions. To address these challenges, an innovative method has been developed for solar panel current and voltage monitoring  using Internet of Things (IoT) technology. This system relies on the NodeMCU ESP8266 microcontroller and the INA219 sensor to monitor the current and voltage of the solar power system. Data obtained by the sensor is collected in real-time, stored in a cloud-based database, and visualized through a web platform. This allows users to monitor the system remotely and access solar panel performance information. Measurements indicate that discrepancies between manual and web-based data are within 2%. The average manual readings of PV voltage and current are 16.96 volts and 119.66 mA, while the web-based readings are 16.98 volts and 118.38 mA. The differences in voltage and current are 0.12% and 1.07%, respectively. The average battery voltage is recorded at 10.5 volts, while the DC motor load shows a voltage difference of 0.63% and a current difference of 1.15%. The battery power test also indicates a difference of 0.65%. This system is effective because it provides real-time access from any location, facilitates quick responses to anomalies, and supports maintenance planning by storing historical data.
IoT-Based Smart Monitoring and Controlling System for Shallot Planting Medium Conditions Using a Combination of Context-Aware and Fuzzy Logic Algorithms Pramudita, Brahmantya Aji; Meynako, Sisko; Ediananta, Muhammad Rafi; Budiman, Faisal
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol. 11 No. 1 (2024): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v11i1.8150

Abstract

Shallots are a high economic commodity that needs special attention because this plant is a high-risk horticultural commodity and is in the short-lived plant category. Moreover, shallot growth relies on environmental variables, such as temperature, soil moisture, soil pH, and humidity. However, Indonesian farmers have difficulties maintaining shallot growth since they only rely on the weather and do not use special equipment to measure the soil condition. Therefore, the monitoring and controlling system is required to be a solution for maintaining the growth parameters of shallot. This study proposed a system that could control and monitor the soil conditions of the shallot based on IoT technology and applied context-aware and fuzzy logic algorithms to control the actuator. The proposed system was developed to control the soil conditions using three specific liquids: neutral water, pH-lowering liquid, and pH-increasing liquid. These liquids were utilized to control the soil pH, soil temperature, and soil moisture. A microcontroller controlled them according to the context-aware algorithm analysis, and the data from the sensor was converted into context information. Then, fuzzy logic will use this information to control the liquid pump. The result can exhibit a high accuracy sensor with more than 0.9 of the coefficient determination, indicating that the sensor measurements perform similarly to the instrumentation devices as a reference. Moreover, the proposed system can successfully handle several conditions by utilizing the information processing of a context-aware algorithm and using it as control parameters of fuzzy logic.

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