Research on Instrumentation
Aim and Scope Research on Instrumentation is a scientific journal that aims to provide a comprehensive platform for the dissemination of research and advancements in the field of instrumentation. Its focus is on analog and digital circuit design, measurement systems, control systems, antennas and wave propagation, electromagnetic, and other relevant areas. The journal welcomes original research articles, review papers, and technical notes that contribute to the development and application of instrumentation in various engineering and scientific disciplines. Scope: Analog and Digital Circuit Design: Research on the design, optimization, and application of analog and digital circuits in instrumentation. This includes, but is not limited to, analog-to-digital and digital-to-analog converters, signal conditioning circuits, and mixed-signal integrated circuits. Measurement Systems: Advances in the development of systems and methodologies for precise and accurate measurement in various environments. Topics may include sensor technology, data acquisition systems, signal processing techniques, and calibration methods. Control Systems: Innovations in control system design, including feedback and feedforward control, adaptive and robust control, and applications of control theory in instrumentation. This also covers real-time control systems and embedded systems design. Sensors and Actuators: The design, development, and application of sensors and actuators in instrumentation. This includes studies on sensor materials, sensor networks, MEMS-based sensors, and their integration into complex systems. Signal Processing: Research on advanced signal processing techniques for instrumentation systems, including noise reduction, filtering, data compression, and pattern recognition. Embedded Systems: Studies on the integration of embedded systems in instrumentation, focusing on hardware-software co-design, real-time computing, and the development of low-power and high-performance systems. Test and Calibration Methods: Development of innovative testing and calibration techniques for instrumentation systems, ensuring accuracy, reliability, and repeatability in measurements. Applications of Instrumentation: Papers exploring the application of advanced instrumentation in fields such as industrial automation, medical devices, environmental monitoring, telecommunications, and aerospace engineering. Electromagnetic, Antenna and Wave Propagation: Antennas—covering their analysis, design, development, measurement, and testing—as well as radiation, propagation, and how electromagnetic waves interact with both discrete and continuous media. Additionally, the journal addresses applications and systems related to antennas, propagation, and sensing. These include applied optics, millimeter- and sub-millimeter-wave techniques, antenna signal processing and control, radio astronomy, and the propagation and radiation aspects of terrestrial and space-based communication. The Research on Instrumentation is dedicated to advancing the field by publishing high-quality research that drives innovation and facilitates the application of cutting-edge instrumentation techniques across various industries. Contributions that explore interdisciplinary approaches and emerging technologies are highly encouraged.
Articles
23 Documents
<![CDATA[An IoT-Enabled Tomato Sorting System with Dual Opposing Ultrasonic Sensors and Multispectral Color Detection for Five-Class ]]>
<![CDATA[Nurahmadani]]>;
<![CDATA[Asrizal]]>;
<![CDATA[Fatni Mufit]]>
<![CDATA[ Research on Instrumentation Vol. 3 No. 1 (2026): Research on Instrumentation ]]>
Publisher : <![CDATA[RESSTECH ]]>
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DOI: 10.66926/rins.2026.1.31
<![CDATA[Tomato sorting plays an important role in maintaining crop quality, especially in terms of ripeness and size, which affect market value. Tomato sorting is generally still done manually, which is time-consuming, labor-intensive, and often results in misclassification. To address this issue, this study aims to design an automatic tomato sorting device using a TCS34725 color sensor and an ultrasonic sensor integrated with the Internet of Things (IoT) using ESP32 as a remote monitoring system. The research method used is research engineering, which includes hardware and software design. The hardware consists of a DC motor to drive the conveyor, a PCA9685 module to control four servos, a TCS34725 sensor to detect RGB values, and two opposing ultrasonic sensors to measure diameter. The software was built using Arduino IDE, with Blynk IoT integration as a medium for monitoring RGB values, diameter, category, and number of sorting results. The system was developed to classify tomatoes into five categories, namely large ripe, small ripe, large semi-ripe, small semi-ripe, and mixed unripe. Test results show that the sorting tool is capable of classifying ripeness levels based on RGB values and diameter with an average accuracy of 90% to 99% and an average error of less than 10%. Sorting data can be monitored remotely via Blynk, and the system can still operate offline without an internet connection. Thus, this tomato sorting tool is expected to facilitate the community, especially farmers, in the process of sorting tomatoes more accurately and efficiently.]]>
<![CDATA[A Smart Health Device to Measure Stress Levels Based on the Internet of Things Using the K-Nearest Neighbor Algorithm ]]>
<![CDATA[Tiara Ayunda]]>;
<![CDATA[Asrizal]]>;
<![CDATA[Leni Aziyus Fitri]]>
<![CDATA[ Research on Instrumentation Vol. 3 No. 1 (2026): Research on Instrumentation ]]>
Publisher : <![CDATA[RESSTECH ]]>
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DOI: 10.66926/rins.2026.1.32
<![CDATA[Mental health plays an important role in daily life. However, many factors can affect mental health, one of which is stress. Students are one group that is prone to stress. Academic stress is common among students. Currently, physiological stress screening devices are available, but most of them still work separately and are quite expensive. Therefore, this study aims to design an IoT-based stress detection device with a KNN algorithm that can measure physiological symptoms to detect stress levels in a practical and economical manner. This research is a type of engineering research, which involves the process of designing hardware and software for the system in an IoT-based stress level detection tool. The tool is designed to measure three physiological parameters, namely skin conductance, heart rate, and body temperature. Sensor data is processed using the KNN algorithm to classify stress levels into four categories, namely normal, mild, moderate, and severe. The results are displayed on an OLED and ThingSpeak platform so that they can be accessed remotely through IoT integration. Testing was carried out by collecting stress condition data from several subjects. The test results show that the device has an average accuracy and precision value of 83.33% to 99.82%. In addition, the average prediction computation time produced by the system was only 0.44 seconds, this computation time falls within an acceptable range for real-time applications. Thus, this stress level detection tool is expected to be an alternative solution and facilitate remote condition monitoring through the IoT feature.]]>
<![CDATA[Design and Implementation of a Hybrid Voice- and IoT-Based Smart Home Control System Using Local Speech Processing to Reduce Cloud Dependency ]]>
<![CDATA[Sukma Maksum]]>;
<![CDATA[Yulkifli]]>;
<![CDATA[Mona Berlian Sari]]>
<![CDATA[ Research on Instrumentation Vol. 3 No. 1 (2026): Research on Instrumentation ]]>
Publisher : <![CDATA[RESSTECH ]]>
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DOI: 10.66926/rins.2026.1.49
<![CDATA[Electrical devices are an important part of modern life. However, forgetting to turn off electrical appliances is still one of the causes of house fires in many areas. This research aims to determine the performance and design specifications of a home electrical appliance control system using a voice recognition sensor based on the Internet of Things (IoT). The research method used is an engineering method with several steps, including problem identification, conceptual design, system design, detailed design, prototype building, and system testing. The system is built using an Arduino Uno microcontroller, ESP32 module, voice recognition sensor, and relay module, which are connected to the Blynk application as a user interface for real-time communication. The system has two modes: voice control mode and manual control mode. In voice control mode, devices work based on voice commands from the user. In manual mode, users can control and monitor devices remotely through the Blynk application using a switch. The test results show that the system achieved an accuracy of 90% and demonstrated good consistency under controlled testing conditions. Furthermore, the system operates effectively and has demonstrated a high level of functional success during testing. These results show that the IoT-based control system using a voice recognition sensor works well and is reliable for controlling home electrical appliances.]]>
