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All Journal IAES International Journal of Robotics and Automation (IJRA) Faktor Exacta Jurnal Infomedia Journal of Renewable Energy, Electrical, and Computer Engineering Jurnal Energi Elektrik
Misriana Misriana
Politeknik Negeri Lhokseumawe
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Implementation of Augmented Reality at Interactive Food Menu Using the Speed Up Robust Features (SURF) Algorithm Ahmad Ihsan; Liza Fitria; Mursyidah Mursyidah; Herri Mahyar; Suryati Suryati; Misriana Misriana
Jurnal Infomedia: Teknik Informatika, Multimedia, dan Jaringan Vol 8, No 1 (2023): Jurnal Infomedia
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jim.v8i1.4074

Abstract

— Promotion is an attempt to notify or offer a product or service with the aim of attracting potential customers to buy or consume it, with the promotion, producers or distributors expect an increase in sales figures. In this study researchers used Augmented Reality technology for interactive media promotion of food menus by adding 3D multimedia elements. The method used in this study uses the Natural Feature Tracking method with the Speed Up Robust Features (SURF) algorithm, which detects local features in marker images that are resistant to rotation, scale and blurring. The results showed that the keypoint functions to render 3D objects. Search for keypoints is interrupted due to distance, light intensity and slope of the marker. Test results to see the distance between the camera and the marker as far as 60 cm. Medium light intensity that can detect markers, the average time of object speed can be displayed is 3.026 seconds and the marker slope limit is 30 °. This is because the keypoint readings at the position and time limit from keypoint readings clearly, keypoint readings clearly produce 3D objects can be displayed. This research uses the Android platform as the foundation of this Augmented Reality technology application. So that by displaying 3D food menu items in restaurants it is expected to be a means of promotion to attract consumers.
SCADA system in water storage tanks with NI vision LabVIEW Kartika Kartika; Misriana Misriana; M. Fathan Naqi; Asran Asran; Misbahul Jannah; Arnawan Hasibuan; Suryati Suryati
IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v14i3.pp381-392

Abstract

Advances in technology have driven the need for efficient water management systems. This study presents a SCADA-based water management system that integrates LabVIEW and Arduino to monitor and regulate water levels and flow rates in a storage tank. The system uses an HC-SRF04 ultrasonic sensor for water level measurement with 99.77% accuracy and an HX710 pressure sensor, which achieves 98.54% accuracy. The LabVIEW interface displays real-time data, giving users an intuitive view of system performance. A proportional integral derivative (PID) algorithm optimizes the water pump through pulse width modulation (PWM), achieving water flow rate control. The Ziegler-Nichols method tunes the PID parameters to Kp = 16.59, Ti = 1.102, and Td = 0.2755. This tuning ensures the system maintains a consistent target flow rate of 4 liters per minute (L/min) with minimal variation. Initial testing showed a 2.5% overshoot but stabilized at the desired flow rate within 10 seconds, indicating effective control. This SCADA system reduces water and energy waste by enabling continuous real-time monitoring and control. The system provides accurate data through a LabVIEW interface, ensuring effective and informed operational decisions. This robust solution supports efficient water management for industrial and environmental applications, contributing to sustainability and resource optimization.
Implementation of Linear Regression Method in Light Strength Measurement Using GY1750BH Sensor Kartika Kartika; Misbahul Jannah; Rizki Aulia; Misriana Misriana
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.26062

Abstract

Developments in light sensor technology have made it possible to achieve better measurement accuracy. The GY1750BH sensor, for example, is known for its ability to detect changes in light with high sensitivity. While this sensor has many advantages, the accuracy of the results depends highly on the calibration method. Without proper calibration, measurement data can suffer from biases detrimental to the applications that rely on it. Linear regression methods can extract the mathematical relationship between the sensor output and light intensity in light sensors. In light sensor calibration, linear regression helps determine the relationship between the sensor-generated signal (e.g., voltage or current) and the measured light intensity. Thus, we can mathematically map the sensor's response to changes in light intensity, which is used for measurement correction to get closer to the actual value. Implementing linear regression in the GY1750BH sensor is expected to contribute significantly to improving the measurement accuracy of this sensor. By modeling the sensor's response to the actual light intensity, the data generated is expected to be more consistent and accurate so that it can be used in applications that require high accuracy. The results of this study are light intensity measurement with the application of linear regression on the GY 1750 BH sensor, which is more stable, and the resulting comparison is close to the measurement results using measuring instruments. The error produced before using linear regression is 1.2%, and when using linear regression on the GY 1750 BH sensor, it becomes 0.54%.
Matlab Simulation Using Kalman Filter Algorithm to Reduce Noise in Voice Signals Fitra Permana Putra; Kartika Kartika; Nanda Sitti Nurfebruary; Misriana Misriana; Kerimzade G. S; Ramdhan Halid Siregar
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 4 No. 1 (2024): March 2024
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v4i1.13687

Abstract

Sound signals polluted by noise are a common problem in various audio applications, including communication, sound processing, and audio recording. In this article, proposes the use of Kalman Filter algorithm as an effective method to reduce noise in speech signals. Simulations are performed using Matlab software to implement the Kalman Filter algorithm on noise polluted voice signals. The study includes several important steps, including the input of noise-polluted speech signals and the implementation of the Kalman Filter to clean the signals. Simulation results are measured using commonly used audio quality metrics, such as Signal-to-Noise Ratio (SNR) and Mean Square Error (MSE), to evaluate the effectiveness of the algorithm. The results from the simulations show that the use of the Kalman Filter algorithm significantly improves the quality of noise-contaminated speech signals. These results indicate that this algorithm can be a potential solution to the problem of noise reduction in audio applications. In addition, the implementation in the Matlab environment allows for easy testing and adaptation of this algorithm for different types of audio applications. This research makes a positive contribution to the development of more efficient noise reduction techniques in speech signal processing, focusing on the use of the Kalman Filter algorithm and its implementation using Matlab software. The implications of this research can be potentially beneficial in improving the quality of sound signals in various audio application contexts.
Sistem pengingat jadwal minum obat bagi penderita epilepsi ternotifikasi telegram Kautsar; Kartika Kartika; Jannah; Misriana Misriana
Jurnal Energi Elektrik Vol. 14 No. 2 (2025): Jurnal Energi Elektrik
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jee.v14i2.26033

Abstract

Medication adherence is a vital factor in the management of epilepsy patients to prevent recurrent seizures. However, manual monitoring methods are often ineffective and prone to human error. This study aims to design an automated medication reminder and leftover monitor system based on the Internet of Things (IoT). The system is built using a Load Cell sensor to detect weight changes in a syrup bottle or medication container, along with an ESP8266 microcontroller integrated with the Telegram API as a notification interface. The research methods include hardware design, development of a weight reduction detection algorithm, and sensor accuracy testing. Calibration testing results show that the system is capable of detecting medication intake activity based on the weight difference before and after consumption. From a series of tests, an average reading difference (error) of 3.9 grams compared to the original weight was obtained. This system successfully sends reminder notifications and alerts if the medication is not consumed, thus offering an effective remote monitoring solution for patient caregivers.
Co-Authors Ahmad Ihsan Arnawan Hasibuan Asran Asran Fitra Permana Putra Herri Mahyar Jannah Kartika Kartika Kautsar Kerimzade G. S Liza Fitria M. Fathan Naqi Misbahul Jannah Mursyidah . Nanda Sitti Nurfebruary Ramdhan Halid Siregar Rizki Aulia Suryati Suryati