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Jurnal ULTIMA Computing
Published by Universitas Multimedia Nusantara
ISSN : 23553286     EISSN : 25494007     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering
urnal ULTIMA Computing merupakan Jurnal Program Studi Sistem Komputer Universitas Multimedia Nusantara yang menyajikan artikel-artikel penelitian ilmiah dalam bidang Sistem Komputer serta isu-isu teoritis dan praktis yang terkini, mencakup komputasi, organisasi dan arsitektur komputer, programming, embedded system, sistem operasi, jaringan dan internet, integrasi sistem, serta topik lainnya di bidang Sistem Komputer. Jurnal ULTIMA Computing terbit secara berkala dua kali dalam setahun(Juni dan Desember) dan dikelola oleh Program Studi Sistem Komputer Universitas Multimedia Nusantara bekerjasama dengan UMN Press.
Arjuna Subject : -
Articles 150 Documents
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Field Assessment for Initial Preparation of Net Zero Building Certification for The Universitas Multimedia Nusantara (UMN) Building: A Case Study On Visual Comfort in C and D Tower Pranata, Nicholas; Salehuddin, Muhammad
ULTIMA Computing Vol 16 No 1 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i1.3609

Abstract

Ensuring optimal physical comfort, the need for a comprehensive evaluation of the performance of building systems was established. This investigation endeavors to meticulously scrutinize illuminance and light power density metrics across distinct temporal segments (morning, noon, afternoon, and night), as well as the dynamism of daylighting and artificial lighting presence within Tower C and D of Universitas Multimedia Nusantara (UMN). Noteworthy for their incorporation of double skin façades, these edifices serve as focal points of inquiry. The empirical findings reveal that illuminance levels within classrooms and offices, irrespective of natural or artificial lighting, consistently fall short of the prescribed 350 lux threshold based on SNI across most floor levels. The efficacy of the double skin façade manifests in a discernible attenuation, diminishing illuminance ingress to the building by approximately 50%, and precipitously by up to 90% about window fixtures. Furthermore, the analysis of light power density underscores an energy efficiency quotient hovering around 60%. These empirical insights are intended to serve as a foundational resource for guiding the initiation of Net Zero Healthy Greenship certification endeavors.
Modeling and Simulation of 4-DOF RRPR Manipulator Robot Using MATLAB Permadi, Tesya; Ath Thahirah Al Azhima, Silmi; Al Qibtya, Mariya; Arief Hakim, Nurul Fahmi
ULTIMA Computing Vol 16 No 1 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i1.3628

Abstract

In recent decades, the rapid development of robotic technology has increased the demand for efficient and affordable robots, especially in the manufacturing industry. One type of robot that is commonly used is the robotic arm, which is capable of performing complex tasks with high precision and speed. This research focuses on the modeling and simulation of a 4-DOF RRPR robot manipulator using MATLAB software, including the SimScape Multibody Toolbox and Robotic System Toolbox. This study investigates various aspects of robot performance, such as joint angles, end-effector coordinates, and robot dynamics. With an emphasis on simulation, this research aims to accelerate the development of robotic technology and minimize the risks associated with physical implementation in the field. The simulation results provide valuable insights for improving the efficiency, precision, and reliability of robot manipulators in various applications. Furthermore, this research suggests future research directions, such as the exploration of advanced control systems to dynamically compensate for disturbances and the investigation of robots with higher degrees of freedom for more adaptive technology in challenging operational conditions.
One-Phase Smart Switch using OpenCV Hand Gesture Recognition Fauzan, Mochamad Rizal; Khairi, Saiqa Fatur; Kaniarudi, Neneng Puspita; Ath Thahirah Al Azhima, Silmi; Arief Hakim, Nurul Fahmi; Kustiawan, Iwan; Al Qibtya, Mariya; Elvyanti, Siscka
ULTIMA Computing Vol 16 No 1 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i1.3633

Abstract

The need for simplicity in various activities encourages further technological development. One of them is a system to turn lights on and off with just a hand gesture. This hand gesture-based One-phase smart switch uses OpenCV, Arduino Nano, relays, and webcam cameras to recognize hand gestures. Static finger movements are used as buttons to turn on the lights. The results show that the algorithm used has high reliability with a precision score of 0.90, sensitivity of 0.90, accuracy of 0.96, and F1-score of 0.90. The accuracy of the system is affected by light intensity, distance, and hand tilt angle. At a light intensity of 70 LUX, the accuracy reaches 100%, while at 40 LUX the accuracy ranges from 98-99%. A distance of 30-60 cm gave the best accuracy of 100%, but decreased at longer distances. A hand tilt of 0° gives 100% accuracy, while at an angle of 60° the accuracy drops significantly, especially for the fifth finger with 64% accuracy. The average response time of the light to finger movement is 0.133 seconds. This device can recognize a variety of finger patterns well, thus meeting the desired needs.
Liquid Petroleum Gas (LPG) Cylinder Leak Detection Tool Using MQ-2 Sensor Based on Internet of Things (IoT) Wicsksono, Hartawan Alief; Syahda, Rizky Oriza; Syahid, Nur; Sary, Indri Purwita
ULTIMA Computing Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3658

Abstract

The widespread use of LPG gas cylinders brings the risk of gas leaks that can cause serious hazards, including fires and explosions. Therefore, an effective system is needed to detect gas leaks and provide early warnings to users. This study aims to develop an LPG gas cylinder leak detection device using an MQ-2 sensor based on the Internet of Things (IoT). The system consists of an MQ-2 sensor capable of detecting LPG gas, a microcontroller module for data processing, and an IoT communication module to send alerts to user devices via the internet. When the MQ-2 sensor detects a gas concentration that exceeds the predetermined threshold, the system sends an alert in the form of a notification to the user's mobile application. Additionally, the system is equipped with an audible alarm for direct on-site warnings. Test results indicate that this system can detect gas leaks with high accuracy and send alerts promptly. The implementation of IoT technology allows for real-time monitoring and handling of gas leaks, thereby enhancing the safety of LPG gas cylinder users. Thus, this leak detection device is expected to reduce the risk of accidents due to gas leaks and provide a sense of security for users.
Analysis of Noise Removal Performance in Speech Signals through Comparison of Median Filter, Low FIR Filter, and Butterworth Filter: Simulation and Evaluation: Median filter; FIR low filter; Butterworth filter; noise removal; signal noise; Mean Squared Error (MSE); Signal-to-Noise Ratio (SNR);simulation; evaluation Putri, Nurulita Purnama; ., Martarizal
ULTIMA Computing Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3678

Abstract

This research aims to analyze the performance of three types of filters, namely median filters, low FIR filters, and Butterworth filters, in eliminating noise in sound signals. Evaluation is carried out through simulation and evaluation using the Mean Squared Error (MSE) and Signal-to-Noise Ratio (SNR) parameters. The simulation results show that the three filters are able to produce signal estimates that are close to the original signal with low MSE values. The median filter shows the best performance with an MSE of 0.015833 and the highest SNR of 51.6334 dB, indicating its ability to reduce noise without sacrificing signal clarity. FIR and Butterworth filters also provide good results, although with slightly lower levels of accuracy. In conclusion, median filters are the optimal choice for noise removal in speech signals, while FIR and Butterworth filters remain good alternatives depending on application requirements. Further research and practical testing are needed for validation in real-world situations
Air Quality Monitoring System Design Based on Wireless Sensor Network Integrated with the Internet of Things Budiawan, Irvan; Wigianto, Danu Febri; Wicaksono, Bagus; Hakim, Arif Rohman
ULTIMA Computing Vol 16 No 1 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i1.3694

Abstract

Government and officials set rules to keep the air clean and healthy. To accommodate this, an efficient air quality monitoring system is required. Real-time monitoring is crucial for observing air quality. This allows for immediate action if air quality declines. However, current systems often rely on just one measurement point, risking inaccurate results due to rapid pollutant dispersion. To overcome this problem, researchers propose designing an air quality monitoring system based on a wireless sensor network. Sensor nodes will be installed at various points within the area to be monitored, forming a connected sensor network using the ESP-Now protocol. The data obtained from each node will be sent to the base station, then the data will be transmitted via the Message Queuing Telemetry Transport (MQTT) protocol using the internet network. Thus, this design produces a wireless sensor network that is integrated with the internet of things (IoT). The advantages of the IoT system include ease of data storage and accessibility that can be accessed from anywhere as long as it is connected to the internet and has appropriate authorization.
Gross Error Detection and Data Correction in IIoT-Based Data Center Cooling System Hamid, Abdul; Budi, Eko Mursito; Ekawati, Estiyanti
ULTIMA Computing Vol 16 No 1 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i1.3695

Abstract

A data center always require a proper cooling system. This research study a data center with water based cooling system that consists of two chillers and two in-rack coolers. To control the system, an Industrial Internet of Things (IIoT) infrastructures has been deployed. It able to monitors real-time data from various sensors such as temperature (T), pressure (P), water flow (Q). The data were supposed to be used for optimization. However, early assessment showed that there were discrepancies between the sensors. Therefore, data reconciliation method is essential to get the valid data from the sensors. This paper discusses the implementation of gross error detection and correction by using least square method and bias compensation.
Development of Cavendish Banana Maturity Detection and Sorting System Using Open Source Computer Vision and Loadcell Sensor Rochman, Achmad Fatchur; Sulistiyowati, Indah; Jamaaluddin, Jamaaluddin; Anshory, Izza
ULTIMA Computing Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3869

Abstract

This research aims to develop a system of detecting the maturity and sorting of cavendish bananas using Open Source Computer Vision (OpenCV) and also assisted by a loadcell sensor. The problem experienced at this time is that fruit sorting is still manual which is less efficient and inaccurate in distinguishing banana maturity based on the color of the skin. This is because the human eye is sensitive to changes in lighting and fatigue. This designed system will use webcam for image processing and loadcell for fruit weight measurement, controlled by Arduino Uno microcontroller. While the algorithm used to determine the color of the ripeness of the banana fruit itself is HSV. The test results show an average weight error of 0.08% for ripe bananas, 0.71& for unripe bananas, while the color detection produces an accuracy of 47.34% on average in bright lighting conditions. In conclusion, this system is successful in improving sorting efficiency with adequate accuracy results, but further development is needed so that the accuracy level increases.
Air Filtration System Utilizing Biomimetic Technology and IoT for Air Quality Improvement Fauzan, Mochamad Rizal; Al Azhima, Silmi Ath Thahirah; Pramudita, Resa; Hakim, Dadang Lukman; Rahmawati, Hanifah Indah; Azmi, Mutiara Nabila; Fauzi, Rafi Rahman; Somantri, Maman; Rahayu, Sri
ULTIMA Computing Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3871

Abstract

The "Hepix" smart air filtration system, developed with biomimetic and Internet of Things (IoT) technology, aims to address the urgent issue of poor indoor air quality, particularly in high-mobility urban areas. This system integrates advanced sensors (MQ135 and BME680) and biomimetic filtration inspired by leaf stomata to monitor and filter air pollutants. Tested across three locations”Cilame, Jatinangor, and Cibiru”the system achieved an approximate 24.4% reduction in pollutant levels, as well as stable control of humidity and air pressure. Real-time data is continuously monitored through a mobile and web interface, supported by Google Assistant integration for voice commands. The results demonstrate that "Hepix" effectively improves air quality, offering a practical solution for healthier indoor environments in urban areas.
Microscopic Sand Image Classification Using Convolutional Neural Networks Redja, Christie; Pranoto, Wati Asriningsih; Wulandari, Meirista
ULTIMA Computing Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3907

Abstract

Abstract” This research paper reviews the use of Convolutional Neural Networks (CNNs) to categorize diverse sand type using microscopic images, with an objective of improving quality control in construction materials. The paper compares three CNN architectures”LeNet-5, Inception v3, and ResNet50”for discriminating between specific sand categories, such as two river sands (Cipongkor and Citarum) and three types of silica sand (brown, cream, and white). Each model was trained and tested on different dataset splits, with images pre-processed to highlight specific microscopic properties. To achieve a thorough comparison, each model's performance was measured using a variety of measures such as F1-score, accuracy, recall, and precision. These measurements enabled a comprehensive evaluation of how accurately and reliably each CNN model categorized the various sand types. ResNet50 consistently delivered the highest accuracy, achieving perfect classification in some instances, showcasing its effectiveness in capturing fine details in sand textures. These results highlight the potential of CNN-based approaches for precise and automated sand classification, which supports increased quality assurance in construction and related areas. Index Terms” Convolutional Neural Network (CNN); sand classification; LeNet-5; Inception v3; ResNet50

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