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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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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 : Jurnal Sistem Komputer 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 : Jurnal Sistem Komputer 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.
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 : Jurnal Sistem Komputer 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 Putri, Nurulita Purnama; ., Martarizal
Ultima Computing : Jurnal Sistem Komputer 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
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 : Jurnal Sistem Komputer 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 : Jurnal Sistem Komputer 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 : Jurnal Sistem Komputer 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
A Real-Time Space Availability Detection in Smart Parking Systems Using Infrared Sensor and Microcontroller Atmega 328p Putri, Fidel Lusiana
ULTIMA Computing Vol 17 No 1 (2025): 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.v17i1.3802

Abstract

In the growing digital era, vehicles have become a staple for daily mobility. This poses a significant parking problem, especially in urban areas with limited parking spaces. The search for parking spaces often leads to congestion, air pollution, fuel waste, and frustration for drivers. This research aims to develop an Internet of Things (IoT) based smart parking system using infrared sensors and an ATmega328p microcontroller to detect the availability of parking slots in real time. This system provides information to the driver through an LCD screen installed at the entrance of the parking area. The methods used in this research are direct testing and tool prototyping. The results show that this smart parking system can detect the availability of parking slots with high accuracy and provide real-time information to drivers, thereby reducing congestion and improving parking management efficiency.
Long Term Prediction of Extreme Weather with Long Short Term Memory (LSTM) Model: Effect of Climate Change Putri, Nurulita Purnama; Harmoko Saputro, Adhi
ULTIMA Computing Vol 17 No 1 (2025): 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.v17i1.4022

Abstract

Increasingly intense climate change has increased the frequency and intensity of extreme weather, making weather prediction critical for mitigation and adaptation. This research focuses on long-term prediction of extreme weather using the Long ShortTerm Memory (LSTM) model, as well as evaluating the influence of climate change on prediction accuracy. In this study, historical weather data is used to train and test an LSTM model combined with a RandomForestClassifier. Analysis was carried out using the Mean Squared Error (MSE) evaluation technique for 50 epochs and 8 trials at various threshold values (26, 29, 32, 35, 38, 41, 44, 47). The research results show that the LSTM model is able to predict extreme weather with an accuracy of up to 100%. Apart from that, this research also predicts daily rainfall in Bandung City through the process of data collection, preprocessing, normalization and evaluation using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). This model produces an RMSE of 4.24 and MAE value of 2.72%, indicating quite good predictions. It is hoped that this research can make a significant contribution to the field of meteorology and can be developed further by adding parameters or other methods to improve the quality of predictions. Suggestions are given to increase the amount of data used to obtain better prediction results in the future.
Design of Greenhouse Prototype Controller and Monitor on Green Mustard Plants Rozzaq, Ahmad Nur; Harijanto, Alex; Maryani
ULTIMA Computing Vol 17 No 1 (2025): 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.v17i1.4054

Abstract

The prototype greenhouse control and monitoring system for green mustard plants is expected to facilitate greenhouse farmers in farming activities. Control and monitoring are carried out on the intensity of incoming sunlight, greenhouse temperature, greenhouse humidity, and soil moisture. The control and monitoring system is carried out by ESP32, BH1750 sensor, DHT22 sensor, and soil moisture sensor. The control process is assisted by an actuator that will turn on and off automatically according to the value limits entered by the greenhouse owner and the readings from the sensor. The control and monitoring device uses Blynk IoT which is connected to an internet of things (IoT) connection. The purpose of this study is to describe the design process of the controller and monitor of the prototype greenhouse for green mustard plants based on the internet of things (IoT) and to find out the results of the controller and monitor of sunlight intensity, air temperature, air humidity, and soil moisture on green mustard plants in the greenhouse. This study uses quantitative descriptive research. The results of this study are the realization of a prototype greenhouse control and monitor for green mustard plants based on the internet of things (IoT) with the main control system being ESP32. The results of the calibration values of the 4 sensor variables are very satisfactory and can be considered as valid tools. The R_square values of the 4 sensor calibrations, namely the BH1750 light sensor, DHT22_1 temperature sensor, DHT22_2 temperature sensor, DHT22_1 humidity sensor, DHT22_2 humidity sensor, and soil moisture sensor are respectively 0.9936; 0.9689; 0.9665; 0.9412; 0.9451; 0.9574.

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