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All Journal Sinergi JOIV : International Journal on Informatics Visualization
Rizman, Zairi Ismael
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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MLP-NARX Bitcoin Price Prediction Model Integrating System Identification Modelling Principles Farhan Nasarudin, Muhammad Nazrin; Yassin, Ihsan Mohd; Megat Ali, Megat Syahirul Amin; Adzhar Mahmood, Mohd Khairil; Baharom, Rahimi; Rizman, Zairi Ismael
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.943

Abstract

Bitcoin is a decentralized digital currency that enables people to exchange value without requiring a third-party intermediary. Due to its many advantages, it has received much interest from institutional and individual investors. Despite its meteoric increase, the price of Bitcoin extremely volatile asset class as it purely relies on supply and demand. This presents an interesting opportunity to create a forecasting model. However, many research papers in this area does not analyse the residuals as part of the forecasting resulting in potentially biased models. In this paper, we demonstrate System Identification (SI) residual analysis techniques to the analysis of our forecasting model. The Multi-Layer Perceptron (MLP) Nonlinear Autoregressive with Exogeneous Inputs (NARX) uses historical price data and several technical indicators to predict the future price movements of Bitcoin. The Particle Swarm Optimization (PSO) algorithm was used to find optimal parameters for the model. The model was able to predict one day ahead price in the prediction test. The model has successfully captured the dynamics of the data through the tests performed on residuals. It is also proving the randomness of residuals, albeit some minor violations.
Real-time Unmanned Surface Robot (USR) for river quality monitoring systemm Mohd Aras, Mohd Shahrieel; Ponusamy, Pavitrah; Md Nawawi, Mohamad Riduwan; Zohedi, Fauzal Naim; Bahar, Mohd Bazli; Abdullah, Lokman; Khamis, Alias; Rizman, Zairi Ismael
SINERGI Vol 30, No 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2026.1.001

Abstract

A real-time Unmanned Surface Robot (USR) for river water quality monitoring system is a technology that employs a small autonomous boat outfitted with sensors and other monitoring equipment to gather and transmit data on various water quality parameters like pH, temperature and total dissolved solids sensors in rivers and other bodies of water. The USR can traverse the river, gather information or data at specific points or designated locations, as well as continuously monitor a specific stretch of river at all times. The data or information was sent in real time to a central monitoring station, where it was analyzed and used to identify potential water quality problems. Initially, the USR was designed using SolidWorks software, and its structural performance was the main focus of the investigation and examination of the design.  This USR was then created and manufactured.  The entire USR system could help detect and mitigate pollution and other environmental problems, as well as offer useful information for managing water resources. Next, to determine the overall performance of the USR, five experiments and autopilot accuracy tests were performed. Finally, this study also verified and validated the accuracy of water quality monitoring sensors. 
Performance Analysis of a Micro Underwater Remotely Operated Vehicle (ROV) Zohedi, Fauzal Naim; Chuan, Chan Yeow; Mohd Aras, Mohd Shahrieel; Khamis, Alias; Rizman, Zairi Ismael
SINERGI Vol 30, No 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2026.1.002

Abstract

Underwater Remote Operated Vehicle (ROV) is a tethered marine robot that are widely employed for scientific and commercial applications. Several industries are working on underwater robots to increase the productivity, monitoring and surveillance especially in the petroleum and gas industries. These operations are often performed by human divers; however, the underwater environment poses hazards and pressure-related limits, making them costly and risky. As a result, ROVs have been designed to replace divers themselves. It is a tethered underwater robot that the operator controls manually using a PS2 controller. This project is to design and develop a micro underwater ROV for monitoring applications. The ROV are designed to withstand pressure underwater by selection of suitable material for its frame and other components will be equipped including pressure/depth sensor, MPU6050 IMU sensor and waterproof endoscope camera. Standard testing procedures are employed to assess the ROV's performance in buoyancy and control efficiency tests for the propulsion system in real environment, including laboratory pool. The developed ROV prototype shows promising performance with achieved 90% negative buoyancy is crucial for the ROV to perform effective submerge and raise operations and also with stable velocity and acceleration in forward, backward, and submerging. The steering tests highlighted that the ROV is more flexible and faster in maneuvering concerning turning performance as the horizontal thrusters’ configurations are positioned at 45° at the back of the ROV. The outcomes of this project are anticipated to bring substantial advantages to industries associated with underwater applications.
Co-Authors Abdullah, Lokman Adzhar Mahmood, Mohd Khairil Alias Khamis, Alias Bahar, Mohd Bazli Baharom, Rahimi Chuan, Chan Yeow Farhan Nasarudin, Muhammad Nazrin Md Nawawi, Mohamad Riduwan Megat Syahirul Amin Megat Ali Mohd Shahrieel Mohd Aras, Mohd Shahrieel Ponusamy, Pavitrah Yassin, Ihsan Mohd Zohedi, Fauzal Naim