Muhammad Syafrudin

Sejong University | sejong · Department of Artificial Intelligence

Currently, the manufacturing industry is experiencing a data-driven revolution. There are multiple processes in the manufacturing industry and will eventually generate a large amount of data. Collecting, analyzing and storing a large amount of data are one of key elements of the smart manufacturing industry. To ensure that all processes within the...

With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as Internet of Things (IoT)-based sensors can be considered a solution to provide efficient monitoring of the manufacturing process. In this study, a real-t...

Maintaining product quality is essential for smart factories, hence detecting abnormal events in assembly line is important for timely decision-making. This study proposes an affordable fast early warning system based on edge computing to detect abnormal events during assembly line. The proposed model obtains environmental data from various sensors...

Early diseases prediction plays an important role for improving healthcare quality and can help individuals avoid dangerous health situations before it is too late. This paper proposes a disease prediction model (DPM) to provide an early prediction for type 2 diabetes and hypertension based on individual’s risk factors data. The proposed DPM consis...

Detecting self-care problems is one of important and challenging issues for occupational therapists, since it requires a complex and time-consuming process. Machine learning algorithms have been recently applied to overcome this issue. In this study, we propose a self-care prediction model called GA-XGBoost, which combines genetic algorithms (GAs)...

The implementation of Industry 4.0 technology has developed rapidly. Despite its development, Indonesia is still nascent and requires some implementation monitoring in its priority industries. This study aims to design a system for assessing the readiness of implementing Industry 4.0 in priority manufacturing industries in Indonesia. A Fuzzy Infere...

Flood disasters, a natural hazard throughout human history, have caused significant damage to human safety and infrastructure. This paper presents a systematic study using databases from Springer Link, Science Direct, JSTOR, and Web of Science. The study employs the PRISMA report analysis method to examine 11 flood disaster case studies between 201...

A brain tumor is essentially a collection of aberrant tissues, so it is crucial to classify tumors of the brain using MRI before beginning therapy. Tumor segmentation and classification from brain MRI scans using machine learning techniques are widely recognized as challenging and important tasks. The potential applications of machine learning in d...

Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) are worldwide chronic diseases that have strong relationships with one another and commonly exist together. Type 2 diabetes is considered one of the risk factors for NAFLD, so its occurrence in people with NAFLD is highly likely. As the high and increasing number of T2D and NAFLD,...

Video surveillance and activity monitoring are the practical real-time applications of Human Action Recognition (HAR). A fusion of several Convolutional Neural Network (CNN) architectures has been widely used for effective HAR and achieved impressive results. Feature fusion of multiple pre-trained models also extracts redundant features due to the...

The accurate forecasting of energy consumption is essential for companies, primarily for planning energy procurement. An overestimated or underestimated forecasting value may lead to inefficient energy usage. Inefficient energy usage could also lead to financial consequences for the company, since it will generate a high cost of energy production....

In recent years, radio frequency identification (RFID) technology has been utilized to monitor product movements within a supply chain in real time. By utilizing RFID technology, the products can be tracked automatically in real-time. However, the RFID cannot detect the movement and direction of the tag. This study investigates the performance of m...

It is expected that the metaverse will be the next generation of the internet and its online activities and will serve as the foundation for a massive online business platform. Furthermore, it will alter people's behavior, which will have an impact on businesses' decisions to choose the metaverse as their primary business platform. Metaverse Appli...

Recently, the development of a rapid detection approach for glaucoma has been widely proposed to assist medical personnel in detecting glaucoma disease thanks to the outstanding performance of artificial intelligence. In several glaucoma detectors, cup-to-disc ratio (CDR) and disc damage likelihood scale (DDLS) play roles as the major objects that...

Detecting snow-covered solar panels is crucial as it allows us to remove snow using heating techniques more efficiently and restores the photovoltaic system to proper operation. This paper presents classification and detection performance analyses for snow-covered solar panel images. The classification analysis consists of two cases, and the detect...

The emergence of artificial intelligence (AI) and its derivative technologies, such as machine learning (ML) and deep learning (DL), heralds a new era of knowledge management (KM) presentation and discovery. KM necessitates ML for improved organisational experiences, particularly in making knowledge management more discoverable and shareable. Machi...

Companies are beginning to utilize the metaverse to broaden their service network and create new co-creation value for their clients. To better understand how the metaverse phenomena could impact corporate sustainability, investigative research should be conducted. In this chapter, the authors looked at the moral issues raised by businesses using m...

Abstract: Drought analysis via the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) is necessary for effective water resource management in Sarawak, Malaysia. Rainfall is the best indicator of a drought, but the temperature is also significant because it controls evaporation and condensation....

Multi-category vessel detection and classification based on satellite imagery attract a lot of attention due to their significant applications in the military and civilian domains. In this study, we generated a new Artificial-SAR-Vessel dataset based on the combination of the FUSAR-Ship dataset and the SimpleCopyPaste method. We further proposed a...

Businesses are starting to use the Metaverse to expand their service network and establish new value co-creation for customers. However, businesses may need to carefully assess the ethical implications of their data collection and utilisation procedures for business sustainability. This paper examines the ethical concerns surrounding the usage of t...

Predicting future glycemic events such as hypoglycemia, hyperglycemia, and normal for type 1 diabetes (T1D) remains a significant and challenging issue. In this study, an artificial neural network (ANN)-based model is proposed to predict the future glycemic events of T1D patients. We utilized five T1D patient datasets to build the models and predic...

Risk assessment and developing predictive models for diabetes prevention is considered an important task. Therefore, we proposed to analyze and provide a comprehensive analysis of the performance of diabetes screening scores for risk assessment and prediction in five populations: the Chinese, Japanese, Korean, US-PIMA Indian, and Trinidadian popula...

This research project aimed to provide an environmentally friendly method for the decolorization and biosorption of synthetic dye by utilizing fungi as biosorbents. The study was carried out by first growing the fungi in solid medium and then using the fungi as biosorbent to absorb dye in aqueous solution. In the first stage, screening experiments...

The analysis of influential machine parameters can be useful to plan and design a plastic injection molding process. However, current research in parameter analysis is mostly based on computer-aided engineering (CAE) or simulation which have been demonstrated to be inadequate for analyzing complex behavioral changes in the real injection molding pr...

Developing a prediction model from risk factors can provide an efficient method to recognize breast cancer. Machine learning (ML) algorithms have been applied to increase the efficiency of diagnosis at the early stage. This paper studies a support vector machine (SVM) combined with an extremely randomized trees classifier (extra-trees) to provide a...

Water is a vital resource to every living thing on the earth. Once the water is contaminated (physically, chemically, biologically, or radiologically), it brought negative impacts to the living thing. This paper provides a brief review of the characterization of biological pollutants in drinking water and their effects on human health. Some biologi...

Predicting future blood glucose (BG) values for diabetic patients, particularly for type 1 diabetes (T1D), remains an important and challenging issue. To overcome it, several well-known machine learning models have been used in recent years. Thus, a personalized model based by using random forest (RF) regression is implemented to forecast the futur...

Prediction of blood glucose (BG) values in type 1 diabetes (T1D) remains an essential and challenging issue. Recently, machine learning methods have been used to solve this problem. We present a forecasting model based on extreme gradient boosting (XGBoost) regression to estimate the BG value of T1D patients in this study. We developed the models u...

Accuracy improvement of classification model becomes main research objective in various fields. Selecting important features and removing outliers of a dataset are two effective solutions for improving model accuracy. Information Gain is one of the feature selection methods that can be considered as a solution for selecting important features of a...

The Fourth Industrial Revolution (4IR) offers optimum productivity and efficiency via automation, expert systems, and artificial intelligence. The Fourth Industrial Revolution deploys smart sensors, Cyber-Physical Systems (CPS), Internet of Things (IoT), Internet of Services (IoS), big data and analytics, Augmented Reality (AR), autonomous robots,...

An essay was used as an assessment to illustrate a certain way of thinking and attitude of a student. The essay demonstrates the student's utmost degree as an author with a cognitive and affective style. The study aimed to provide a simple description of the essay as an assessment and critical function in the Groundwater Contamination course of the...

The Baram River is one of the largest rivers in Sarawak, where many large industries, such as plywood, sawmills, shipyards, interisland ports, and other wood-based industries are located along the river. Microplastic contamination has become a widespread and growing concern worldwide because of the small sizes of microplastics and their presence in...

The ubiquitous problem of pesticide in aquatic environment are receiving worldwide concern as pesticide tends to accumulate in the body of the aquatic organism and sediment soil, posing health risks to the human. Many pesticide formulations had introduced due to the rapid growth in the global pesticide market result from the wide use of pesticides...

The Internet of Things (IoT)–based sensors together with smartphone can be utilized as personal health devices to gather vital signs data, so that current health condition of patient can be presented. In this study, we propose a health-care monitoring system by utilizing an IoT-based sensor device and prediction model, so that diabetes patients can...

Self-care classification for children with physical disability remains an important and challenging issue. It needs the support from occupational therapists to make decision. Data-driven decision making have been widely adopted to make decision based on the data with help of expert systems and machine learning algorithms. In this study, we develope...

Diabetes is the number one of major causes of death globally. Undetected and untreated diabetes causes serious issues and the individuals with diabetes are at high risk for complication. Thus, an early diabetes prediction is necessary to help the individuals preventing dangerous conditions at the early stage. This study proposed a prediction model...

Predicting future blood glucose (BG) levels for diabetic patients will help them avoid potentially critical health issues. We demonstrate the use of machine learning models to predict future blood glucose levels given a history of blood glucose values as the single input parameter. We propose an Artificial Neural Network (ANN) model with time-domai...

Nowadays, customer's health awareness is of extreme significance. Food can become contaminated at any point during production, preparation and distribution. Therefore, it is of key importance for the perishable food supply chain to monitor the food quality and safety. Traceability system offers complete food information and therefore, it guarantees...

Extracting information from individual risk factors provides an effective way to identify diabetes risk and associated complications, such as retinopathy, at an early stage. Deep learning and machine learning algorithms are being utilized to extract information from individual risk factors to improve early-stage diagnosis. This study proposes a dee...

Heart disease, one of the major causes of mortality worldwide, can be mitigated by early heart disease diagnosis. A clinical decision support system (CDSS) can be used to diagnose the subjects’ heart disease status earlier. This study proposes an effective heart disease prediction model (HDPM) for a CDSS which consists of Density-Based Spatial Clus...

Understanding customer shopping behavior in retail store is important to improve the customers' relationship with the retailer, which can help to lift the revenue of the business. However, compared to online store, the customer browsing activities in the retail store is difficult to be analysed. Therefore, in this study the customer shopping behavi...

Predicting future blood glucose (BG) level for diabetic patients will help them to avoid critical conditions in the future. This study proposed Extreme Gradient Boosting (XGBoost), an ensemble learning model to predict the future blood glucose value of diabetic patients. The clinical dataset of Type 1 Diabetes (T1D) patients was utilized and the pr...

Radio Frequency Identification (RFID) technology has significantly improved in the past few years and is presently sought for implementation in the identification and traceability of perishable food in the food sector to safeguard food safety and quality. It is currently considered a worthy successor to the barcode system and has significant advant...

The potential of Parkia speciosa peel (SBP) for removal of procion red mx-5B (PR) through the adsorption process was investigated. PR is a type of azo dye which is toxic to the environment especially in water. Sustainable adsorbents such as agricultural wastes have been promising to reduce the amount of pollution in wastewater due to their accessib...

Radio frequency identification (RFID) technology can be utilized to monitor tagged product movements and directions for the purpose of inventory management. It is important for RFID gate to identify the several RFID readings such as movement type and direction as well as the static tags (tags that accidentally read by the reader). In this study, ra...

Radio frequency identification (RFID) is an automated identification technology that can be utilized to monitor product movements within a supply chain in real-time. However, one problem that occurs during RFID data capturing is false positives (i.e., tags that are accidentally detected by the reader but not of interest to the business process). Th...

Purpose The purpose of this paper is to propose customer behavior analysis based on real-time data processing and association rule for digital signage-based online store (DSOS). The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is utilized to handle the vast amount of customer behavior data. Design...

Current technology such as Bluetooth Low Energy (BLE) provides an efficient way for Real-Time Location System (RTLS). This study proposes a BLE-based Real-Time Location System that utilizes Smartphone and NoSQL database as gateway and data storage respectively. Firstly, we develop a smartphone-based tracking app to gather the location of employees....

As the risk of diseases diabetes and hypertension increases, machine learning algorithms are being utilized to improve early stage diagnosis. This study proposes a Hybrid Prediction Model (HPM), which can provide early prediction of type 2 diabetes (T2D) and hypertension based on input risk-factors from individuals. The proposed HPM consists of Den...

Current technology provides an efficient way of monitoring the personal health of individuals. Bluetooth Low Energy (BLE)-based sensors can be considered as a solution for monitoring personal vital signs data. In this study, we propose a personalized healthcare monitoring system by utilizing a BLE-based sensor device, real-time data processing, and...

Now days, customer’s health awareness is of extreme significance. Food can become contaminated at any point during production, distribution and preparation. Therefore, it is of key importance for the perishable food supply chain to monitor the food quality and safety. Traceability system offers complete food information and therefore, it guarantees...

To make manufacturers more competitive, there is a need to integrate advanced computing and cyber-physical systems to take advantage of the current technologies. With the advent of smart sensors such as IoT technologies (1), collecting data has become a simple task, but the question remains if these devices or data provide the right information for...

Smart factory is quickly becoming the new reality in the market, and every innovative manufacturer must embrace it to stay competitive. To achieve manufacturing innovation in smart factory, manufacturers will have to invest in improving and or utilizing Internet of Things (IoT) to enable real-time data on their processes and their condition – for e...

Since customer attention is increasing due to growing customer health awareness, it is important for the perishable food supply chain to monitor food quality and safety. This study proposes a real-time monitoring system that utilizes smartphone-based sensors and a big data platform. Firstly, we develop a smartphone-based sensor to gather temperatur...

A carsharing service can be seen as a transport alternative between private and public transport that enables a group of people to share vehicles based at certain stations. The advanced carsharing service, one-way carsharing, enables customers to return the car to another station. However, one-way implementation generates an imbalanced distribution...

In the future, one of the key essential functionality of smart factory is reconfigurable manufacturing. Collecting, analyzing, and monitoring large amounts of sensor data are becoming a key enable technology to implement reconfigurable manufacturing. These day, the manufacturing industry is in the midst of a data-driven revolutionary, which means s...

This paper proposes an eye state detection system using Haar Cascade Classifier and Circular Hough Transform. Our proposed system first detects the face and then the eyes using Haar Cascade Classifiers, which differentiate between opened and closed eyes. Circular Hough Transform (CHT) is used to detect the circular shape of the eye and make sure th...

The reconfigurable manufacturing is an essential functionality of smart factories in the future. In order to implement such reconfigurable manufacturing; collecting, analyzing, and monitoring large amounts of sensor data are becoming a key enable technology. And nowadays, the manufacturing industry is in the midst of a data-driven revolution, which...