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Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning
No full textThe automated system for detecting cyber bot attacks in 5G networks relies on cloud servers
to store data, facilitating the global access necessary for online transactions and services, but
points to the rise of cybercrime with information security flaws and human stealth Attackers
known as "Botmasters" spread Trojan malware to grow bots on the network causing DDOS
attacks. Botnets are compromised computer networks controlled by attackers that are visible
for this reason. Machine learning algorithms have been proposed to identify bot networks with
a focus on extracting features from high-dimensional datasets. However, the literature pays
little attention to selection methods, which are crucial for developing effective machinelearning
models
Hygiene Factors and Motivation Factors towards Job Satisfaction in Malaysia Healthcare Sector
No full textHealthcare professionals' job satisfaction is a measure that should be included in quality
improvement programmes for healthcare services. It significantly affects how productive and
effective healthcare facilities are. The most valuable resource in the healthcare system is its human
resources, which also serve as the driving force behind the delivery of sustainable services (Saari
and Judge, 2004). The effectiveness of health services is impacted by employee turnover and
absenteeism, which are both linked to poorer job satisfaction among these competent health
professionals. The WHO has determined that the threshold of the health workforce density is
currently below expectations in several developing nations. The goal of this study is to have a
better awareness and knowledge of the motivational factors that influence job satisfaction in
Malaysia's healthcare industries. Many academic researchers have studied motivational factors
causing job satisfaction in different populations. The scope of this study will be focused on the
Malaysian healthcare industry, and the respondents will be Malaysian healthcare professionals.
This study concentrates on the national level of job satisfaction and motivational factors among
healthcare professionals. The findings of the study help the Malaysian Ministry of Health, regional
health bureaus, and other stakeholders who invest in the Malaysian health sector plan appropriate
interventions to promote healthcare professionals' retention in public health sectors
Churn Forecast Portal using Random Forest Classifier
No full textThe competitive scene inside the telecom and keeping cash businesses demands compelling client
upkeep strategies. This request almost centres on making a energetic Client Churn Figure system
utilizing machine learning strategies, especially the Subjective Forest Classifier, to recognize atrisk
clients proactively. By analysing client data, tallying socioeconomics, advantage utilization
plans, and charging information, the system predicts the likelihood of churn. The encounters
picked up coordinate companies in actualizing centred on trade to make strides client steadfastness.
The made system is affirmed utilizing datasets from the telecom and overseeing an account
division, outlining tall precision and unflinching quality in churn figure
Diabetic Retinopathy Prediction Using Machine Learning
No full textDiabetic retinopathy is among the notorious complications of diabetes and a leading cause of
blindness among adults. Since prevention of vision loss in diabetic retinopathy is possible when
the disease is detected early and interventions instituted, screening is highly essential for this
disease. However, the process of diagnosing the manual images or studying the images of
retinas is lengthy, and because of the connectivity of these interconnections, they blur in certain
cases. This research aims to provide solutions to the preceding challenges through the
development of a web application that can have the ability to diagnose diabetic retinopathy
based on machine learning methods. Within the framework of a rolling scheme, CNN is utilized
for a group of retinal images when the images can be recognized and diagnosed quickly. The
web application is built in the Flask web application platform deliberately for the purpose of
providing the user a rich experience as they upload retina images and receive feedback whether
there is any abnormality or not. This approach enables doctor to be present in a better position
in the assessment of the general surrounding environment while patients become more
conscious and responsible for their vision. Preparing the data, training the model, validating
and testing it, and integrating it into a web-based platform to use the created model are all
included in this. Additionally, this page explains the significance of the established model for
diabetes retinopathy screening and management
Factors that Influence Employee Job Performance: A Case Study of GDEX Express Carrier Bhd
No full textThe purpose of this study is to investigate the key factors influencing employee job performance
in GDEX. Employee job performance has been found to be easily influenced by corporate
behaviours. Therefore, it is important for an organisation to know pertinent issues that are capable
of influencing employee job performance in order to help the organisation achieve high-quality
work performance in future. The main objective of this study is to investigate variables that would
influence employee job performance in GDEX. The four variables include training and
development, rewards, good working environment, and effective communication toward employee
job performance in GDEX. This study employed the qualitative approach to study employee job
performance in a logistics company. The secondary data has been chosen as a research technique
to analyze and examine the problem. Based on the secondary research, the findings showed that
training and development, rewards, good working environment, and effective communication has
a significant positive effect on employee job performance
Work-life Balance towards Employee Well- being and Productivity in Malaysia Private Sector
No full textTo date, work-life balance (WLB) has been a focus topic especially towards the work and family
domains. With the change of workplace psychology and value mapping, the current workforce
heterogeneously, workforce nowadays may value it beyond family. This study is looking to
discover and determine work-life balance among Malaysian working adults. The focus is on the
relationship of flexibility, motivation, job satisfaction, workplace support, and technological
adaptation. Through a survey of 100 participants, this research uncovers key factors contributing
to work-life balance, offering insights for employers and policymakers to enhance employee wellbeing
and productivity in Malaysia. The findings highlight the significance of tailored workplace
practices that address these determinants to foster a balanced and healthy work environment
Lung Cancer Prediction Model to Improve Survival Rates
No full textThe truth that lung cancer is still the essential cause of cancer-related fatalities around the
world emphasizes how critical early distinguishing proof is. This paper utilizes machine
learning methods to reckon the chance of lung cancer from persistent information, such as
socioeconomics, therapeutic history, and imaging outcomes. The framework utilizes
calculations, counting calculated relapse, choice trees, and bolster vector machines, with the
objective of making strides in demonstrative accuracy and speeding up incite mediation. To
ensure the model's steadfastness in clinical settings, its execution is surveyed utilizing
measures counting exactness, exactness, and review. This strategy of treating lung cancer
has the potential to improve understanding results and early discovery rates
A Data Analytics Strategy to the Underground Economy of Cybercrime
No full textMassive cyberattacks and cybercrimes such as ransomware and distributed denial of service
(DDoS) attacks have become more and more of a danger, and individuals, organizations, and
governments have struggled to discover effective means to defend against them. In 2017, the
WannaCry ransomware was to blame for roughly 45,000 strikes across almost 100 nations.
Governments have come under pressure to enhance their cybersecurity spending as a result of
the increasing impact of cybercrime. In his fiscal year 2017 budget, United States President
Barack Obama suggested investing more than $19 billion in cybersecurity, a rise of more than
35% from 2016. Thus, a new sort of organization known as the "cybercrime underground" has
developed, one that both runs underground markets and fosters the growth of cybercrime
conspiracies. The threat posed by the emergence of highly skilled network-based cybercrime
business models, such as Crimeware-as-a-Service (CaaS), is mostly invisible to governments,
organizations, and individuals because cybercrime networks are lateral, diffuse, fluid, and
dynamic. Although cyber dangers are rapidly increasing, there hasn't been much research done
on the methodology or theoretical underpinnings of the field that could help inform information
systems researchers and practitioners who work in the field of cyber security. Additionally, little
is understood about Crime-as-a-Service (CaaS), the illegal business model that supports the
underground world of cybercrime
Analysis of Indonesian Public Perception on the Influence of American Food Brands with the Indonesia-America Cooperation Relationship Using SEM-PLS
No full textGlobalization has removed barriers between countries, particularly in the field of food. One of the main impacts of this phenomenon is the entry of foreign food and beverage brands into domestic markets, including brands from the United States. The United States (US) supports Israel in its conflict with Palestine, which is contrary to Indonesia's stance. Therefore, an analysis was conducted on the perception of Indonesian society towards American brands and how this affects the bilateral cooperation between the two countries. The method used was descriptive quantitative, and data analysis was performed using Structural Equation Modeling Partial Least Square (SEM-PLS) with a sample of 200 respondents. The results of this study showed an R-square value of 10.22% without a mediating variable and 49.87% when including a mediating variable. This value indicates that incorporating the mediating variable into the model increases the explained variability of the model to 49.87%, while the remainder can be explained by other variables
Analyzing the Digital Transformation Competence of Vietnamese Students Using Exploratory Factor Analysis (EFA)
No full textIn Vietnam, digital transformation has been taking place strongly in all fields, especially education. Universities are very interested and focused on promoting digital transformation activities at their facilities. Students are individuals who participate and directly benefit from this process. The question is how competent students are when participating in digital transformation at the institution. This article focuses on researching the digital transformation competency of Vietnamese students in general, and at Commerce University in particular. From there, it provides educational institutions with the perspective of the digital transformation competency of students. Especially, based on experiments conducted with 405 students at the Universities of Commerce, the research group applied the Exploratory Factor Analysis (EFA) method and multiple linear regression to identify seven factors influencing digital transformation competence: "Interest", "Usefulness", "Importance", "Personal capacity", "Relationship", "University" and these seven factors explained 71.7% of the variation in digital transformation competence. In summary, the research provides support for educational institutions to develop plans for enhancing the digital transformation competency of students in general and at Thuongmai University in particular