International Journal of Information Engineering and Electronic Business (IJIEEB)

ISSN: 2074-9023 (Print)

ISSN: 2074-9031 (Online)

DOI: https://doi.org/10.5815/ijieeb

Website: https://www.mecs-press.org/ijieeb

Published By: MECS Press

Frequency: 6 issues per year

Number(s) Available: 87

(IJIEEB) in Google Scholar Citations / h5-index

IJIEEB is committed to bridge the theory and practice of information engineering and electronic business. From innovative ideas to specific algorithms and full system implementations, IJIEEB publishes original, peer-reviewed, and high quality articles in the areas of information engineering and electronic business. IJIEEB is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of information engineering and electronic business applications.

 

IJIEEB has been abstracted or indexed by several world class databases: Scopus, Google Scholar, Microsoft Academic Search, CrossRef, Baidu Wenku, IndexCopernicus, IET Inspec, EBSCO, VINITI, JournalSeek, ULRICH's Periodicals Directory, WorldCat, Scirus, Academic Journals Database, Stanford University Libraries, Cornell University Library, UniSA Library, CNKI Scholar, ProQuest, J-Gate, ZDB, BASE, OhioLINK, iThenticate, Open Access Articles, Open Science Directory, National Science Library of Chinese Academy of Sciences, The HKU Scholars Hub, etc..

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IJIEEB Vol. 17, No. 4, Aug. 2025

REGULAR PAPERS

Financial Forecasting with Deep Learning Models Based Ensemble Technique in Stock Market Analysis

By Chandrayani Rokde Jagdish Chakole Aishwarya Ukey

DOI: https://doi.org/10.5815/ijieeb.2025.04.01, Pub. Date: 8 Aug. 2025

In recent years, deep learning techniques have emerged as powerful tools for analyzing and predict- ing complex patterns in sequential data across various fields. This study employs an ensemble of advanced deep learning models: Long Short-Term Memory (LSTM), Bi-Directional LSTM, Gated Recurrent Unit (GRU), LSTM Convolutional Neural Network (CNN), and LSTM with Self-Attention, to enhance prediction accuracy in time series forecasting. These models are applied to three distinct financial datasets: Tata Motors, HDFC Bank, and INFY.NS, we conduct a thorough comparative analysis to assess their performance. Utilizing K-fold cross-validation, we convert loss (MSE) into RMSE and MAPE, which help estimate accuracy .we achieved train accuracies of 97.46% for Tata Motors, 75.93% for INFY.NS, and 56.60% for HDFC Bank. Our empirical results highlight the strengths and limitations of each model within the ensemble framework and pro- vide valuable insights into their effectiveness in capturing complex patterns in financial time series data. This research underscores the potential of deep learning-based ensemble techniques for improving stock price forecasting and offers significant implications for investors and the development of sophisticated trading and risk management systems.

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Comprehensive Application of Logistics Cost Optimization Models for the Delivery of Goods by Road

By Nataliya Mutovkina

DOI: https://doi.org/10.5815/ijieeb.2025.04.02, Pub. Date: 8 Aug. 2025

The current society’s development is the intensive growth of human needs. That leads to an increase in production volumes. That requires an appropriate level of product transportation. Currently, there are various kinds, including automobile, railway, water, and air transport. According to the International Maritime Organization, maritime transport is the undisputed leader in international transportation; however, on land, road freight transportation surpasses other types in demand. That is due to the mobility of cars and the availability of a well-developed road infrastructure, which allows cargo to be delivered directly from the seller to the customer. In this regard, there is a need to plan routes for vehicles, solve transport tasks, and ensure the rational use of the carrying capacity of means of transport. When organizing cargo transportation, tasks include building optimal routes, minimizing transportation costs, and avoiding the underutilization of the truck. Continuous improvement of cargo delivery is a serious strategic objective of competing transport companies. It is necessary to regulate the costs of the services provided. Cost management and optimization are serious tools in organizing a transport company, which contribute to increasing its efficiency. That is due to the relevance of the research topic. The article discusses the theoretical and methodological aspects of cost optimization in transport companies, presents some optimization models, and justifies their application. Practice shows that these models can be applied to the activities of cargo carriers to significantly reduce unproductive costs and ensure the achievement of strategic goals, such as achieving market leadership positions and increasing competitiveness.

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A Scalable Blockchain Framework for Secure IoT Communication

By Sudipta Majumder

DOI: https://doi.org/10.5815/ijieeb.2025.04.03, Pub. Date: 8 Aug. 2025

The rapid proliferation of Internet of Things (IoT) devices has revealed weaknesses in its centralized communication architectures, rendering them vulnerable to security risks such as Distributed Denial of Service (DDoS) attacks. This scenario highlights the need for secure and efficient communication frameworks to safeguard IoT networks. In this paper, we present a blockchain-based framework designed to improve IoT communication networks' security, scalability, and performance. Our methodology utilizes decentralized architecture to mitigate risks linked to centralized sources of failure while enhancing performance metrics, including latency, throughput, energy consumption, and transaction success rates. We present an innovative approach that integrates a plateau effect in latency and consensus time, guaranteeing performance stability as the number of devices increases. The proposed model demonstrates decreases in latency by 26.57% and reductions in energy usage by 35.29% compared to existing Ethereum frameworks, based on extensive simulations conducted under diverse network conditions with one thousand devices, underscoring the framework's effectiveness in managing network congestion. This research offers a viable answer to the problems of IoT communication, facilitating future investigations into the optimization of blockchain integration for improving IoT security and efficiency.

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Enhanced Predictive Modelling of Heart Disease Using Optimized Machine Learning Algorithms

By Ahmed Qtaishat Wan Suryani Wan Awangb

DOI: https://doi.org/10.5815/ijieeb.2025.04.04, Pub. Date: 8 Aug. 2025

Cardiovascular disease (CVD) remains a leading global cause of mortality, underscoring the importance of its early detection. This research leverages advanced Machine Learning (ML) algorithms to predict Coronary Heart Disease (CHD) risk by analysing critical factors. A comprehensive evaluation of ten ML techniques, including K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), AdaBoost, Multi-Layer Perceptron Neural Network (MLPNN), and Extremely Randomized Trees (ERT), was conducted. The ERT algorithm demonstrated superior performance, achieving the highest test accuracy of 88.52%, with precision, recall, and F1-scores of 0.89, 0.88, and 0.88, respectively, for class 0 (no CHD), and 0.88, 0.91, and 0.89, respectively, for class 1 (CHD). The model was optimized using hyperparameters such as a bootstrap setting of False, no maximum depth, a minimum sample split of 2, a minimum leaf size of 4, and 300 estimators. This study provides a detailed comparison of these techniques using metrics such as precision, recall, and F1-score, offering critical insights for optimizing predictive models in clinical applications. By advancing early detection methodologies, this work aims to support healthcare practitioners in reducing the global burden of cardiac diseases.

[...] Read more.
IoT-based Crop Recommendation System using Machine Learning via Mobile Application for Precision Agriculture in Bangladesh

By Md. Shahriar Hossain Apu Md. Nur-E Ferdaus Tousif Mahmud Emon Suman Saha

DOI: https://doi.org/10.5815/ijieeb.2025.04.05, Pub. Date: 8 Aug. 2025

Precision agriculture transform the agricultural sector by integrating advanced technologies to enhance productivity and sustainability. In crop farming, precision agriculture can significantly improve practices through precise monitoring and data-driven decision-making, addressing challenges such as optimizing resource usage and improving crop health. This study presents the development and implementation of an IoT-based Crop Recommendation System designed to optimize farming practices through a mobile application. This system uses different sensors to continuously extract data regarding the temperature, pH, NPK value and other relevant parameters. These parameters can be analyzed in real-time to help farmers make informed decisions on irrigation, fertilization, and crop selection, tailored to specific field conditions. This information is stored to create individual datasets, offering researchers valuable insights into optimal conditions for various crops. This can improve yield and promote sustainable farming practices. In this study, we evaluated a series of machine learning algorithms for their ability to predict an optimal crop based on environmental parameters. Among these algorithms, Naive Bayes demonstrated superior performance, achieving an accuracy of 99.55%, precision of 99.58%, recall of 99.55%, and F1-score of 99.54%. These findings highlight the effectiveness of our approach in integrating machine learning with the IoT for precise crop management. Implemented through a user-friendly mobile application, the proposed system enhances accessibility and usability for farmers.

[...] Read more.
Evaluating Impact of Quality of Work Life Factors on Job Satisfaction: Structural Equation Modelling based Data Analysis in Banking

By N. Usha Deepa Sundari Lakshmi Narayanamma Poli

DOI: https://doi.org/10.5815/ijieeb.2025.04.06, Pub. Date: 8 Aug. 2025

The service sector, particularly banks, has undergone a significant shift in recent years. This has resulted in increased pressure and stress for bank employees who strive to provide timely and efficient services while meeting management objectives and ensuring customer satisfaction. This research employs a comprehensive methodological approach to examine the Quality of Work Life (QWL) and Job Satisfaction (JS) within the banking sector in Andhra Pradesh. The research focuses on confirming the construct validity of QWL and JS through Confirmatory Factor Analysis (CFA) and assessing the reliability of the measurement model using Cronbach's Alpha. Discriminant validity is examined to ensure that these constructs represent distinct concepts. The research employs Structural Equation Modeling (SEM) to explore the correlation between QWL and JS, as well as their interactions with factors such as Motivation and Compensation, Work Factors, Safety and Welfare, Relationship and Support, Nature of Job, and Career Growth and Development. The outcomes of this research offer valuable insights into the banking industry in Andhra Pradesh. By validating the QWL and JS constructs and understanding their relationships, the research serves as a foundation for organizations to enhance employee well-being and job satisfaction. The study provides practical recommendations, tailored to the specific needs of bank employees in Andhra Pradesh, to improve work-life balance, career development, compensation, safety, relationships at work, and overall employee well-being.

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Comprehensive Intellectual Analysis of Statistical Data on Leading Energy Companies’ Actions

By Viktoriia Bulatova Sofiia Popp Victoria Vysotska Yuriy Ushenko Zhengbing Hu Dmytro Uhryn

DOI: https://doi.org/10.5815/ijieeb.2025.04.07, Pub. Date: 8 Aug. 2025

The paper conducted a comprehensive analysis of the time series of stock prices of three leading energy companies – Shell, BP and ExxonMobil – for the period from January 2021 to January 2025. At the initial stage, data quality was checked: dates were set as indices, the absence of duplicates and missing values was confirmed, and descriptive statistics (mean, variance, skewness and kurtosis) were calculated. Next, the trends of adjusted closing prices (AdjClose) were analysed using moving averages (SMA14, SMA50), exponential smoothing, moving volatility (30-day standard deviation) and cumulative returns. It was found that еhe price dynamics growth has accelerated since 2022 against the background of the energy crisis caused by the war in Ukraine: ExxonMobil’s cumulative return reached ≈250% by mid-2022 and ≈350% at the beginning of 2025, Shell and BP, respectively ≈220% and ≈200% by 2024. Correlation analysis showed that BP and Shell have the most significant interdependence (r = 0.87, R² = 0.75). The autocorrelation method established high non-stationarity of the time series (ACF about one at low lags). K-Means clustering (k = 2) allowed us to distinguish periods of active growth and relative price consolidation, although the feature selection behind this clustering requires further clarification. The initially reported financial metrics (Sharpe, Sortino, and Calmar ratios) were significantly overstated due to unit errors, specifically, using percentage values as absolute figures. After applying appropriate annualization and decimal scaling performance indicators were obtained for ExxonMobil – CAGR = 36.84%, Sharpe ≈ 1.24, Sortino ≈ 1.9–2.5, Max Drawdown = 20.51%, Calmar ≈ 1.80; Shell: CAGR = 21.29%, Sharpe ≈ 0.76, Sortino ≈ 1.2–1.5, Max Drawdown = 25.04%, Calmar ≈ 0.85; BP: CAGR = 14.54%, Sharpe ≈ 0.53, Sortino ≈ 0.9–1.2, Max Drawdown = 26.23%, Calmar ≈ 0.55. The study confirms that ExxonMobil showed the most stable and substantial growth during the examined period, while BP exhibited the highest volatility. Shell demonstrated an intermediate performance level. The close correlation between Shell and BP is attributed to the similarity in their geographical market activity and stock behaviour. The choice of these methods of analysis is due to the desire to assess the behaviour of stocks during the period of increased market volatility caused by the energy crisis, geopolitical risks and changes in investor priorities. Technical analysis allows you to identify short- and medium-term patterns, clustering allows you to automatically separate market phases without the need for subjective hypotheses, and statistical metrics will enable you to compare the performance of assets within the industry. This research contributes to the broader field of financial analysis by demonstrating how machine learning and technical analytics tools can be applied to assess the resilience and relationships of assets during periods of market turmoil. The results can be helpful for institutional investors, financial analysts, and portfolio managers looking to adapt strategies to dynamic energy market conditions.

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PARADAJuan: A Web-Based Parking Lot Management System Designed and Developed Using Multi-Paradigm Programming Languages

By Ruth G. Luciano Angelito I. Cunanan Romualdo P. Mariano Edrain Nico A. Tavares Mark Reniel L. Jacinto

DOI: https://doi.org/10.5815/ijieeb.2023.03.05, Pub. Date: 8 Jun. 2023

This study aims to develop a web-based parking lot management system using multi-paradigm programming languages. This application is designed to help parking lot owners in monitoring the ins and outs of the parking spaces including the income they generated from it. The researchers used multi-paradigm programming languages where more than one programming paradigm was employed. This allows them to use the most suitable programming style and associated language constructs to build the system. Specifically, the researchers made use of the following languages in creating the system: HTML5, CSS3, JavaScript, PHP, MySQL, and Flutter. The study utilized developmental research methods in which the product-development process is analyzed and described, and the final product is evaluated. As a result, the creation of the system has been successful.

[...] Read more.
Diabetes Prediction: A Deep Learning Approach

By Safial Islam Ayon

DOI: https://doi.org/10.5815/ijieeb.2019.02.03, Pub. Date: 8 Mar. 2019

Nowadays, Diabetes is one of the most common and severe diseases in Bangladesh as well as all over the world. It is not only harmful to the blood but also causes different kinds of diseases like blindness, renal disease, kidney problem, heart diseases etc. that causes a lot of death per year. So, it badly needs to develop a system that can effectively diagnose the diabetes patients using medical details. We propose a strategy for the diagnosis of diabetes using deep neural network by training its attributes in five and ten-fold cross-validation fashion. The Pima Indian Diabetes (PID) data set is retrieved from the UCI machine learning repository database. The results on PID dataset demonstrate that deep learning approach design an auspicious system for the prediction of diabetes with prediction accuracy of 98.35%, F1 score of 98, and MCC of 97 for five-fold cross-validation. Additionally, accuracy of 97.11%, sensitivity of 96.25%, and specificity of 98.80% are obtained for ten-fold cross-validation. The experimental results exhibit that the proposed system provides promising results in case of five-fold cross-validation.

[...] Read more.
A Review of Applications of Linear Programming to Optimize Agricultural Solutions

By Alanoud Alotaibi Farrukh Nadeem

DOI: https://doi.org/10.5815/ijieeb.2021.02.02, Pub. Date: 8 Apr. 2021

Quantitative methods help farmers plan and make decisions. An apt example of these methods is the linear programming (LP) model. These methods acknowledge the importance of economizing on available resources among them being water supply, labor, and fertilizers. It is through this economizing that farmers maximize their profit. The significance of linear programming is to provide a solution to the existing real-world problems through the evaluation of existing resources and the provision of relevant solutions. This research studies various LP applications including feed mix, crop pattern and rotation plan, irrigation water, and product transformation; that have the main role to enhance various facets of the agriculture sector. The paper will be a review that will probe into the applications of the LP model and it will also highlight the various tools that are central to analyzing LP model results. The review will culminate in a discussion on the different approaches that help optimize agricultural solutions.

[...] Read more.
Sentiment Analysis of Review Datasets Using Na?ve Bayes‘ and K-NN Classifier

By Lopamudra Dey Sanjay Chakraborty Anuraag Biswas Beepa Bose Sweta Tiwari

DOI: https://doi.org/10.5815/ijieeb.2016.04.07, Pub. Date: 8 Jul. 2016

The advent of Web 2.0 has led to an increase in the amount of sentimental content available in the Web. Such content is often found in social media web sites in the form of movie or product reviews, user comments, testimonials, messages in discussion forums etc. Timely discovery of the sentimental or opinionated web content has a number of advantages, the most important of all being monetization. Understanding of the sentiments of human masses towards different entities and products enables better services for contextual advertisements, recommendation systems and analysis of market trends. The focus of our project is sentiment focussed web crawling framework to facilitate the quick discovery of sentimental contents of movie reviews and hotel reviews and analysis of the same. We use statistical methods to capture elements of subjective style and the sentence polarity. The paper elaborately discusses two supervised machine learning algorithms: K-Nearest Neighbour(K-NN) and Naïve Bayes‘ and compares their overall accuracy, precisions as well as recall values. It was seen that in case of movie reviews Naïve Bayes‘ gave far better results than K-NN but for hotel reviews these algorithms gave lesser, almost same accuracies.

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Two Proposed Models for Securing Data Management for Enterprise Resource Planning Systems Using Blockchain Technology

By Nafiz Ahmed Anik Kumar Saha Mustafa Ahmad Arabi Sheikh Talha Jubayer Rahman Dip Nandi

DOI: https://doi.org/10.5815/ijieeb.2023.06.02, Pub. Date: 8 Dec. 2023

An Enterprise Resource Planning (ERP) system is a software application that serves as a centralized platform to streamline and automate organizational functions and share real-time data, facilitating efficient communication and collaboration. It provides an all-inclusive approach to managing and optimizing business processes, boosting efficiency, fostering cooperation, and giving an overall picture of how the organization is operating. However, the traditional centralized databases in ERP systems pose security concerns. Blockchain Technology can be an appealing alternative as it comes with immutable and decentralized data as well as enhanced security. This study focuses on two methods of securing data management in ERP systems: Organizing the distributed information using The Ralph Kimball data model and optimizing an individual block using Database Sharding. This study does an extensive examination to determine the effectiveness of both suggested strategies, comprising a detailed evaluation that highlights the benefits and limitations of both techniques. This paper intends to patch the security holes in ERP systems to safeguard sensitive data and mitigate risks.

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Web Based Student Registration and Exam Form Fill-up Management System for Educational Institute

By Md. Tofail Ahmed Md. Humaun Kabir Sujit Roy

DOI: https://doi.org/10.5815/ijieeb.2022.02.04, Pub. Date: 8 Apr. 2022

Registration of new students’ academic information is essential for every educational institute to continue their education at every semester level and go through their whole student life. And this registration information is used when they do their form fill up of consecutive semesters. Nowadays, almost all educational institutes are using paper based registration and form fill up systems which is prone to many human errors and very time consuming for both students, teachers as well as other related administrative bodies. In this paper, we developed a web based application for academic purposes to control and save student registration and form fill up data that will be helpful for students, teachers and admin authority to make the process easier, less time consuming and error free. There are four main types of users who can use this system: student, department authority, students’ hall authority and administrator. The student can submit their registration and form fill up information by using a web form. Moreover, he/she can download their admit card and registration form after the approval of the concerned authority. The students also can be able to do other module activities. The hall and department authority can use the system to approve the students' registration, semester examination form and to provide the students' attendance data. In addition, the department and hall authority has a choice to see all students’ academic information. Moreover, the system administrator controls the system by managing (add, delete, update) student, hall and department authority, exam or registration date, subjects of a particular semester, notice board of the institute, module and programme data. The administrator can also add and remove the running and passed student data. The students also can pay their semester fees by using an online banking system.

[...] Read more.
Barriers to E-Commerce Adoption in Egyptian SMEs

By Abdel Nasser H. Zaied

DOI: https://doi.org/10.5815/ijieeb.2012.03.02, Pub. Date: 8 Jul. 2012

E-commerce has been predicted to be a new driver of economic growth for developing countries. The SME sector plays a significant role in its contribution to the national economy in terms of the wealth created and the number of people employed. Small and Medium Enterprises (SMEs) in Egypt represent the greatest share of the productive units of the Egyptian economy and the current national policy directions address ways and means of developing the capacities of SMEs. Many factors could be responsible for the low usage of e-commerce among the SMEs in Egypt. In order to determine the factors that promote the adoption of e-commerce, SMEs adopters and non-adopters of e-commerce were asked to indicate the factors inhibiting the adoption of e-commerce. The results show that technical barriers are the most important barriers followed by legal and regulatory barriers, whereas lack of Internet security is the highest barrier that inhibit the implementation of e-commerce in SMEs in Egypt followed by limited use of Internet banking and web portals by SMEs. Also, findings implied that more efforts are needed to help and encourage SMEs in Egypt to speed up e-commerce adoption, particularly the more advanced applications.

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The Role of Knowledge Management in Enhancing Organizational Performance

By Abdel Nasser H. Zaied Gawaher Soliman Hussein Mohamed M. Hassanc

DOI: https://doi.org/10.5815/ijieeb.2012.05.04, Pub. Date: 8 Oct. 2012

Knowledge management is recognized as an important weapon for sustaining competitive advantage and improving performance. The evaluation of knowledge management (KM) performance has become increasingly important since it provides the reference for directing the organizations to enhance their performance and competitiveness. This paper provides an understanding of factors that involved in implementing knowledge management concept to enhance organizational performance. Also, it provides an assessment tool that helps organizations to assess their knowledge management capabilities and identify the possible existing gaps in their knowledge management systems and suggest the possible ways to enhance organizational performance. The results show that all elements of knowledge management capabilities have a positive significant relationship with all measures of the performance at 1% level of significant; it means that there is a great correlation between knowledge management capabilities and organizational performance

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E –Hospital Management & Hospital Information Systems – Changing Trends

By Premkumar Balaraman Kalpana Kosalram

DOI: https://doi.org/10.5815/ijieeb.2013.01.06, Pub. Date: 8 May 2013

The rapid growth in Information & Communication Technology (ICT), and the power of Internet has strongly impacted the business and service delivery models of today’s global environment. E-Hospital Management Systems provide the benefits of streamlined operations, enhanced administration & control, superior patient care, strict cost control and improved profitability. Globally accepted health care systems need to comply with Healthcare Insurance Portability and Accountability Act (HIPAA) standards of the US and that has become the norm of the Healthcare industry when it comes to medical records management and patient information privacy. The study is focused on understanding the performance indicators of Hospital information systems (HIS), summarizing the latest commonly agreed standards and protocols like Health Level Seven (HL7) standards for mutual message exchange, HIS components, etc… The study is qualitative and descriptive in nature and most of the data is based on secondary sources of survey data. To arrive at a conclusive idea of the larger picture on E- Hospital Management and Hospital information systems, existing survey data and specific successful case studies of HIS are considered in the study. With so many customized versions of E – hospital management solutions (E – HMS) and Hospital Information systems (HIS) available in the market, a generic module wise version of E – Hospital management system is charted out to give a clear understanding for researchers and industry experts. From the specific successful case studies analyzed in the study, the success factors and challenges faced in successful E-HMS implementation are highlighted. Some of the mandatory standards like HIPAA are discussed in detail for clarity on Healthcare system implementation requirements.

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A Review on Data Analytics for Supply Chain Management: A Case study

By Anitha P Malini M. Patil

DOI: https://doi.org/10.5815/ijieeb.2018.05.05, Pub. Date: 8 Sep. 2018

The present study bridges the gap between the two intersecting domains, data science and supply chain management. The data can be analyzed for inventory management, forecasting and prediction, which is in the form of reports, queries and forecasts. Because of the price, weather patterns, economic volatility and complex nature of business, the forecasts may not be accurate. This has resulted in the growth of Supply chain analytics. It is the application of qualitative and quantitative methods to solve relevant problems and to predict the outcomes by considering quality of data. The issues like increased collaboration between companies, customers, retailers and governmental organizations, companies are adopting Big Data solutions. Big Data applications can be linked for Supply Chain Management across the fields like procurement, transportation, warehouse operations, marketing and also for smart logistics. As supply chain networks becoming vast, more complex and driven by demands for more exacting service levels, the type of data that is managed and analyzed also becomes more complex. The present work aims at providing an overview of adoption of capabilities of Data Analytics as part of a “next generation” architecture by developing a linear regression model on a sales-data. The paper also covers the survey of how big data techniques can be used for storage, processing, managing, interpretation and visualization of data in the field of Supply chain.

[...] Read more.
PARADAJuan: A Web-Based Parking Lot Management System Designed and Developed Using Multi-Paradigm Programming Languages

By Ruth G. Luciano Angelito I. Cunanan Romualdo P. Mariano Edrain Nico A. Tavares Mark Reniel L. Jacinto

DOI: https://doi.org/10.5815/ijieeb.2023.03.05, Pub. Date: 8 Jun. 2023

This study aims to develop a web-based parking lot management system using multi-paradigm programming languages. This application is designed to help parking lot owners in monitoring the ins and outs of the parking spaces including the income they generated from it. The researchers used multi-paradigm programming languages where more than one programming paradigm was employed. This allows them to use the most suitable programming style and associated language constructs to build the system. Specifically, the researchers made use of the following languages in creating the system: HTML5, CSS3, JavaScript, PHP, MySQL, and Flutter. The study utilized developmental research methods in which the product-development process is analyzed and described, and the final product is evaluated. As a result, the creation of the system has been successful.

[...] Read more.
Web Based Student Registration and Exam Form Fill-up Management System for Educational Institute

By Md. Tofail Ahmed Md. Humaun Kabir Sujit Roy

DOI: https://doi.org/10.5815/ijieeb.2022.02.04, Pub. Date: 8 Apr. 2022

Registration of new students’ academic information is essential for every educational institute to continue their education at every semester level and go through their whole student life. And this registration information is used when they do their form fill up of consecutive semesters. Nowadays, almost all educational institutes are using paper based registration and form fill up systems which is prone to many human errors and very time consuming for both students, teachers as well as other related administrative bodies. In this paper, we developed a web based application for academic purposes to control and save student registration and form fill up data that will be helpful for students, teachers and admin authority to make the process easier, less time consuming and error free. There are four main types of users who can use this system: student, department authority, students’ hall authority and administrator. The student can submit their registration and form fill up information by using a web form. Moreover, he/she can download their admit card and registration form after the approval of the concerned authority. The students also can be able to do other module activities. The hall and department authority can use the system to approve the students' registration, semester examination form and to provide the students' attendance data. In addition, the department and hall authority has a choice to see all students’ academic information. Moreover, the system administrator controls the system by managing (add, delete, update) student, hall and department authority, exam or registration date, subjects of a particular semester, notice board of the institute, module and programme data. The administrator can also add and remove the running and passed student data. The students also can pay their semester fees by using an online banking system.

[...] Read more.
A Review of Applications of Linear Programming to Optimize Agricultural Solutions

By Alanoud Alotaibi Farrukh Nadeem

DOI: https://doi.org/10.5815/ijieeb.2021.02.02, Pub. Date: 8 Apr. 2021

Quantitative methods help farmers plan and make decisions. An apt example of these methods is the linear programming (LP) model. These methods acknowledge the importance of economizing on available resources among them being water supply, labor, and fertilizers. It is through this economizing that farmers maximize their profit. The significance of linear programming is to provide a solution to the existing real-world problems through the evaluation of existing resources and the provision of relevant solutions. This research studies various LP applications including feed mix, crop pattern and rotation plan, irrigation water, and product transformation; that have the main role to enhance various facets of the agriculture sector. The paper will be a review that will probe into the applications of the LP model and it will also highlight the various tools that are central to analyzing LP model results. The review will culminate in a discussion on the different approaches that help optimize agricultural solutions.

[...] Read more.
Development of a Decision Support System on Employee Performance Assessment Using Weighted Performance Indicators Method

By Terttiaavini Yusuf Hartono Ermatita Dian Palupi Rini

DOI: https://doi.org/10.5815/ijieeb.2023.03.01, Pub. Date: 8 Jun. 2023

Employee Performance Assessment is a part of the Decision Support System. One of the decision support system methods that are most used in performance assessment is Simple Additive Weighting (SAW). In the SAW method, each criterion has a weight value to show the interest level. The determination of the criteria on the SAW method is subjective and the final result is on the ranked system and creates many problems. The study utilizes the Weighted Performance Indicators (WPI) method to solve the problems in the SAW method. The criterion is determined based on the respondent's opinion so that it will be more realistic to achieve the target. The population of the study is the employee of Indo Global Mandiri University which reach 30 persons. WPI method consists of 9 steps. The research result is shown that 4 employees has a performance below MSV and 36 employee has above MSV. The general value of the employee performance value = is 0.69. It shows that the performance of the employee at Indo Global Mandiri University is good enough. However, it needs to be increased, so that the target could be achieved. WPI method is easy to implement, it is not just limited to the employee performance assessment only, but it could be implemented for the other performance assessment, for example, human resource performance, finance, company, industry, system, etc.

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Sales Management Application at Widya Collection Store Web-based

By Vilianty Rafida Ita Arfyanti Irfan Hidayat

DOI: https://doi.org/10.5815/ijieeb.2022.04.01, Pub. Date: 8 Aug. 2022

Widya Collection Store is a business that provides sports clothing, as well as one of the producers in the Samarinda area. Sales management is still not optimal because it still uses paper notes and is still being written which makes it easy for errors to occur in writing prices, quantities of goods and total prices so that it takes a long time to process transactions, both from payment in full or receivables. In addition, managing stock of goods is also more difficult because it is not recorded in the database. Therefore, a Sales Management application was made at the Web-Based Widya Collection Store to process item data, sales transactions, make complete notes and reports and make the transaction process faster. The long-term goal to be achieved is that the stock management process has been recorded in order to know the stock that must be ordered from the supplier. In addition, to simplify and expedite activities in searching for sales transaction data if one day it is needed. In this study, the method used to build a Sales Management Application at a Web-Based Widya Collection Store is the System Development Life Cycle (SDLC) development stage which consists of needs analysis, system design, and implementation.

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Development E-commerce Information System of Agriculture in Samarinda

By Asep Nurhuda Aulia Khoirunnita Arika Rusli Dimas K. Umami Sri Handayani

DOI: https://doi.org/10.5815/ijieeb.2022.06.05, Pub. Date: 8 Dec. 2022

Samarinda village is a village that is predominantly working as a farmer and has a wide range of agricultural products, in addition to the abundance of agricultural products there is a problem of marketing of agricultural products that do not have access to sell their agricultural products. Authors conducted research in order to increase sales and expand marketing in the Village Samarinda through sales system-based Business to the Business and method development using the Research and Development. The results obtained in the form of a web site that can be accessed to serve online sales transaction so that it can increase sales in the village Samarinda.

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House Price Prediction Modeling Using Machine Learning

By M. Thamarai SP. Malarvizhi

DOI: https://doi.org/10.5815/ijieeb.2020.02.03, Pub. Date: 8 Apr. 2020

Machine Learning is seeing its growth more rapidly in this decade. Many applications and algorithms evolve in Machine Learning day to day. One such application found in journals is house price prediction. House prices are increasing every year which has necessitated the modeling of house price prediction. These models constructed, help the customers to purchase a house suitable for their need. Proposed work makes use of the attributes or features of the houses such as number of bedrooms available in the house, age of the house, travelling facility from the location, school facility available nearby the houses and Shopping malls available nearby the house location. House availability based on desired features of the house and house price prediction are modeled in the proposed work and the model is constructed for a small town in West Godavari district of Andhrapradesh. The work involves decision tree classification, decision tree regression and multiple linear regression and is implemented using Scikit-Learn Machine Learning Tool.

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Developing Smart Conversation Agent ECOM-BOT for Ecommerce Applications using Deep Learning and Pattern Matching

By Maria Zafar

DOI: https://doi.org/10.5815/ijieeb.2023.02.01, Pub. Date: 8 Apr. 2023

Chatbots are a technological leap in conversational services, generating messages to users either following a set of rules to respond based on recognized patterns or training themselves from previous data or conversations. The primary goal is to enable a device to communicate with a user upon receiving natural language user requests using artificial intelligence and machine learning to generate automated responses. Technology is progressively catering to the questions, both in academic and business contexts, such as situations that require agents to investigate the cause of customer dissatisfaction or to recommend products and services. Significance of this research is to reduce the human dependency and improving customer support by providing close to human natural responses using pattern matching and deep learning on the custom-made data. The main objective of this work is to (a) study the existing literature on cutting-edge technologies in chatbot development in terms of research trends, legacy components, techniques, datasets, and domains specifically in e-commerce and (b) to develop a product that fill some of the gaps/missing functionality identified in current frameworks. We have achieved the following, (a) generated small yet generic dataset, which can be used for all types of products, (b) the intents are identified accurately by the bot using deep learning, whenever a user query.

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Cybercrimes during COVID -19 Pandemic

By Raghad Khweiled Mahmoud Jazzar Derar Eleyan

DOI: https://doi.org/10.5815/ijieeb.2021.02.01, Pub. Date: 8 Apr. 2021

COVID-19 pandemic has changed the lifestyle of all aspects of life. These circumstances have created new patterns in lifestyle that people had to deal with. As such, full and direct dependence on the use of the unsafe Internet network in running all aspects of life. As example, many organizations started officially working through the Internet, students moved to e-education, online shopping increased, and more. These conditions have created a fertile environment for cybercriminals to grow their activity and exploit the pressures that affected human psychology to increase their attack success. The purpose of this paper is to analyze the data collected from global online fraud and cybersecurity service companies to demonstrate on how cybercrimes increased during the COVID-19 epidemic. The significance and value of this research is to highlight by evident on how criminals exploit crisis, and for the need to develop strategies and to enhance user awareness for better detection and prevention of future cybercrimes.

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The Decentralized Shariah-Based Banking System in Bangladesh Using Block-chain Technology

By Oishi Chowdhury Md Al Samiul Amin Rishat Md. Al-Amin Md. Hanif Bin Azam

DOI: https://doi.org/10.5815/ijieeb.2023.03.02, Pub. Date: 8 Jun. 2023

Shariah-based banking aims to apply Islamic finance while adhering to Shariah principles. The primary distinction between conventional and Islamic finance is that Sharia law explicitly forbids several of the activities and principles applied in conventional banking. According to Sharia law, “Paying or charging an interest (Riba)” lending with interest payments as an exploitative practice that benefits the lender at the expense of the borrower, “investing in businesses engaged in banned activities" like producing and selling alcohol or pork, “speculation or gambling(Maisir)” That means financial institutions are prohibited from participating in contracts where the ownership of goods depends on an unpredictable future event, and Participation in contracts with a high level of risk or uncertainty is referred to as "uncertainty and risk (Gharar)", which are strictly prohibited. As a result, consumers must be aware of whether they are taking Riba, Gharar, Maisir or if their money is invested in a halal firm. Because of its qualities, blockchain would be useful in this situation. This research tries to determine how blockchain technology can be used to make investments and profit or loss returns more transparent, more secure, Immutable and sharia compliant. Blockchain networks can be utilized in the financial industry, such as banking, to provide safe sharia banking.

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