- Все статьи 642
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International Journal of Information Engineering and Electronic Business @ijieeb
Статьи журнала - International Journal of Information Engineering and Electronic Business
Все статьи: 642
Статья научная
This study aims to examine how to evaluate the activities undertaken in IDX. By building the system "business intelligence implementation to determine the evaluation of activities ". Where in this study also used the algorithm Naive Bayes in the process of data classification activities that have been done. The approach to the development of this software is through the study of libraries, data collection, system design, system implementation, Test systems and analysis. The tools used in the development of this software are Pentaho, PostgreSQL (as a data processing tool), Microsoft Excel (as a tool for creating training data), XAMPP (as a Web server tool) and the encoding used in this software development is the PHP CodeIgniter framework (as the backend), Highcharts (as Dashboard views) and DataTables (as table views). In this study, authors build software that is expected to help the Directorate of Development (RPE) in conducting evaluation activities in IDX. The analysis of the study uses variables from budget-realization data and activity categories as comparators to figure out the activity status. The study also used IDX activity data in 2018 to implement a built-in system. The results of this study show that the realization of the budget and category of this activity strongly affects the activities that will be evaluated or not evaluated. Activities in each of the IDX representative offices are also potentially to be evaluated, depending on the value of the budget specified in the training data set.
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Implementation of Particle Swarm Optimization Algorithm in VHDL for Digital Circuits Optimization
Статья научная
In order to accomplish the targets of specified levels for reducing the hardware requirements of digital systems, innovative techniques are required to be implemented either at the device level, architectural level or gate level designs. In this paper one of the evolutionary techniques i.e. Particle Swarm Optimization Algorithm has been used to optimize digital circuits at the gate level on VHDL platform to draw an automatic, generalised and reliable technique to find optimum solutions with reduced gate count for the designing of digital systems.
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Improving Fault-Tolerant Load Balancing Algorithms in Computational Grids
Статья научная
Fault tolerant scheduling of many jobs in an environment with millions of unpredictable nodes is not an easy issue. To the best of our knowledge, no work in the literature has proposed a solution that combines the merits of active and passive replication schemes of fault tolerance with the advantages of performance-driven load balancing so as to make the most of the strong points of each. While extensive fault tolerant scheduling and load balancing methods have been presented for the sequential jobs, none have taken into account fault-tolerant load balancing that minimizes the job make-span, provides efficient network and node utilization, achieves a Ill-balanced load and high system flexibility even during the resource failures. Hence, in this article, I present an Adaptive Scheduling Algorithm namely ASA that overcomes these problems. With thorough simulations, I conclude that ASA allocates any number of jobs to a million nodes with relatively low overhead and high flexibility. Experimental results show that the performance of ASA is better than those of its counterparts.
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Increasing ERP Implementation Success Ratio by Focusing on Data Quality & User Participation
Статья научная
ERP systems projects have been spread widely across many organizations in general and small and medium enterprises (SMEs) in particular. Regrettably, failures were the results for most of the ERP implementations. As a result of that, critical failure and success factors (CFFs & CSFs) have been identified with the help of large number of researches. Accordingly, data quality and user participation were categorized as two of the most critical factors that threaten the success of the ERP projects. In order to raise the success percentage of such projects, a data cleansing methodology and some guidelines for user participation have been proposed.
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Indicator Automation with Power BI in the Innovation Sector of a Transformer Company
Статья научная
The use of indicators is increasingly common, as they allow the visualization and analysis of useful data to assist in decision-making and planning. In this context, this article aimed to evaluate the process of automating indicators in the area of innovation in a multinational company located in Brazil, a transformer manufacturer. To this end, the themes of indicators and the application of Business Intelligence (BI) and process automation for project manager functions were conceptualized. The action research methodology developed automated indicators to facilitate decision-making and improve the productivity of the project team. These results also allowed for the improvement of visual and systemic management, by presenting all current projects and information on the occupancy rate of each team member, in addition to real-time control of whether goals are being achieved in the company. Thus, it was evident that centralizing data helps managers make more assertive decisions and the case reported can be replicated to other industrial sectors. In the academic sphere, the research also contributed to the evolution of the topic of project integration, automation and visual management of indicators using the Power BI tool.
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Information Technology for the Data Integration in Intelligent Systems of Business Analytics
Статья научная
The purpose of the research is to develop mathematical models, solution methods and layouts of tools for problems solving of integrating information resources and creation of intelligent systems of business analytics based on effective models. These problems can be solved by automating the business processes execution and introducing artificial intelligence components into the business processes management systems. It can be said that the essence of the modern stage of the business processes modelling systems development is the transition from mainly manual (or with the use of auxiliary software) methods of business processes analysis to mainly automatic management of the business processes execution, construction of intelligent business processes networks in the interconnected conceptual models’ set form that encapsulate knowledge about the structure, the business processes features, system events, limitations and dependencies and are processed by machine. Decision-making powers are delegated to such information system in clearly defined (most often simple, routine) situations. So, in this way, it is possible to form the information resource of intelligent systems of business analytics as a single coherent set of data, suitable for use in solving a wide range of multifaceted problems. The integration approach of forming information resources has certain advantages over other approaches, in particular, regarding the information resources of intelligent systems of business analytics. The use of integration as a means of forming a set of consistent data has certain advantages, namely, it allows: combine data of different formats, content and origins in a single, consistent set; combine data without converting them to a single format, which is especially important when such conversion is difficult or impossible; creates virtual custom images of data that do not depend on their real appearance; creates opportunities to operate both real physical and virtual data in their combination; dynamically supplement, change and transform both the data itself and their descriptions; to provide uniform methods and technologies of perception and application of a large amount of various data.
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Instructor’s Performance:A Proposed Model for Online Evaluation
Статья научная
Currently due to high awareness and quality audits, the higher education institutions have made to keep a track on various performances of the institutions. One such most important activity that has to be analyzed and evaluated is Instructor’s classroom performance. As the students are the main stakeholders of the educational process, their concerns over the instructor, teaching pedagogies and methodologies, assessment techniques need to be collected and analyzed for achieving the institution’s goals and objectives. The students shall give their opinions related to the various performance indicators of instructor.In general, the higher education institutions use various techniques to evaluate instructor’s performance in the classroom from the students. The latest technological developments help in data collection using web technologies. Online system with required questionnaire and attributes will help the higher education institutions in easy data collection. Apart from that the students shall give their opinions without any fear from any place and at any time. In this paper, we have identified the major factors and users of an instructor online evaluation system. Also, we have proposed a model for such system with subsystem interface, entity relationship diagram and context diagram.
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Integrating Asymmetric Cryptographic Digital Wallet for Online Services in Nigeria
Статья научная
Online stores have integrated one or more payment gateways on their website to facilitate the transaction of goods and services. In the Nigerian case, many physical stores are moving online. However, there is a gap in the payment methods which have slowed down business due to limited payment methods, charges incurred on gateways, and insecurity of websites. This paper is tailored towards the security of online transactions, reduced credit card usage and yet accentuation of cashless policy in Nigeria. Inline with the above stated, this paper proposed a secured digital wallet using cryptography to proffer a solution to exposing confidential information to different sites and curb fraudulent actions. By means of qualitative and quantitative research approach, data on user transactions were collected through google survey forms on how often they make transactions, 91.3% shop online but only 48.1% shop very often and 55% of sample questioned security of online payment, from the quantitative facts above, a larger percent of people who uses financial tools in their shopping activities have more security concern which this study solely aim at. In response to the corncern in the preceeding clauses, a mathematical model was formulated to generate keys for the wallet using an asymmetric cryptography scheme to improve the security process while using an online service. Furthermore, wallet referred in this paper uses the fund preload techniques which limits how often users needs to swipe their credit card for an handshake with the commercial banks, the end goal thus strengthen the Nigeria cashless policy. This paper generated encryption and decryption keys from the extension of the Euclid theorem and implemented a system that can generate keys for fund and asset transfer with the crypto service. The system was tested using unit testing and alpha and beta testing to assert the aims of the research. The result showed that digital wallet usage reduces the exposure of sensitive information on funds and allows using the account on different sites.
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Integrating QR Code to e-Class System for Managing Attendance Lecture Services in Higher Education
Статья научная
Currently attendance is still done manually by recapping each lecturer's attendance sheet. The method used is the prototype method and testing using the User Acceptant Test (UAT) method. This takes a long time, even misinterpretations of existing absences sometimes cause problems when giving salary receipts to lecturers, besides that, reporting to campus management also takes time. The lecturer attendance system can help the finance department to calculate lecturer teaching attendance faster and more easily, which can be used to calculate salaries and evaluate lecturer attendance. The system at the implementation stage and during implementation the average teaching attendance of lecturers is easier to control. Some of the features in this attendance system include Check-in, Lecturer, profile, History, Schedule, Help, Tutorial and Chat Group. Apart from that, the main menu also provides information regarding the check-in time limit, waiting time for the next check-in, campus information, and application updates. The system was built with a QR Code and is Android-based to make things easier for lecturers, admin, and the finance department.
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Integration of Heterogeneous Cloud Storages through an Intermediate WCF Service
Статья научная
Many organizations provide computing resources or services to the client like hardware, software, storage etc. Storage is one of important service that is popular and commonly used today and it provides storage space online to store the data. Service providers give a storage space to consumers on the basis of renting criteria with a trust of high and powerful security. Consumer and organizations uses these storages to secure own personal data. There are many reasons come across that causes to move data from one place to another. Some of them are: reconstruction of storage, backup, new technologies, security etc. So, data migration, data transfer between different cloud storages, often requires. Achieving mechanism of Data migration between clouds is very difficult because of its different architecture to store data. For example Window Azure cloud storage creates a primary key name ID automatically whenever a new table is created. Architecture of cloud storage is depending upon its implementation done by corresponding cloud vendors (like Microsoft). The main vision of this research work is to provide an intermediate service to move the data between both homogeneous and heterogeneous cloud storages. This intermediate service is a two way strategy that built in a SOA technology called WCF that helps the clients, organizations to move data between same and different cloud storages (Window Azure and Go Daddy cloud storages mainly used in this research work).
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Intelligent Network Architecture Development for E-Business Processes Based on Ontological Models
Статья научная
The use of ontological models for intelligent systems construction allows for improved quality characteristics at all stages of the life cycle of a software product. The main source of improvement in quality characteristics is the possibility of reusing the conceptualization and code provided by the corresponding models. Due to the use of a single conceptualization when creating various software products, the degree of interoperability and code portability increases. The new-generation electronic business analytics systems implementation is based on the use of active models for business processes (BP). Such models, on the one hand, reflect the BPs taking place in the organization on a real-time scale, and on the other hand, embody corporate and other regulatory rules and restrictions and monitor their compliance. The purpose of this article is to research the methods of presenting and building active executable BP models, determining the methods of their execution and coordination, and building the resulting intelligent network of BP models. In the process of its implementation, such a network ensures the implementation, support of decision-making and compliance with regulatory rules in the relevant real BPs. A formal specification of an intelligent system for modelling a complex of BPs of the enterprise using models has been proposed. A hierarchical approach to the introduction of intelligent functions into the modelling system has been proposed. The simulation system is designed to be used for the design and management of complex intelligent systems. Achieving the set goal involves solving several development tasks: methods of presenting BP models for different types of such models; methods of analysis and display of time relations and attributes in BP models; ways of presenting the association of artefacts, and business analytics models with individual BP operations; metric ratios for evaluating the quality of process execution; methods of interaction of various BPs and coordination of their implementation. The purpose of functioning an intelligent model-driven software system is achieved through the interaction of a large number of simple models. At the same time, each model encapsulates a certain aspect of the expert's knowledge about the subject area. To apply executable conceptual models in the field of modelling BPes, it is necessary to determine the types of conceptual models used, their purpose and functions, and the role they play in the operation of an intelligent system. Models used in modelling BPes can be classified according to various characteristics. At the same time, the same model can be included in different classifications.
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Статья научная
Refer to this paper, an intelligent-fuzzy feed-forward computed torque estimator for Proportional-Integral-Derivative (PID) controller is proposed for highly nonlinear continuum robot manipulator. In the absence of robot knowledge, PID may be the best controller, because it is model-free, and its parameters can be adjusted easily and separately and it is the most used in robot manipulators. In order to remove steady-state error caused by uncertainties and noise, the integrator gain has to be increased. This leads to worse transient performance, even destroys the stability. The integrator in a PID controller also reduces the bandwidth of the closed-loop system. Model-based compensation for PD control is an alternative method to substitute PID control. Computed torque compensation is one of the nonlinear compensator. The main problem of the pure computed torque compensator (CTC) was highly nonlinear dynamic parameters which related to system’s dynamic parameters in certain and uncertain systems. The nonlinear equivalent dynamic problem in uncertain system is solved by using feed-forward fuzzy inference system. To eliminate the continuum robot manipulator system’s dynamic; Mamdani fuzzy inference system is design and applied to CTC. This methodology is based on design feed-forward fuzzy inference system and applied to CTC. The results demonstrate that the model base feed-forward fuzzy CTC estimator works well to compensate linear PID controller in presence of partly uncertainty system (e.g., continuum robot).
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Статья научная
During the implementation of the work on the creation of the system of tonality recognition and text categorization in the news, a study of the subject area was conducted, which allowed the understanding of the processes of text analysis in the mass media to be enriched. The necessary data for further processing was found. The work resulted from a program that consists of an information parser, a data analyser and cleaner, a Large Language Models model, a neural network, and a database with vectorized data. These components were integrated into the user interface and implemented as a program window. The program can analyse news texts, determining their tone and categories. At the same time, it provides the user with a convenient interface for entering text and receiving analysis results. Therefore, the created system is a powerful tool for automated analysis of textual data in mass media, which can be used for various purposes, including monitoring the news space, analysis of public opinion, and others. Also, the developed information technology successfully meets the set tasks aimed at tonality analysis and categorization of news. It effectively solves the task of collecting, analysing and classifying news materials, which allows users to receive operational and objective information. Its architecture and functionality allow for easy changes and additions in the future, making it a flexible and adaptable tool for news analytics and decision-making in various business sectors.
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Intergovernmental Allocation of Public Resources, Fiscal Decentralization and Economic Growth
Статья научная
Incorporating a two-level government structure into an endogenous growth model, we discussed the growth impacts of different intergovernmental allocation of public resources, i.e. intergovernmental transfer payments and the power of revenue autonomy of the lower-level government, along with fiscal decentralization. we showed that (1) there was an “Inverted U-shaped” relationship between fiscal decentralization and economic growth; (2) Different intergovernmental allocation of public resources does not affect the “Inverted U-shape” relationship between fiscal decentralization and economic growth.
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Internal Control Improvement for Creating Good Governance
Статья научная
Cooperative, which support the national economy of Indonesia, still has many problems. In 2015 the report by the Ministry of Cooperatives and SMEs shows many cooperatives are inactive because of having incompetence. Some issues such as the value of savings that do not fit between the cooperative and its customers, embezzlement of customer funds by parties who are not responsible, refunds troubled loans so that the cooperative suffered losses. These problems will be used as a critical point to do mapping with COBIT 5 framework. Based on the result of this mapping, it will be prepared internal control based on the framework of possible internal controls such as COBIT(Control Objective for Information & Related Technology), COSO(Committee of Sponsoring Organizations), ITIL(IT Infrastructure Library) and national regulations that are prevailing in Indonesia. Control is expected to discuss the internal problems that occurred in each business process that used in the cooperative.
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Interoperability in Nigeria Healthcare System: The Ways Forward
Статья научная
Interoperability of health related information is one of the agendas of many counties in the world, with no exception to Nigeria and other developing countries. This is because healthcare costs are rising exponentially. However, interoperability of health related information seem largely unattainable in Nigeria due to reluctance to change from the traditional paper based healthcare system to the use of e-health systems, inadequate ICT infrastructure, poor utilization of the available ICT resources, erratic power supply, increased burden of underdevelopment, poverty, political instability, shortage of educational capacity in Nigeria rural and urban healthcare centers, low level of ICT awareness, poor maintenance culture as well as corruption. Consequently, the healthcare system in Nigeria is saddled with high cost, high rate of disease outbreak driven by HIV/AIDs, malaria and other infectious diseases which results in a high rate of mortality. Nevertheless, the urgent need to meaningfully exchange safe and reliable health information is a key priority to the healthcare system in Nigeria as the qualities of patients’ care depend majorly on the timely acquisition, processing and retrieval of data related to the patient. Thus, this paper attempts to unravel the factors hindering interoperability in the Nigeria healthcare system and suggests ways of making total interoperability a reality in Nigeria healthcare system as well as other developing countries.
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Статья научная
Neutrosophic set is a power general formal framework, which generalizes the concept of the classic set, fuzzy set, interval valued fuzzy set, intuitionistic fuzzy set, and interval intuitionistic fuzzy set from philosophical point of view. In Geographical Information Systems (GIS) there is a need to model spatial regions with indeterminate boundary and under indeterminacy. In this paper, we first gives fundamental concepts and properties of a neutrosophic spatial region.
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Investigation of Machine Learning Algorithms for Network Intrusion Detection
Статья научная
Network intrusion is an increasing major concern as we are rapidly advancing in technology. To detect network intrusion, Intrusion Detection Systems are required. Among the wide range of intrusion detection technologies, machine learning methods are the most appropriate. In this paper we investigated different machine learning techniques using NSL-KDD dataset, with steps of building a model. We used Decision Tree, Support Vector Machine, Random Forest, Naïve Bayes, Neural network, adaBoost machine leaning algorithms. At step one, one-hot-encoding is applied to convert categorical to numeric features. At step two, different feature scaling techniques, including normalization and standardization, are applied on these six selected machine learning algorithms with the encoded dataset. Further in this step, for each of the six machine learning algorithms, the better scaling technique application outcome is selected for the comparison in the next step. We considered six pairs of better scaling technique with each machine learning algorithm. Among these six scaling-machine learning pairs, one pair (Naïve Bayes) is dropped for having inferior performance. Hence, the outcome of this step is five scaling-machine learning pairs. At step three, different feature reduction techniques, including low variance filter, high correlation filter, Random Forest, Incremental PCA, are applied to the five scaling-machine learning pairs from step two. Further in this step, for each of the five scaling-machine learning pairs, the better feature reduction technique application outcome is selected for the comparison in the next step. The outcome of this step is five feature reduced scaling-machine learning pairs. At step four, different sampling techniques, including SMOTE, Borderline-SMOTE, ADASYN are applied to the five feature reduced scaling-machine learning pairs. The outcome of this step is five over sampled, feature reduced scaling-machine learning pairs. This outcome is then finally compared to find the best pairs to be used for intrusion detection system.
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Investigations of Cellular Automata Game of Life Rules for Noise Filtering and Edge Detection
Статья научная
In digital image processing, edge detection of images is an important and difficult task. Also, if the images are corrupted by noise, it smears some details and thus resulting in inaccurate edge detection. Hence, a pre-processing step must be taken before the edge detection. In this paper a new approach for edge detection with noise filtering of digital images using Cellular Automata Game of Life is presented. This procedure can easily be generalized and used for any type of digital media. To illustrate the proposed method, some experiments have been performed on standard test images and compared with popular methods. The results reveal that the proposed method has relatively desirable performance.
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IoT Based Smart Energy Consumption Prediction for Home Appliances
Статья научная
Optimizing energy management for household appliances is essential for maximizing domestic energy utilization and enabling preventive maintenance. Recent studies indicate that traditional forecasting approaches frequently lack the necessary accuracy and real-time learning capabilities required for effective management of household energy. This study demonstrates the implementation of a comprehensive strategy that integrates Internet of Things (IoT) data, machine learning (ML), and explainable artificial intelligence (XAI) to improve the accuracy and interpretability of predicting energy usage in residential buildings. Our research focuses on the rising issues faced by IoT-based smart systems, partic- ularly the deficiencies in the performance of current solutions. Therefore, as compared to the other 17 models that were examined, polynomial regression demonstrated outstanding performance. Our solution utilizes a non-intrusive sensor to collect data without disrupting its operation. Real-time data collecting is achieved through a Flask-based web page with Ngrok for external access.The efficacy of the proposed system was assessed using many metrics, yielding highly satisfac- tory results: the root mean square error (RMSE) was 0.03, the mean absolute error (MAE) was 0.02, the mean absolute percentage error (MAPE) was 0.04, and the coefficient of determination (R²) was 0.9989. However, modern cutting-edge methods still face considerable hurdles when it comes to interpretability. In order to tackle these problems, we include XAI techniques such as SHAP and LIME. Explainable Artificial Intelligence (XAI) improves the interpretability of the model by elucidating the impact of various variables on energy consumption forecasts. Not only does this increase the effectiveness of the model, but it also promotes comprehension of the data and enables them to identify the elements that influence home energy usage.
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