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: 82
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..
IJIEEB Vol. 16, No. 5, Oct. 2024
REGULAR PAPERS
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.
[...] Read more.In this paper, we take Industrial IoT (IloT) as a main point, where we touch on the direction of Industrial IoT concepts and connectivity protocols used by Industrial IoT devices. Moreover, we go into deep security challenges the Industrial ecosystem faces. Nowadays, most industries focus on specific protocols in their smart IoT devices. In return, we mainly focus on Message Queuing Telemetry Transport (MQTT) protocol, MQTT server where IoT devices are connected to it, and secure connectivity among server, cloud, and end user. Our purpose here is to describe the security approach for server and cloud-based environments and the utilization of cloud security tools such as IoT-hub, Network Security Group (NSG) and virtual private network (VPN). In more detail, here we have indicated proposed solution by separating into device, on-premises and cloud zone sections, proper technologies which are being used in modern security approaches and comparison with traditional IoT security approaches. This article enables readers to obtain fundamental knowledges on available technologies which are utilized in industrial areas and real-time scenarios where this solution is deployed.
[...] Read more.Recent advancements in pest classification using deep learning models have shown promising results in various agricultural contexts. The VGG16 model, known for its robust performance in image classification, has been applied to the task of classifying pests in oil palm plants. This study aims to evaluate the effectiveness of the VGG16 model in identifying pests on oil palm, comparing the performance of default settings with models fine-tuned using grid search and random search techniques. We employed a quantitative approach, training the VGG16 model with three different configurations: default, fine-tuned with grid search, and fine-tuned with random search. Evaluation metrics including precision, recall, F1-Score, and overall accuracy were used to assess model performance across different pest categories: Metisa plana, Setora nitens, and Setothosea asigna. The default VGG16 model achieved precision, recall, and F1-Score values around 90% for Metisa plana, Setora nitens, and Setothosea asigna, with an overall accuracy of 91.00%. Fine-tuning with grid search improved these metrics, with precision, recall, and F1-Score reaching approximately 93.88%, 92%, and 92.93% respectively, and an overall accuracy of 93%. The random search fine-tuning resulted in even higher performance, with precision of about 95.92%, recall of 94%, and F1-Score of 94.95% for Metisa plana, and overall accuracy of 94.67%. The VGG16 model demonstrated strong performance in pest classification on oil palm, with significant improvements achieved through fine-tuning techniques. The study confirms that grid search and random search fine-tuning can substantially enhance model accuracy and efficacy. Future research should focus on expanding the dataset to include more diverse pest species, incorporating attention mechanisms, and leveraging automated control technologies like drones and the Internet of Things (IoT) to further improve pest management practices.
[...] Read more.This research explores the integration of artificial intelligence (AI), the internet of things (IoT), and smart technologies in sustainable development. The study identifies the applications of AI in waste management, smart cities, energy optimization, the green internet of things (GIoT), environmental resilience, pollution mitigation, and sustainable agriculture practices. The research emphasizes the need for a comprehensive approach to harness the potential of AI and IoT for sustainable development. The study also highlights the economic, social, and environmental dimensions of sustainable development and the implications of AI in these areas. The findings suggest that AI can contribute to inclusive and responsible economic growth, social equity and well-being, environmental conservation, and efficient resource utilization. The research provides valuable insights for researchers, practitioners, and policymakers working on sustainable development.
[...] Read more.The article proposes a method for clarifying the degree of correspondence between the request of a company looking for a specialist for a vacant position and the request of an applicant. As practice shows, the requirements in the requests of companies and the requests of applicants are linguistic, using vague boundaries of compliance parameters. Based on the results of a survey of graduate students and representatives of potential employer companies conducted by the author of the work, the company’s image, its experience in the market, and a decent salary are significant for graduates. For potential employers, applicants with some experience in the branch and low financial expectations are substantial first of all. Thus, from the statements of both sides, the author managed to identify two linguistic variables: “Time” and “Salary level.” These variables are applied to identify correlations between requests at the preliminary stage of staff selection. Indirect methods, namely methods of statistical data and expert assessments, were used in the variable membership functions. The algorithm for detecting matches is noticeably simple and can be in almost any table processor, which expands the field of the proposed approach. The recruitment agency acts as an intermediary in recruitment. The algorithm for identifying compliance in its activities will significantly reduce recruiters’ time and labor costs.
[...] Read more.The increasing ubiquity of Social Internet of Things (SIoT) devices necessitates innovative data aggregation techniques to distill meaningful insights from diverse sources. This study introduces a Dynamic Data Aggregation Model for SIoT devices. The model aims to amalgamate static and mobile device data, employing Density-Based Spatial Clustering of Applications with Noise (DBSCAN) for spatial clustering and Recurrent Neural Networks (RNN) for predicting mobile device movement patterns. The purpose is to offer a holistic approach to predictive analytics in the SIoT domain by seamlessly integrating these methodologies. The model begins with data preprocessing, ensuring data quality. It then applies DBSCAN for spatial clustering, enabling a comprehensive understanding of spatial relationships between devices. Simultaneously, RNNs are used for predictive modeling, specifically in forecasting mobile device movement patterns. The integration of DBSCAN clustering and RNNs forms the model’s innovative core, providing a unified solution for dynamic data aggregation. Comprehensive testing demonstrates the model’s notable accuracy in predicting mobile device movement patterns. By combining the spatial clustering capabilities of DBSCAN with the predictive power of RNNs, the model effectively unifies static and mobile data, advancing predictive analytics in the SIoT context. The proposed model yielded average values of 0.14604 (Mean Squared Error), 2.678385 (Mean Absolute Error), 0.307154 (Root Mean Squared Error), and 1.342317 (Mean Absolute Percentage Error), respectively. The Dynamic Data Aggregation Model proves its efficacy in addressing SIoT challenges. The integration of DBSCAN clustering and RNNs offers a versatile framework for dynamic data analysis, contributing significantly to predictive analytics in SIoT contexts.
[...] Read more.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.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.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.
[...] Read more.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.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.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.
[...] Read more.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.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.
[...] Read more.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.
[...] Read more.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.
[...] Read more.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.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.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.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.
[...] Read more.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.
[...] Read more.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.
[...] Read more.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.
[...] Read more.The article examines the application of e-commerce systems and technologies that have a positive impact on the development of the economy of the post-coronavirus period and the formation of appropriate technical and technological infrastructure for it, as well as promising features and directions of e-commerce. The physical and virtual opportunities created by e-commerce technologies for buyers and sellers are explained. The advantages of e-commerce in the international economic space have been identified. The functions of e-business models in accordance with the commercial stages of enterprises are explained. It was noted that the development of ICT has accelerated the process of transition from traditional commerce to e-commerce, led to the emergence of new global trends in e-commerce. These innovations have raised the issue of the application of modern ICT in the development of e-commerce on the platform of the 4.0 Industrial Revolution. Taking into account these factors, the presented article discusses the application of modern technologies in e-commerce systems, such as 3D modeling, the Internet of Things, artificial intelligence, big data. Features of application and regulation mechanisms of E-commerce systems in real economic sectors, which have a direct stimulating effect on economic growth in Azerbaijan, have been studied. Recommendations were given for the modernization and use of e-commerce systems with the application of the latest ICT technologies.
[...] Read more.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.
[...] Read more.Game is one of the big industries today and can be an alternative entertainment and fun for children and adults. Game can be used as an interactive and interesting learning media. One of the platform game development methods is the Finite State Machine (FSM). This method is used to adjust the behavior of the NPC (Non-Player Character) to guide the player through the game. This study developed an Android-based "Jungle Adventure" game with interesting gameplay to make the learning process very enjoyable so that the player is expected to be able to play while learning. Combination NPC with FSM will make that responses under certain conditions, and NPC will accompany player like a friend survival.
[...] Read more.