Back-end System Research Articles

Using semantic story maps to describe a territory beyond its map

The paper presents the Story Map Building and Visualizing Tool (SMBVT) that allows users to create story maps within a collaborative environment and a usable Web interface. It is entirely open-source and published as a free-to-use solution. It uses Semantic Web technologies in the back-end system to represent stories through a reference ontology for representing narratives. It builds up a user-shared semantic knowledge base that automatically interconnects all stories and seamlessly enables collaborative story building. Finally, it operates within an Open-Science oriented e-Infrastructure, which enables data and information sharing within communities of narrators, and adds multi-tenancy, multi-user, security, and access-control facilities. SMBVT represents narratives as a network of spatiotemporal events related by semantic relations and standardizes the event descriptions by assigning internationalized resource identifiers (IRIs) to the event components, i.e., the entities that take part in the event (e.g., persons, objects, places, concepts). The tool automatically saves the collected knowledge as a Web Ontology Language (OWL) graph and openly publishes it as Linked Open Data. This feature allows connecting the story events to other knowledge bases. To evaluate and demonstrate our tool, we used it to describe the Apuan Alps territory in Tuscany (Italy). Based on a user-test evaluation, we assessed the tool’s effectiveness at building story maps and the ability of the produced story to describe the territory beyond the map.

Building Bridges: Universitas Multimedia Nusantara's Experience in Strengthening Academic Relationships through a Social Community Media Approach

Universitas Multimedia Nusantara has thousands of academicians and several academic or non-academic organizations. Some of these things allow the potential for increased social relationship connections between the academic community and the intensity of receiving and disseminating information, especially for students. Through a survey of students, there are examples of confirmed problems regarding the receipt and dissemination of information such as the lack of exposure of student work, the location of wall magazines that are difficult to find, information on student emails that are less relevant, time-consuming searches for coursework respondents, and the number of social media accounts of organizations that must be searched on different social media platforms to get information. Therefore, the design and development of a social community media website utilizing the Rapid Application Development method, a rapid prototype system development model with the stages of planning, design workshop, and implementation. The focus of the research is the backend system. The backend system design utilizes draw.io to create flowcharts and supabase schema for entity relationship diagrams, while the system development utilizes javascript with next js as the system development tool while system development utilizes javascript with next js as a framework and supabase as the system database. Backend media website backend of the social community media website was successfully designed and built and received User Acceptance Testing results with an acceptance rate of 88.08% for the perceive usefulness and 88.67% for the perceive satisfaction variable, which means that users strongly agree that the function of the social community media website system has fulfilled the two elements of the variable.

Efficient Backend Development with Spring Boot: A Comprehensive Overview

Abstract: This journal paper provides a comprehensive exploration of Spring Boot, a highly sought-after framework in contemporary web application development. It begins by introducing Spring Boot's core concepts, architectural principles, and its capacity to reduce redundant coding efforts. The paper delves into various facets of backend development, focusing on data storage through Spring Data JPA, as well as its adaptability to relational databases. Spring Boot's proficiency in simplifying data source integration and providing efficient data access tools is emphasized. Serving as an invaluable resource, this paper offers developers insights into Spring Boot's pivotal features, benefits, and best practices for crafting scalable, maintainable, and robust backend systems in the ever-evolving landscape of web applications

IoT-Edge Healthcare Solutions Empowered by Machine Learning

Managing the overwhelming volume of data collected by medical sensors presents a challenge in extracting relevant insights. This paper advocates for the development of an algorithm tailored to body sensor networks to identify outliers in collected data. Leveraging machine learning and statistical sampling methodologies, this research aims to optimize real-time response, particularly as computational tasks migrate to backend systems. Addressing the increasing dispersion of computing power across various domains, this study highlights the potential bottleneck posed by computation as Internet-of-Things (IoT) devices proliferate. To mitigate battery drain, a common approach involves offloading processing to background servers. However, the widespread adoption of IoT devices has sparked concerns about privacy and security. Current measures are deemed insufficient in light of escalating cyber threats. Machine learning methods offer promise in identifying vulnerabilities within IoT systems. Edge computing emerges as a solution to enhance network response times, decentralization, and security. By leveraging distributed-edge computing within an IoT framework, this paper investigates the fusion of cloud and edge computing with machine learning. Specifically, it explores how these technologies can be harnessed in the medical field, utilizing sensor-equipped IoT devices to collect extensive data for analysis. The proposed approach involves proactive decision-making at the front end, guided by an IoT server, and employs machine learning algorithms at the backend to identify pertinent data signatures. This paper underscores the significance of combining cloud, edge computing, and machine learning in a distributed-edge-computing-based IoT framework, offering a potential avenue for real-time, efficient solutions in various domains.

Trip Planning and Recommendation System with AI Chatbot

The principle aim of this project is to develop a responsive website, which would comprehend the process of tour planning and management for users. With the increasing popularity of tourism and recreational activities all around the world has increased, there is a need for an advanced and smart tour planning system, which would make it easier for users to plan and execute trips. This proposed website is built in such a way that the user will get to know all aspects related to his trips, and there will be a ChatBot, which would make the booking procedure easier for the user. The Chatbot would suggest the user different destinations based on the user’s area of interest and make the decision-making process more rational. Also, it would help the user to gain more insights about their dream holidays for a smooth trip without any disturbances and mismanagements. Along with the ChatBot, we also integrated a virtual tour feature, which would give users a glance at their dream destinations. The development of the website involves various software integrated using a robust backend system, which will implement and handle the processing and retrieval of travel-related data, ensuring fast and accurate user queries. The front end of the website will be designed to provide an intuitive and visually appealing UI, enhancing the UX. Keywords — Chatbot, virtual tour, user interface, user experience, frontend, backend.

Efficient ship noise classification with positive incentive noise and fused features using a simple convolutional network

Ship noise analysis is a critical area of research in hydroacoustic remote sensing due to its practical implications in identifying ship direction, type, and even specific ship identities. However, the limited availability of data poses challenges in developing accurate ship noise classification models. Previous studies have mainly focused on small-sample learning approaches, resulting in complex network structures. Nonetheless, underwater robots often have limited computing power, making it essential to develop simpler recognition networks. In this paper, we address the issue of data scarcity by introducing positive incentive noise. We propose a CNN-based hydroacoustic signal recognition method that achieves comparable or superior performance to previous studies, using a simple network structure as a back-end decision system. We describe the feature extraction process using a dataset with added noise and compare the performance of various features. Additionally, we compare our proposed method with previous studies. Experimental results demonstrate that simple neural networks can achieve high performance and excellent generalizability without the need for complex network structures like adversarial learning models.

Convolutional neural network for substantiation of children's books, intelligent interactive communication and application analysis of voice question answering

At present, there are many children accompanying robots. A key indicator to measure their performance is convenient and efficient human–computer interaction. The implementation of voice question-answering technology needs to solve three problems: voice recognition, the establishment of a knowledge base, and answer matching. As the front-end data entry, speech recognition accuracy is directly related to the answer-matching effect of the back-end question-answering system. Based on convolutional neural network and intelligent communication technology, this paper analyzes the characteristics of children's reading robot and designs and develops intelligent voice interaction function on the Android platform. The focus of this paper is on Chinese word segmentation and keyword extraction and matching in the interaction function. Further, we designed a simple question-and-answer database for the children's reading robot. In this paper, convolutional neural network connection timing is used as the feature parameter. Through a large number of experiments, the structure of the CNN network is constantly adjusted to minimize the word error rate, optimize the model recognition rate, and better identify users' voice problems.

Enhancing Card Transaction’s Security through Cyber Security

This paper highlights the security issues associated with credit cards and underscores the crucial role of encryption in mitigating the risk of credit or debit card data theft. Credit card encryption encompasses safeguarding the card itself, securing the terminal used for card scanning, and ensuring the protection of card information during transmission between the terminal and a backend computer system. The encryption mechanism is specifically engineered to validate and limit access to card security features. In our project, we developed a web application using VS Code, employing HTML for the frontend and PHP for the backend, and implemented AES encryption as a robust security measure.

A robust IoT-based cloud model for COVID-19 prediction using advanced machine learning technique

Due to the rapid spread of COVID-19, an urgent need arose for a quick and accurate diagnosis approach. The well-known RT-PCR test is often unavailable and too costly for many suspected cases. In contrast, the chest X-ray scan proves to be a robust and efficient tool for promptly identifying the virus, using various cost-effective tests. This study proposes a hybrid intelligent model for identifying COVID-19 patients based on their chest X-ray scans. The proposed model consists of five phases. Firstly, the X-ray images are preprocessed using a median filter to enhance and remove noise. Secondly, robust invariant and high-level engineering features are extracted using five different feature extraction methods, namely (speeded up robust features (SURF), grey-level co-occurrence matrix (GLCM), histogram of oriented gradients (HoG), segmentation-based fractal texture analysis (SFTA), and local binary pattern (LBP) to help in rapid diagnosis. Then these features are fused to complement the gap of each other and to achieve the best performance. Thirdly, a deep convolutional neural network (DCNN) is used to classify the chest X-ray scans of infected COVID-19 patients. Then, the proposed model is compared with different machine learning techniques under different quality measures. Fourthly, an IoT platform composed of a mobile client application and a backend system is designed. The mobile client application captures the content from the patient side, handles these captured images, and prepares them for rapid sending to the backend side for further processing. The backend system receives the patient images from the client side and applies the proposed model to diagnose the COVID-19 patients. Finally, a cloud-based design for the platform utilizes the modern AWS services characterized by availability, elasticity, coverage, configurability, and reliability. The results show that the proposed model has a good accuracy of around (99.31%) and outperforms the other models. Therefore, the proposed model could be used for real-time automatic early recognition of COVID-19 cases.

Enhancing Card Transaction Security through Cyber Security

This paper highlights the security issues associated with credit cards and underscores the crucial role of encryption in mitigating the risk of credit or debit card data theft. Credit card encryption encompasses safeguarding the card itself, securing the terminal used for card scanning, and ensuring the protection of card information during transmission between the terminal and a backend computer system. The encryption mechanism is specifically engineered to validate and limit access to card security features. In our project, we developed a web application using VS Code, employing HTML for the frontend and PHP for the backend, and implemented AES encryption as a robust security measure.

The Use of Geofencing in Android-Based Mobile Applications for Promotional Ads in Shopping Centers

This paper describes the implementation of geofencing technology in Android-based mobile applications for promotional advertisements based on the user's location. Geofencing is a location-based service that uses GPS, cellular networks, or Wi-Fi to create virtual geographic boundaries around specific locations. This technology enables businesses to send targeted advertisements to mobile users based on their current location. The paper presents the development of an Android-based mobile application that uses geofencing technology to provide location-based promotional advertisements to users. Researchers use one of the big shopping centers in Jakarta as a location object for geofencing technology. The application uses Google Maps and Firebase to create geofences around specific locations, and then sends push notifications to users within the geofenced areas. The implementation also includes a backend system to manage the promotional advertisements and user data. The results show that the implementation of geofencing technology in Android-based mobile applications can provide a more targeted and effective way to deliver promotional advertisements to users.

DESIGN AND DEVELOPMENT OF WEB-BASED APPLICATION CANGKINGAN USING SCRUM METHOD


 
 
 The web-based application can ease business owners on promoting and giving the services to the customers. Nevertheless, nowadays there are still not many UMKMs (micro, small, and medium enterprises) in the Banyumas Regency that apply it. Many of them still preserve the conventional way by doing the transaction directly. This research is aimed to design and develop a web-based marketplace application, namely Cangkingan. That application is supposed to help UMKMs in Banyumas in managing inventory, processing orders, and marketing culinary products online. The outline of this research flow includes needs analysis, system design, system development, and system testing. The methods of data collection that are used are interview, observation, literature study, and questionnaire. The application design is created in various diagrams and user interface designs. The method of system development is scrum. This design and development are done within 10 sprints in which each sprint is held for two weeks. The application is built using MySQL, CodeIgniter framework, and PHP language. Testing of Cangkingan system is carried out using the ISO 9126 standard which consists of testing functionality, usability, reliability, efficiency, portability, and maintainability. The test result on most of the test aspects state that the application is satisfactory (good). Especially for the usability testing that is done to 36 respondents, Cangkingan gets excellent result. This test result is one of the proofs that the research purpose has been achieved and the application Cangkingan that has been developed is able to help the UMKMs with culinary products in Banyumas.
 
 

Design and Fabrication of Smart Shelf System

In order to solve an issue that most stores have, this project will use a load cell to measure weight and communicate the weight input to a HX711 converter, which converts the signal to a digital number. The digital value is used to notify the consumer of the stock level. The owner of the shop will receive a notification on their cell phone every time the supply is low telling them to replenish. We have started using PIR sensors to utilize less electricity. Only motion causes a light bulb to turn on. We'll utilize a relay in this case, which uses energy from a power source to turn on or off switch connections. Retailers may employ smart shelves for a variety of purposes, including as better storage, better decision-making, informing the back-end system of the number of products already on the shelf, monitoring product levels, detecting theft, and finding missing items. If necessary, the network of shelves might communicate updated product inventories to shop owners, managers, employees, customers, warehouse personnel, or producers. As a result, there is no need to make an order or conduct a physical inventory count at the warehouse or storeroom.

Prospects of digital scientific publishing on blockchain: The concept of DAP

Background: Traditional publishing models, open access and major publishers, cannot adequately address the key challenges of academic publishing today: Speed of peer review, recognition of work and incentive mechanisms, transparency and thrust of the system. Methods: To address these challenges, the authors propose Decentralised Academic Publishing (DAP), which is based on the novel HashNET DLT platform. The DAP introduces several innovative components: tracking the activities of all participants in the peer review process using blockchain and smart contracts, the introduction of the Scholarly Wallet for holding reputation (non-fungible) and reward (fungible) tokens, the use of the Scholarly Wallet as the main interface to the DAP platform, the Virtual Editor that enables automatic discovery of the research area and invitation of reviewers, and finally the global database of evaluated reviewers, ranked by the quality of their previous work. Results: The DAP platform is in the development phase, with the design and functionalities of all modules defined. An exception is the central component of DAP, the Scholarly Wallet module, whose first prototype has already been created, tested and published. The implementation of DAP is planned for the next phase of the HorizonEurope TruBlo project and other research initiatives. The DAP platform will be connected to the publishing ecosystem: 1) as a backend system (distributed blockchain database) for existing publishing platforms and 2) as a standalone publishing platform with its own API interface. Conclusions: The authors believe that DAP has the potential to significantly improve academic peer review and knowledge dissemination. It is expected that the use of blockchain technology, the fast HashNET consensus platform and tokens for reward (fungible) and reputation/ranking (non-fungible) will lead to a more efficient and transparent way of rewarding all participants in the peer review process and ultimately advance scientific research.

Back-End development on Laboratory Information System in Universitas Riau

Laboratories usually have different tools, materials, documents, and a lot of other content. At the University of Riau, especially the Faculty of Engineering, it is filled with many laboratories. Starting with a computer network laboratory and chemical laboratory, machine laboratory, and many more. Currently information about laboratories cannot be found on the internet, and it is still difficult to access information about laboratories. This research focuses on creating a back-end system that can later be implemented in the development of a laboratory information system. This development process uses the V-Shaped model as a reference in the manufacturing stages. The system that has been made will be tested using the unit testing, integration testing, and system testing methods with ISO 25010 as a reference standard in determining the quality of the tests carried out. The results of testing the system obtained very good results with A results on reliability, maintainability, and security testing. In testing the efficiency of the system in getting a response time 80ms average on each page. White box testing also obtained results that all the features and data in the system were functioning and matched as they should.

Desain Aplikasi Database Sistem Informasi Akuntansi Sekolah pada Yayasan Ainur Rahmah

This study aims to develop an accounting information system database application for Ainur Rahmah Foundation school in West Pasaman, West Sumatra Province. The problem faced by the Ainur Rahmah Foundation is the absent of an information system to manage student data, tuition fees, admission of new students, receipt and disbursement of cash, purchase and use of consumables, acquisition and depreciation of fixed assets. The developed accounting information system database application consists of two main subsystems, namely the back-end and front-end. The back-end system uses DBMS MySQL Server 8.0 while the front-end system is developed using Microsoft Access 2010. Application modules and reports are developed on the front-end using the Visual Basic for Application programming language which is available in Microsoft Access database tools. Applications that have been developed are then tested for use by users to find out if there are errors and adjustments that must be made. After making adjustments based on the user trial stage, the application can be accepted by users and can be operated according to needs.

Research Issues in the Generative Design of Cyber-Physical-Human Systems

Abstract Cyber-physical-human systems (CPHS) are smart products and systems that offer services to their customers, supported by back-end systems (e.g., information, finance) and other infrastructure. In this paper, initial concepts and research issues are presented regarding the generative design of CPHS and CPHS families. Significant research gaps are identified that should drive future research directions. The approach proposed here is a novel combination of generative and configuration design methods with product family design methodology and an explicit consideration of usability across all human stakeholders. The need for a new CPHS transdiscipline is identified. With the proposed approach, a wide variety of CPHS, including customized CPHS, can be developed quickly by sharing technologies and modules across CPHS family members, while ensuring user acceptance. The domain of assistive technology is used in this paper to provide an example field of practice that could benefit from a systematic design methodology and opportunities to leverage technology solutions.

Complaint Box App Implementation Using React Native

Abstract: This paper presents the implementation of a complaint box app using React Native, a cross-platform mobile app development framework. The app allows users to submit complaints and suggestions, while the admin panel enables complaint handlers to manage complaints and communicate with users. The app features user authentication, complaint submission, complaint tracking, and real-time communication, while the implementation involved designing the user interface, integrating it with a backend system and a database, and testing its functionality. The paper discusses the benefits and challenges of using React Native for mobile app development and how it can be leveraged to build scalable and efficient complaint box apps. Overall, this paper presents a practical and effective approach to implementing a complaint box app using React Native with an admin panel, which can help organizations capture user feedback and improve their products and services.

Chatbot Development Through the Ages : A Survey

A chatbot is a computer program that aims to make a conversation between both humans and machines. The chatbot can be utilized in a variety of platforms, including messaging apps and virtual assistants. The chatbot has evolved a lot in decades starting from amusement usage to performing serious tasks. While designing a chatbot, design considerations like purpose, audience, channels, conversational flow, testing and iterations must be taken into account in order to ensure that it is accurate and user-friendly. Based on its domain, model, and conversation style, a chatbot can be categorized into customer-service, sales, informational, personal assistant, entertainment, health and educational chatbot. Chatbot technology continues to face a wide variety of challenges like contextual understanding, integration with backend systems, personalization, security and user acceptance. This paper explores and compares various recent chatbots from different domains that are being used. We have surveyed the entire development process and the different development techniques used to design chatbots and the audience they cater to. We also look at the various evaluation methodologies used in checking the efficiency and enforceability of the considered chatbots.

RFID Technology in Retail: A Study on IoT-Based Shopping Cart System

The emergence of the Internet of Things (IoT) technology has revolutionized various industries, and the retail industry is no exception. The application of IoT technology in the retail sector has led to the development of smart and connected devices that enhance the customer experience and streamline operations. One such application is the IoT-based shopping cart, which uses sensors and microcontrollers to automate inventory management and real-time monitoring. The proposed IoT-based shopping cart is designed to automate and optimize the shopping experience. The RC522 sensor enables accurate and fast RFID scanning of products, which ensures real-time inventory management and tracking. The NodeMCU microcontroller handles data processing and wireless communication with the cloud server, ensuring seamless communication between the shopping cart and the backend system. The system is designed to provide personalized recommendations to customers based on their shopping history, which can enhance the customer experience and increase sales