Web-based System Research Articles

Online Exam Portal

An online test is one that is conducted via the internet or an intranet utilizing a computer system. It is a web-based exam system. It works well as a mass education evaluation solution. Our system for online exams is built on a Browser/Server architecture. The multiple choice questions that are fed into the system are examined and automatically graded by the system. Even while it is comfortable, the classic pen and paper exam format has drawbacks in the current digital learning environment. IT students find these limits even more noticeable because they are used to using internet resources and platforms. In response, this proposal suggests creating an efficient, user-friendly, and safe online assessment system especially for IT students. This project goes beyond practicality. It increases assessment quality with interesting formats, empowers students with freedom, and promotes efficiency with quicker administration and grading. Teachers receive insightful data-driven information for bettering their curricula. In the end, it welcomes the digital age and uses cutting-edge evaluation techniques to get IT students ready for success

DEVELOPMENT OF A WEB-BASED NEW STUDENT ADMISSION INFORMATION SYSTEM

Admission of new students is a routine activity carried out by schools every new school year. This activity aims to advance the school so that in its implementation a selection is needed. This selection is carried out in order to achieve a target of achieving the quality of prospective students. In this new student admission, a committee is needed to facilitate the activity. Currently, not many schools in Indonesia have implemented an online admission system. The purpose of this research is to design a web-based new student admission information system "SIPSB" and facilitate the registration of prospective new students to be more efficient. In designing this new student admission information system, the Object Orientred Analysis and Design (OOAD) method and the waterfall model are used. The use of the waterfall model in this study makes it easier for researchers to design information systems because there are several stages in system development, namely requirements analysis, system design, implementation, system testing, and maintenance. The results of this study show that the new student admission information system "SIPSB" is able to manage the web-based new student admission process more efficiently.

DETEK-AI: A Web-based Deepfake Detection System

AI-driven deepfake bots pose a serious risk to society, security, and trust, which necessitates the development of reliable techniques to detect and mitigate their threat, as their proliferation leads to disinformation, deceit, and harm. Deepfake detection systems can improve cybersecurity, safeguard digital identities, mitigate misinformation, protect reputations of individuals and organizations, assure ethical use of AI technology, empower people and organizations, support regulatory efforts, and contribute to a safer digital ecosystem. Detek AI is a frontrunner in innovative technology aimed at combating deepfake content, safeguarding individuals and organizations from misinformation, and upholding the integrity of online platforms. Keyword— Deepfake Technology, Deepfake Detection, Convolutional Neural Networks, Artificial Intelligence bots, Machine Learning Artificial Intelligence, Face Morphing Detection, Deep Learning, Benford’s Law.

Integrating NLP Chatbot into Career Guidance Web Application

Artificial Intelligence (AI) is the development of computer systems that can perform tasks that typically require human intelligence. The development of an advanced web-based chatbot system involves the integration of various technologies and methodologies to create a seamless conversational interface. Leveraging HTML, CSS, and JavaScript for frontend development, alongside Python Flask framework for backend functionality, the project aims to deliver a robust and intuitive user experience. Key to the system's operation is the incorporation of PyTorch for machine learning, allowing for the implementation of sophisticated natural language processing (NLP) techniques. Through tokenization and stemming using NLTK (Natural Language Toolkit), the system enhances its understanding of user queries, enabling it to provide relevant and contextually appropriate responses. At the core of the system lies a supervised learning model trained on a custom dataset compiled from user interactions. This model utilizes bag-of-words representations and neural network architectures to predict responses based on input text. By continuously refining its predictions through feedback mechanisms, the system improves its accuracy and responsiveness over time, ensuring a more tailored and effective user experience. Voice input functionality, facilitated by speech recognition technology, further enhances user interaction by allowing users to communicate with the chatbot using spoken commands. This feature expands the accessibility and convenience of the system, catering to a broader range of users with varying preferences and abilities. In addition to its conversational capabilities, the system prioritizes security and privacy, implementing robust user authentication mechanisms and secure data storage practices. By adhering to industry best practices and standards, the project aims to instill trust and confidence in users regarding the confidentiality and integrity of their data.User interface design and usability are also key considerations in the development process, with careful attention given to creating an intuitive and visually appealing interface. Through thoughtful design choices and user feedback, the system seeks to optimize the user experience and streamline the interaction flow, ensuring that users can easily navigate and utilize its features. Overall, the project endeavors to create an intelligent and user-friendly chatbot system that enhances communication and interaction between users and technology. By leveraging advanced technologies and methodologies, the system aims to provide personalized assistance and support to users, ultimately improving productivity, efficiency, and satisfaction in various domains and applications

Implementasi Sistem dalam Menghitung Transaksi dan Stok pada Proses Penjualan di Yamaha Anugerah Motor Berbasis Web

The rapid development of technology in the era of Industry 4.0 has made various internet uses essential to fulfill several needs. This includes systems that can assist in the business sector. With the advancement of technology, it greatly aids daily life. The research aims to develop a web-based application to calculate transactions and stock in business. This application can display information related to sales figures, reports, and data management of goods that are user-friendly for business practitioners. The system to calculate transactions and stock can be applied to assist the sales business process. It provides information about available items so that business practitioners can sell goods and view transaction data. This web-based system is operated through a website and uses the internet as a platform to manage and store available data. Researchers used qualitative field research methods to collect profile data and information about the current running systems as supporting elements in application development. For application design, researchers used Visual Studio Code software, which can be used to create websites using programming languages such as HTML, CSS, and JavaScript. The system development method applied is the prototype method. This method was chosen by researchers as it is suitable and meets the needs of the system to be developed. The final result of this research is a web-based application for calculating transactions and stock in the sales process at Yamaha Anugerah Motor. The designed application features displaying information about managing goods and categories, as well as conducting transactions that are directly recorded in sales reports. With this system, one can track transactions and stock levels. Data management for goods is computerized, and reports about transactions and stock can be printed easily. It also facilitates easy restocking of goods.

A Web-Based Assessment and Evaluation System for Architectural Design Studio Modules

Architectural design studio modules are known to be difficult to teach and/or assess. To acquire design skills, typically, students have several design modules during their program and several projects for each module. However, traditional project assessment and evaluation lacks consistency, objectivity and fairness. Furthermore, monitoring student progress over the different projects and over the different modules and different semesters is very difficult and needs much time and effort. This work presents a web-based system developed to support fair rubrics-based assessment and evaluation of design projects and to provide in-depth analysis of students' results. It also links between the results over the different projects and the different modules and provides feedback about students' skills and weaknesses in a simple form thus allowing progressive learning. The system has been tested and evaluated and the results show its simplicity, reliability and effectiveness.

Develop a web-based system using the Naïve Bayes algorithm to predict asphyxia neonatal

Introduction: Most cases of perinatal asphyxia are caused by conditions unrelated to labor. When asphyxia occurs during childbirth, it is usually caused by an obstetric emergency that was not detected during pregnancy. It is essential to prevent asphyxia by identifying the incidence of asphyxia during pregnancy. Several studies have been conducted to identify asphyxia problems developing by predictive models. However, there has been no development of a system for predicting birth asphyxia during pregnancy and carried out in primary health facilities.Purpose: Develop a web-based system using the Naïve Bayes (NB) algorithm to predict asphyxia neonatal using a dataset of antepartum risk factors in primary health facilities.Methods: This study employed research and development, which consists of 4 stages, namely literature study, development stage, expert validity, and trial.Results: A system that health workers in primary health facilities can use to predict asphyxia neonatal and recommend referrals for determining the place of childbirth has been successfully created. The system performance test predicted asphyxia neonatal with all NB evaluation values reaching more than 98%, and the prediction accuracy in the respondent test included in the High Accuracy category (MAPE value 9.06%).Conclusion: The development of a web-based system using the NB algorithm has been proven to be able to predict asphyxia neonatal and can be implemented for health workers as an effort to anticipate delays in handling cases of asphyxia neonatal because of the predicted results along with recommendations for focusing mothers with the risk of babies born asphyxia to find out possible childbirth places.

Epidemiology and outcomes of drug-resistant tuberculosis cases notified in a low-resource district in Kerala, India 2017–2021 – A 5-year retrospective analysis

Objectives: Kasaragod district reports the highest drug-resistant tuberculosis (DR-TB) case notification rates in Kerala. We conducted a cross-sectional study in Kasaragod to describe the DR-TB cases notified from January 2017 to December 2021 and to identify the factors associated with unfavorable treatment outcomes in DR-TB patients. Materials and Methods: We analyzed the programmatic data from the “Nikshay portal” (a web-based patient management information system for [TB] under the National TB Elimination Program), DR-TB treatment cards, and treatment registers available with the district TB center for all the DR-TB patients notified during the study period. We described the DR-TB cases by year, local self-government area (the local administrative setup), age, gender, income level, and treatment outcomes. We compared sociodemographic, anthropometric, and clinical factors among the DR-TB patients with favorable (cured and treatment completed) and unfavorable (died, lost to follow-up, and treatment failure) treatment outcomes. Results: From January 2017 to December 2021, 128 DR-TB cases were notified from Kasaragod. Annual notification rates varied from 1.4 to 3.4/100,000 population with the highest notification in 2019. The proportion of new TB cases notified tested for drug sensitivity rose from 22% in 2017 to 86% in 2021. Seven of 41 local self-government areas had not notified DR-TB cases during 2017–2021. The notification was higher in inter-state border areas and the coastal belt of the district. The notification of DR-TB cases was highest among the 45–59 age group (17/100,000), followed by the 60 above group (11/100,000). Males and those living below the poverty line had higher notification rates. Among the outcomes evaluated 118 DR-TB patients, 89 (75.4%) had favorable outcomes, whereas the remaining 24.6% had unfavorable outcomes (death 18 [15.3%], loss to follow-up 7 [6%], and treatment failure 4 [3.4%]). Age more than 45 years adjusted odds ratio (aOR) 3.1 (95% confidence interval [CI] 1.1–8.8), income category below the poverty line aOR 6 (95% CI 1.2–28.6), admitted at least twice during treatment aOR 9.2 (95% CI 2.8–30.3), and body mass index at diagnosis <18.5 kg/m2 aOR 3 (95% CI 1.1–10.3) were found to be significantly associated with unfavorable treatment outcomes. Conclusion: DR-TB notifications have increased in the Kasaragod district from 2017 to 2021, with a high burden among males aged 45 years and above. The favorable treatment outcome is better than the national and state average. Regular monitoring and follow-up of multidrug-resistant patients with low incomes, above 45 years, and underweight may improve the final treatment outcomes.

Modeling of web-based collaborative learning management system

The challenges faced by most learning management systems (LMS) can be classified into two main areas: pedagogical and technical issues. A comprehensive exploration of these interrelated challenges provides valuable insights for developing a new and more effective model for LMS. In this paper, a novel conceptual model for a web-based collaborative LMS is introduced, merging two distinct learning theories: behaviorism and social constructivism. Through an analysis of the strengths and limitations of each theory, the study moves on to outline the fundamental principles and technical features of the proposed LMS model, which stems from this integration. In conclusion, the paper explores the implications of creating user-centered LMS solutions, with a specific focus on addressing the varied requirements of learners.

Trastuzumab deruxtecan versus treatment of physician's choice in patients with HER2-positive metastatic breast cancer (DESTINY-Breast02): patient-reported outcomes from a randomised, open-label, multicentre, phase 3 trial

In DESTINY-Breast02, patients with HER2-positive unresectable or metastatic breast cancer who received trastuzumab deruxtecan demonstrated superior progression-free and overall survival compared with those receiving treatment of physician's choice. We present the patient-reported outcomes (PROs) and hospitalisation data. In this randomised, open-label, phase 3 trial conducted at 227 clinical sites globally, enrolled patients had to be aged 18 years or older with HER2-positive unresectable or metastatic breast cancer that had progressed on trastuzumab emtansine and had an Eastern Cooperative Oncology Group performance status of 0 or 1. Patients were randomly assigned (2:1) using block randomisation (block size of 3) to receive trastuzumab deruxtecan (5·4 mg/kg intravenously once every 21 days) or treatment of physician's choice by an independent biostatistician using an interactive web-based system. Patients and investigators remained unmasked to treatment. Treatment of physician's choice was either capecitabine (1250 mg/m2 orally twice per day on days 1-14) plus trastuzumab (8 mg/kg intravenously on day 1 then 6 mg/kg once per day) or capecitabine (1000 mg/m2) plus lapatinib (1250 mg orally once per day on days 1-21), with a 21-day schedule. The primary endpoint, which was progression-free survival based on blinded independent central review, has previously been reported. PROs were assessed in the full analysis set (all patients randomly assigned to the study) using the oncology-specific European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30), breast cancer-specific EORTC Quality of Life Questionnaire Breast 45 (QLQ-BR45), and the generic HRQoL EQ-5D-5L questionnaire. Analyses included change from baseline and time to definitive deterioration for PRO variables of interest and hospitalisation-related endpoints. This study is registered with ClinicalTrials.gov, NCT03523585, and is closed to recruitment. Between Sept 6, 2018, and Dec 31, 2020, 608 patients were randomly assigned to receive either trastuzumab deruxtecan (n=406; two did not receive treatment) or treatment of physician's choice (n=202; seven did not receive treatment). Overall, 603 patients (99%) were female and five (<1%) were male. The median follow-up was 21·5 months (IQR 15·2-28·4) in the trastuzumab deruxtecan group and 18·6 months (IQR 8·8-26·0) in the treatment of physician's choice group. Median treatment duration was 11·3 months (IQR 6·2-20·5) in the trastuzumab deruxtecan group and approximately 4·5 months in the treatment of physician's choice group (4·4 months [IQR 2·5-8·7] with trastuzumab; 4·6 months [2·1-8·9] with capecitabine; and 4·5 months [2·1-10·6] with lapatinib). Baseline EORTC QLQ-C30 global health status (GHS) scores were similar with trastuzumab deruxtecan (n=393) and treatment of physician's choice (n=187), and remained stable with no clinically meaningful change (defined as ≥10-point change from baseline) over time. Median time to definitive deterioration was delayed with trastuzumab deruxtecan compared with treatment of physician's choice for the primary PRO variable EORTC QLQ-C30 GHS (14·1 months [95% CI 10·4-18·7] vs 5·9 months [4·3-7·9]; HR 0·5573 [0·4376-0·7099], p<0·0001) and all other prespecified PROs (EORTC QLQ-C30 subscales, EORTC QLQ-BR45 arm and breast symptoms, and EQ-5D-5L visual analogue scale). Patient hospitalisation rates were similar in the trastuzumab deruxtecan (92 [23%] of 406) and treatment of physician's choice (41 [20%] of 202) groups; however, median time to hospitalisation was 133 days (IQR 56-237) with trastuzumab deruxtecan versus 83 days (30-152) with treatment of physician's choice. Overall, GHS and quality of life were maintained for both treatment groups, with prespecified PRO variables favouring trastuzumab deruxtecan over treatment of physician's choice, suggesting that despite a longer treatment duration, there was no detrimental impact on patient health-related quality of life with trastuzumab deruxtecan. When considered with efficacy and safety data from DESTINY-Breast02, these results support the overall benefit of trastuzumab deruxtecan for patients with HER2-positive unresectable or metastatic breast cancer previously treated with trastuzumab emtansine. Daiichi Sankyo and AstraZeneca.

Perancangan Sistem Informasi Perpustakaan Berbasis Web SMK Negeri 3 Karawang

Perancangan Sistem Informasi Perpustakaan Berbasis Web SMK Negeri 3 Karawang

The Structure of Open and Distance English Language Teaching Models: A Follow Up Study 2018 – 2023

In recent years, the widespread adoption of Open and Distance Learning (ODL) has revolutionized education, especially English language teaching. ODL has democratized access to educational resources and enables interaction between students and instructors across geographical boundaries. Moreover, technology integration has emerged as a dominant theme, with a focus on web-based, computeraided, and mobile-learning systems. However, the study advocates for innovative approaches, such as mobile and game-based learning, aligning with contemporary trends. The adoption of various evaluation methods shows the recognition of individual differences and underscores the need for a comprehensive view of learner progress. This research employs a systematic approach to review literature and investigate the common structures of ODL models for teaching the English language, focusing on articles published between 2018 and 2023. This study categorizes studies based on five macro dimensions of ODL —management, communication, learning, technology, and evaluation—in order to identify common themes and patterns within the literature. In contrast to a previous study spanning 1990 to 2017, this investigation uncovers the evolving landscape of distance education, underscoring the need for continued research and improvement. This research emphasizes the lack of a comprehensive management model for EFL education delivered through ODL, and suggests the need for further investigation in this domain. Moreover, the findings emphasize the significance of leveraging diverse communication models to enhance learner engagement. A shift towards autonomous learning models is observed, demanding further investigation into strategies that support effective self-directed learning experiences. In conclusion, this comprehensive analysis provides a roadmap for advancing ODL models in English-language education. To enhance the quality and accessibility of English language instruction in ODL, educators and researchers can concentrate on addressing management gaps, optimizing communication strategies, promoting autonomous learning, exploring advanced technologies, and refining evaluation approaches. This research offers a rich repository of knowledge for educators, researchers, and academic institutions that wish to deepen their comprehension and practical application of ODL approaches in the domain of English language instruction

Web-Based POS with Apriori Market Basket Analysis

This research project focuses on the design and development of a web-based Point of Sale (POS) application that incorporates advanced analytical techniques, specifically Market Basket Analysis with the Apriori algorithm and the Association Rule method. The primary objective of this web-based POS system is to empower retailers in managing their sales transactions efficiently and gaining valuable insights into customer purchasing behavior. The web-based POS application is multifaceted, offering features such as sales transaction recording, product inventory management, and customer data tracking. What sets it apart is the integration of the Apriori algorithm and Association Rule method, which enable the system to analyze and understand customer purchasing patterns. It identifies strong product associations and establishes rules that support intelligent decision-making for businesses. The advantages of Market Basket Analysis are substantial. Retailers can identify relevant purchase patterns, such as frequently co-purchased products or cross-selling opportunities. This information can be used to enhance marketing strategies, optimize product placement in stores, and create bundled product offerings, ultimately boosting sales and revenue. By analyzing transaction data and recognizing patterns, retailers can streamline their operations, minimize wastage, and allocate resources more effectively. In summary, this research project showcases the transformative potential of integrating Market Basket Analysis, the Apriori algorithm, and the Association Rule method into web-based POS systems. By doing so, retailers can enhance operational efficiency, boost sales, and improve customer satisfaction, ultimately leading to more successful and competitive businesses in the retail sector.

Pengembangan Sistem E-learning Berbasis Web Pada Sekolah Tingi Teknologi Informatika Sony Sugema

Sony Sugema College of Information Technology is one of the educational institutions that has a data processing system, so it requires that all data can be processed properly, stored in an orderly manner and its origin can be easily traced. However, the academic system used still has shortcomings, namely not optimal course participation, management of student data, teacher data, course schedules, course allocation and the absence of an online learning system throughout the semester. Then, to overcome deficiencies in the academic system, the author aims to develop the academic system of the Sony Sugema College of Information Technology using the Waterfall software development method. Then develop a system using the Hypertext Preprocessor (PHP) programming language, MySQL database and bootstrap framework, as well as Visual Studio Code as a coding tool. By creating this information system, it is hoped that it can help schools in managing learning data. The final result of this research is a web-based E-learning system that can optimize attendance information services, manage student data, lecturer data, lecture schedules, course classification, course division, and online learning systems during the semester period.

CONSUMER INFORMATION SYSTEM IN WEB-BASED COOPERATIVES: CASE STUDY OF DIRA JAYA SINAR RESKI COOPERATIVE

This study aims to determine the results of the development of consumer information systems at the Dira Jaya Sinar Reski cooperative as well as find out user responses to the system to be developed. This research uses the type of R&amp;D (Research and development) research and prototype development model that uses data collection techniques such as interviews, observations, and questionnaires. Based on the results of the research, a Web-Based Consumer Information System was developed at the Dira Jaya Sinar Reski Cooperative which has been tested using ISO 25010 testing using 8 aspects of testing that have been validated by content experts. The final result of the overall assessment is that the Consumer Information System at the Web-Based Dira Jaya Sinar Reski Cooperative was declared valid by the validator lecturers, and declared effective based on functional suitability aspects, and declared practical based on user responses that have been tested from the usability aspect.

Smart Vehicle Parking Facility and Monitoring System Using ML

In response to the exponential growth of vehicles in the last two decades, we propose a Machine Learning-based Smart Parking System designed to address the challenges of parking management without the need for sensors or IoT technology. This system leverages cloud computing and a cyber-physical framework to streamline parking operations, providing real-time information to users about parking slot availability, efficient management of reserved and unreserved slots, detection of anomalies, and intelligent traffic management. With a user-friendly interface, the system minimises human intervention, resulting in time, cost, and energy savings, offering an enhanced and efficient solution for urban parking management.In response to the exponential growth of vehicles in the last two decades, we propose a Machine Learning-based Smart Parking System implemented as a web application using HTML, CSS, and JavaScript, without the need for sensors or IoT technology. This web-based system leverages cloud computing and a cyber-physical framework to streamline parking operations, providing real-time information to users about parking slot availability, efficient management of reserved and unreserved slots, detection of anomalies, and intelligent traffic management. With a user-friendly interface, the system minimises human intervention, resulting in time, cost, and energy savings, offering an enhanced and efficient solution for urban parking management.

Web-based System for Identifying Fraudulent Job Advertisements with Machine Learning

Abstract: To prevent false job advertisements on the internet, the study proposes a robotized framework that employs machine learning-based classification techniques. Various classifiers are employed to approve fraudulent web posts, and the results are compared to find the most effective job trick location technique. It helps identify fake job advertisements among a big number of posts. For detecting fake job postings, two major classifier types are considered: single classifiers and outfit classifiers. Nonetheless, the test results show that ensemble classifiers outperform single classifiers in task recognition.

Web-based Cooking Recipe Recommender System based on Stocked Groceries

Due to the severity of the recent PM 2.5 and COVID-19 pandemic situations, the work-from-home lifestyle has been widely adopted as a new normal. Consequently, it’s necessarily preferable to cook at home instead of dining out as usual. However, a common problem is that there are unplanned and overstocked grocery items which are usually unrecognized and improperly managed. To address this issue, the "What To Cook" web application was developed with the theoretical application of Term Frequency-Inverted Document Frequency (TF-IDF) calculations to search for recipes based on the stocked groceries and then applied Cosine Similarity to calculate the similarity between each recipe and the stocked grocery items. Users can input the list of own stocked grocery items into the application and then apply the content-based filtering system to recommend recipes that can utilize the stocked grocery items. Additionally, the application supports the image capturing using Google Cloud Vision API. The application also stores the user's cooking history and saves the under interested recipes for future reference. After testing the application in real-world scenarios, it was found to be easy to use with satisfiable results.

INVESTIGATING THE IMPACT OF ONLINE VS. BLENDED LEARNING ON VOCABULARY LEARNING: EVIDENCE FROM IRANIAN INTERMEDIATE EFL LEARNERS

This study aimed to examine the effect of online vs. blended learning on improving vocabulary learning among Iranian intermediate EFL learners. The current study followed a quasi-experimental, pretest-posttest control group research design. The researchers selected a sample of 120 EFL intermediate learners from a private English Language Institute in Lahijan, Iran for this purpose. The researchers divided the participants into three groups of 40 students each. The researchers used three instruments: 1) a Solution Placement Test (SPT), 2) a Vocabulary pre-test 3), and Vocabulary post-test. The control group only learned vocabulary through traditional lecture methods and face-to-face teaching. The LMS instructional model and the blended learning instructional model were used to teach vocabulary to the online learning group and the blended learning group, respectively. After 10 weeks, students were tested again using a before and after design. In the L2 vocabulary test, both the online and blended learning groups performed better than the control group, in addition, no significant difference was observed between the online and blended learning groups. That is, both online and blended learning instructions have been effective in the development of EFL learners’ vocabulary learning and have had a statistically significant effect on the vocabulary learning of Iranian intermediate EFL learners. The researchers suggest that EFL students can benefit from learning L2 vocabulary through online and blended learning. The findings have practical implications for teacher education programs to promote prospective teachers’ interest and willingness to implement web-based systems. The findings also have important implications for web-based application developers. They should consider a clear model for blended learning and teachers should have the right to choose a blended learning model that suits their teaching contexts to manage the classroom and provide a more effective learning environment.

Pengembangan Aplikasi Absensi Siswa Berbasis Web Pada SMKN 1 Karawang

The Student Attendance System application is a platform that provides information regarding student attendance records at school. At SMKN 1 Karawang, the process of recording student attendance has been carried out manually, starting from recording student attendance, managing attendance data, to preparing the final report. Manual approach This has proven to be less efficient and often produces inaccurate attendance data. Other problems that often arise related to document archiving include loss of notebooks or archives, difficulties in searching for data, and damage to archives. The aim of this research is to design a student attendance system that can makes it easier to manage student attendance data, especially by utilizing a web-based student attendance information system. This approach involves the use of Waterfall model development software and the PHP programming language with a MySQL database. The advantages and results of this web-based student attendance information system are that it provides a variety of features that will make it easier for teachers to manage student attendance data.