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Journal : international journal software engineering and computer science ijsecs

Development of a Web-Based SQL Query Online Examination System with Automated Grading Using the MVC Design Pattern Yunhasnawa, Yoppy; Windawati, Atif; Cinderatama, Toga Aldila; Vista, Candra Bella; Abdullah, Moch. Zawaruddin
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3285

Abstract

In this study, the Researchers provide the design, development, and evaluation of a web-based SQL exam system that utilizes the Model-View-Controller (MVC) architectural pattern to enhance automated grading functionality and ease of maintenance. The main objectives of the system are to simplify the process of administering SQL exams, to make it user-friendly for students to enter their SQL statements, and as a means for teachers to automate the grading process. This allows a clear separation between three separate modules: Model to manage data, View to present the application to users, and Controller to manage the application logic. This separation allows for modular development, easier maintenance, and code reuse. The fundamental aspect of the system lies in its automated grading mechanism, which intelligently compares the SQL queries submitted by students with the corresponding validated answer keys stored in the database. Extensive black-box testing was conducted to ensure the reliability and accuracy of the system with various test cases to assess its ability to assess responses and provide real-time feedback to students, in addition to smooth and intuitive navigation within the system. All testing criteria yielded successful results with 100% agreement proving the robustness of the system with all possible locations that could potentially be used in higher education structures. The system provides a scalable and flexible approach to address the challenges associated with SQL assessment in academic institutions, thereby facilitating uniform, efficient, and objective evaluation standards. The system uses data up to October 2023 to prevent the model from becoming obsolete
Development of a Web-Based SQL Query Online Examination System with Automated Grading Using the MVC Design Pattern Yoppy Yunhasnawa; Atif Windawati; Toga Aldila Cinderatama; Candra Bella Vista; Moch. Zawaruddin Abdullah
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3285

Abstract

In this study, the Researchers provide the design, development, and evaluation of a web-based SQL exam system that utilizes the Model-View-Controller (MVC) architectural pattern to enhance automated grading functionality and ease of maintenance. The main objectives of the system are to simplify the process of administering SQL exams, to make it user-friendly for students to enter their SQL statements, and as a means for teachers to automate the grading process. This allows a clear separation between three separate modules: Model to manage data, View to present the application to users, and Controller to manage the application logic. This separation allows for modular development, easier maintenance, and code reuse. The fundamental aspect of the system lies in its automated grading mechanism, which intelligently compares the SQL queries submitted by students with the corresponding validated answer keys stored in the database. Extensive black-box testing was conducted to ensure the reliability and accuracy of the system with various test cases to assess its ability to assess responses and provide real-time feedback to students, in addition to smooth and intuitive navigation within the system. All testing criteria yielded successful results with 100% agreement proving the robustness of the system with all possible locations that could potentially be used in higher education structures. The system provides a scalable and flexible approach to address the challenges associated with SQL assessment in academic institutions, thereby facilitating uniform, efficient, and objective evaluation standards. The system uses data up to October 2023 to prevent the model from becoming obsolete
AutoClusterAPI: A Lightweight Backend Framework for Automated Unsupervised Clustering Pipelines Yoppy Yunhasnawa; Atif Windawati; Toga Aldila Cinderatama; Moch. Zawaruddin Abdullah; Elok Nur Hamdana
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.5997

Abstract

This study presents AutoClusterAPI, a lightweight and extensible backend system designed to simplify and accelerate unsupervised clustering workflows. The system addresses a recurring problem in data analysis practice: many practitioners need rapid clustering capabilities but lack the programming or statistical background required to build complete pipelines from scratch. AutoClusterAPI provides an automated, endpoint-driven solution that allows users to perform every stage of clustering — from data loading and cleaning to feature preparation, algorithm execution, profiling, and visualization — through standard HTTP requests. The system is built using Python and the FastAPI web framework, supports eight clustering algorithms, and includes automated preprocessing alongside PCA-based visualization. Functional testing confirms that all endpoints behave correctly under both valid and invalid inputs, establishing the reliability of the system. A case study using a customer segmentation dataset further demonstrates its practical utility, showing that AutoClusterAPI can efficiently generate meaningful cluster structures and interpretable visual outputs. The system offers an accessible yet configurable environment for rapid clustering analysis and establishes a basis for future extensions and real-world deployment.
Co-Authors Abidatul Izzah Agustono Heriadi Agustono Heriadi Agustono Heriadi, Agustono Ahmad Athoillah Saifi Amini, Julia Intan Andika Kurnia Adi Pradana Ardiansyah, Mohammad Rifqi Dwi Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta, Ashafidz Fauzan Asmoro, Wiwiek Kusumaning Astiningrum, Mungki Ata Amrullah Atif Windawati Atik Tri Andari Atik Tri Andari, Atik Tri Atiqah Nurul Asri Ayundyayasti, Prima Benni Agung Nugroho Benni Agung Nugroho Benni Agung Nugroho Benni Agung Nugroho Benni Agung Nugroho, Benni Agung Budiprasetyo, Gunawan Candra Bella Vista Devianti, Meryta Dewi, Isyana Wikrama Dharma Tungga Dina Yeni Martia Dion Yanuarmawan Eka Apriani, Meyti Eliyen, Kunti Ellya Nurfarida Ellya Nurfarida, Ellya Elok Nur Hamdana Elok Nur Hamdana Fadelis Sukya Fadelis Sukya Fadelis Sukya, Fadelis Fajria, Rola Nurul Fariez Ilham Alviansyah Fery Sofian Efendi Fery Sofian Efendi Fery Sofian Efendi Fery Sofian Efendi Fery Sofian Efendi Fery Sofian Efendi Fery Sofian Effendi Fery Sofian Effendi fitria nur hamidah Fitria Nur Hamidah, Fitria Nur Gunawan Budiprasetyo Hadi Rahmad Hamdani Arif Hendrawan, Muhammad Afif Irfin Sandra Asti Junaedi Adi Prasetyo Kenneth Pinandhito Kunti Eliyen Kunti Eliyen Maskur, M Moch Zawaruddin Abdullah Nugraha, Girindra Fajar Putranti, Eti Rahmad Aliy Cagar Wahyu Aji Ratna Widyastuti, Ratna Renaldi, Rasyed Rinanza Zulmy Alhamri, Rinanza Zulmy Riswan Eko Wahyu Susanto Riswan Eko Wahyu Susanto, Riswan Eko Wahyu Riswanda Al Farisi Rudy Ariyanto Setianingsih, Novie Astuti Sofian Efendi, Fery Trisha Alfandi Wahyu, Mujahid Windawati, Atif Yan Watequlis Syaifudin Yanuarmawan, Dion Yohan Bakhtiar Yoppy Yunhasnawa Yuri Arianto Yuri Ariyanto Zulmy Alhamri, Rinanza