Wahdana, Dilla (2025) Pengembangan Aplikasi Penilaian Otomatis untuk Jawaban Soal Cerita Matematika Berbasis Framework Svelte. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Perkembangan teknologi digital telah memengaruhi berbagai aspek kehidupan, termasuk pendidikan. Proses pembelajaran dituntut untuk mengintegrasikan teknologi demi peningkatan mutu, terutama dalam evaluasi hasil belajar. Berbagai aplikasi penilaian otomatis telah dikembangkan, terutama untuk jenis soal pilihan ganda dan esai. Sistem seperti Google Forms, Moodle, hingga automated essay scoring (AES) berbasis machine learning telah digunakan secara luas untuk memberikan penilaian instan. Meskipun efektif untuk jenis soal tertentu, sebagian besar aplikasi tersebut masih berfokus pada hasil akhir dan belum mampu mengungkap proses berpikir siswa secara mendalam, terutama pada soal cerita matematika yang menuntut pemahaman konseptual dan kemampuan penalaran bertahap.Penelitian ini bertujuan mengembangkan aplikasi website berbasis framework Svelte.js untuk otomatisasi penilaian jawaban soal cerita matematika. Penelitian ini juga mendukung tercapainya tujuan pembangunan berkelanjutan dengan menghadirkan inovasi digital dalam mendukung pendidikan yang berkualitas Aplikasi ini memanfaatkan teknologi machine learning dengan Python untuk menganalisis tahapan pengerjaan soal siswa secara komprehensif, memungkinkan penilaian tidak hanya pada jawaban akhir, tetapi juga proses pengerjaan.Hasil pengujian menunjukkan bahwa aplikasi berhasil menjalankan seluruh fitur utama berdasarkan skenario fungsional yang telah ditentukan (black-box testing). Selain itu, hasil evaluasi melalui metode User Acceptance Test (UAT) dengan skala Likert menunjukkan bahwa sistem memperoleh nilai rata-rata diatas 80%, yang mengindikasikan bahwa aplikasi layak digunakan. Dengan demikian, aplikasi berhasil digunakan untuk menilai jawaban soal cerita matematika secara otomatis serta menyajikan hasil analisis kompetensi yang dicapai oleh siswa.
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The development of digital technology has influenced various aspects of life, including education. The learning process is increasingly required to integrate technology in order to improve quality, particularly in the evaluation of learning outcomes. Various automated assessment applications have been developed, especially for multiple-choice and essay-type questions. Systems such as Google Forms, Moodle, and machine learning-based Automated Essay Scoring (AES) have been widely used to provide instant evaluation. Although effective for certain question types, most of these applications still focus on the final answers and are not yet capable of revealing students' thought processes in depth—especially in mathematical word problems that require conceptual understanding and step-by-step reasoning.This study aims to develop a web-based application using the Svelte.js framework for the automated assessment of mathematical word problem answers. It also supports the achievement of the Sustainable Development Goals (SDGs) by presenting a digital innovation to enhance the quality of education. The application leverages machine learning technology implemented in Python to comprehensively analyze the steps taken by students in solving the problems, enabling assessment not only of the final answer but also of the problem-solving process.Testing results show that the application successfully executed all main features according to the predefined functional scenarios (black-box testing). Furthermore, evaluation through the User Acceptance Test (UAT) using a Likert scale indicates an average score above 80%, signifying that the application is suitable for use. Thus, the application has proven effective in automatically assessing mathematical word problem answers and presenting an analysis of the competencies demonstrated by students.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Svelte.js, Aplikasi, Otomatisasi Penilaian, Python, Evaluasi, Inovasi Digital, Pendidikan Berkualitas, Svelte.js, Apps, Assessment Automation, Python, Evaluation |
| Subjects: | L Education > L Education (General) T Technology > T Technology (General) T Technology > T Technology (General) > T57.5 Data Processing |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | Dilla Wahdana |
| Date Deposited: | 31 Jul 2025 03:52 |
| Last Modified: | 31 Jul 2025 03:52 |
| URI: | http://repository.its.ac.id/id/eprint/124808 |
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