WULANDARI, Dewi Arianti and Soeprobowati, Tri Retnaningsih and Mutiara K.N., Dinar (2025) MODEL ARSITEKTUR SISTEM E-LEARNING BERBASIS MICROSERVICES DI PERGURUAN TINGGI. Doctoral thesis, UNIVERSITAS DIPONEGORO.

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Abstract

Perkembangan teknologi informasi telah mendorong perguruan tinggi di Indonesia mengimplementasikan sistem pembelajaran daring (e-learning) dengan tujuan meningkatkan fleksibilitas dan aksesibilitas pendidikan. Namun banyak institusi masih menggunakan aristektur monolitik yang kurang memenuhi kebutuhan skalabilitas, fleksibilitas, dan kinerja sistem. Survei awal mengungkapkan bahwa 68% mahasiswa merasa puas terhadap kemudahan penggunaan dan manfaat Microsoft Teams sebagai platform pembelajaran daring, meskipun aspek fleksibilitas dan personalisasi sistem masih dirasakan kurang. Model logistic regression yang digunakan untuk memprediksi kepuasan mahasiswa menunjukkan hasil yang sangat baik, dengan akurasi 98,95%, presisi 0,99, dan recall 1,00 pada threshold 3,75. Temuan ini menandakan peluang signifikan untuk meningkatkan kualitas sistem pembelajaran. Analisis demografi memperlihatkan bahwa 59% mahasiswa memanfaatkan perangkat kombinasi smartphone dan laptop dalam mengikuti pembelajaran daring. Penelitian ini menerapkan pendekatan design science research methodology (DSRM) untuk merancang sistem e-learning berbasis microservices. Evaluasi usability oleh mahasiswa dan dosen mencatat success rate antara 80% dan 95%, sementara penilaian dari staff prodi dan bagian teknologi informasi perguruan tinggi melalui system usability scale (SUS) menunjukkan nilai rata-rata 70, yang artinya sistem layak dan user friendly. Pengujian performa menggunakan GTmetrix menghasilkan grade A (skor performa 100%, struktur front-end 85%), dan pada beban tinggi (500-1000 virtual users), sistem tetap berfungsi tanpa error meskipun terjadi peningkatan latency. Evaluasi prototipe dengan kerangka HOT-Fit yang menghasilkan akurasi model rekomendasi mencapai 78%. Implikasi dari penelitian ini memperkaya literatur sistem informasi dengan penerapan arsitektur microservices pada platform e-learning dan sebagai solusi bagi perguruan tinggi dalam membangun sistem pembelajaran daring yang skalabel, fleksibel dan dapat meningkatkan kinerja platform pembelajaran daring.
Kata kunci: E-learning, Microservices, Design Science Research Methodology, Logistic Regression, Human Organization Technology and Benefit

The development of information technology has prompted universities in Indonesia to implement online learning systems (e-learning) with the aim of increasing the flexibility and accessibility of education. However, many institutions still use monolithic architectures that are less suited to the needs of system scalability, flexibility, and performance. Initial surveys revealed that 68% of students were satisfied with the ease of use and benefits of Microsoft Teams as an online learning platform, although aspects of system flexibility and personalization were still felt to be lacking. The logistic regression model used to predict student satisfaction showed excellent results, with an accuracy of 98.95%, precision of 0.99, and recall of 1.00 at a threshold of 3.75. This finding signifies a significant opportunity to improve the quality of the learning system. Demographic analysis shows that 59% of students use a combination of smartphones and laptops for online learning. This research applies the design science research methodology (DSRM) approach to design a microservices-based e-learning system. Usability evaluation by students and lecturers recorded a success rate between 80% and 95%, while assessments from program staff and the university's information technology department using the System Usability Scale (SUS) showed an average score of 70, indicating the system is usable and user-friendly. Performance testing using GTmetrix resulted in an A grade (performance score 100%, front-end structure 85%), and under high load (500-1000 virtual users), the system remained functional without errors despite increased latency. Evaluate the prototype using the HOT-Fit framework, which resulted in a recommendation model accuracy of 78%. The implications of this research enrich the information systems literature by applying microservices architecture to e-learning platforms and serving as a solution for universities in building online learning systems that are scalable, flexible, and can improve the performance of online learning platforms.
Keywords: E-learning, Microservices, Design Science Research Methodology, Logistic Regression, Human Organization Technology and Benefit

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