Analisis Kinerja Mekanisme Caching MongoDB Cluster pada Moodle
Kata Kunci:
e-learning, moodle, caching, optimisasi, basis data terdistribusi, mongodb clusterAbstrak
Moodle merupakan salah satu platform pendidikan digital digunakan secara meluas. Penggunaan platform digital seperti Moodle bergantung pada beberapa faktor yang meliputi kemudahan pengguna, kenyamanan, norma subjektif, kepuasan, dan interaktifitas. Namun, efesiensi kinerja Moodle sangat dipengaruhi oleh banyaknya fitur yang disediakan, tingginya frekuensi penggunaan dan banyaknya pengguna. Untuk mengatasi inefisiensi kinerja Moodle, mekanisme caching dengan MongoDB Cluster diajukan dalam menangani beban trafik yang tinggi dari pengguna. Perbandingan pengujian kinerja Moodle pada aktivitas enrol, view course, dan quiz dengan skenario jumlah pengguna 20, 60, dan 140 user dilakukan untuk memperoleh gambaran peningkatan kinerja Moodle dengan penerapan mekanisme caching MongoDB Cluster. Hasil pengujian menunjukkan bahwa penerapan mekanisme caching MongoDB Cluster yang diajukan belum berhasil meningkatkan kinerja Moodle. Penurunan throughput terendah didapati pada aktivitas view course dengan skenario 60 user (-8,26%), sedangkan penurunan throughput tertinggi berada pada aktivitas quiz dengan skenario 20 user (-16,96%). Peningkatan latency terendah didapati pada aktivitas enrol dengan skenario 20 user (-1,70%), sedangkan peningkatan latency tertinggi berada pada aktivitas quiz dengan skenario 20 user (-27,54%). Salah satu penyebabnya adalah penggunaan storage engine WiredTiger pada MongoDB Cluster tanpa konfigurasi lebih lanjut tidak cukup memadai untuk bisa memberikan peningkatan kinerja untuk kebutuhan mekanisme caching.
Referensi
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Espinoza-Guerrero, M. & Bayani-Abbasy, M. 2019. Implementation of a Mini-cloud E-learning Supplementary Tool by Using free Tier AWS. Memorias del I Congreso Internacional de Ciencias Exactas y Naturales. doi:10.15359/CICEN.1.79.
Findik-Coşkunçay, D., Alkiş, N. & Özkan-Yildirim, S. 2018. A structural model for students' adoption of learning management systems: An empirical investigation in the higher education context. Journal of Educational Technology & Society, 21(2), 13-27. doi:10.1037/t70573-000.
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AMD. 2019. AMD EPYC™ and NAMD® Powering the Future of HPC. [online] Tersedia di: <https://www.amd.com/system/files/documents/namd-gets-high-performance-with-amd-epyc.pdf> [Diakses 20 Juli 2023]
AWS. 2023. Instance types - Amazon Elastic Compute Cloud. [online] Tersedia di: <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instance-types.html> [Diakses 2 Mei 2023]
Bernardo, M. & Bontà, E. 2020. Facing the COVID-19 pandemic: Massive distance learning and on-line exams with moodle, collaborate, smowl, meet. Proc. 2nd International Conference on Higher Education Learning Methodologies and Technologies Online (HELMeTO), 81-84.
David, A., Mihai, D., Mihailescu, M.E., Carabas, M. & Tapus, N. 2022. Scalability through Distributed Deployment for Moodle Learning Management System. Procedia Computer Science, 214, 34-41. doi:10.1016/j.procs.2022.11.145.
Espinoza-Guerrero, M. & Bayani-Abbasy, M. 2019. Implementation of a Mini-cloud E-learning Supplementary Tool by Using free Tier AWS. Memorias del I Congreso Internacional de Ciencias Exactas y Naturales. doi:10.15359/CICEN.1.79.
Findik-Coşkunçay, D., Alkiş, N. & Özkan-Yildirim, S. 2018. A structural model for students' adoption of learning management systems: An empirical investigation in the higher education context. Journal of Educational Technology & Society, 21(2), 13-27. doi:10.1037/t70573-000.
Garone, A., Pynoo, B., Tondeur, J., Cocquyt, C., Vanslambrouck, S., Bruggeman, B. & Struyven, K. 2019. Clustering university teaching staff through UTAUT: Implications for the acceptance of a new learning management system. British Journal of Educational Technology, 50(5), 2466-2483. doi: 10.1111/bjet.12867.
Huang, C., Cahill, M., Fekete, A. & Röhm, U. 2019. Data Consistency Properties of Document Store as a Service (DSaaS): Using MongoDB Atlas as an Example. Dalam: NAMBIAR, R. & POESS M. (editor) Performance Evaluation and Benchmarking for the Era of Artificial Intelligence, TPCTC 2018, Programming and Software Engineering (LNPSE), 11135, 126-139. Springer, Cham. doi:10.1007/978-3-030-11404-6_10.
Ibrahim, M. H. 2019. A study of the use of Docker compose and dockerhub images. Master Thesis. Queen's University Canada.
McCabe, J. D. 2007. Network Analysis, Architecture, and Design. 3rd ed. Morgan Kaufmann, Burlington.
Moodle. 2023a. Cache definitions - MoodleDocs. [online] Tersedia di: <https://docs.moodle.org/400/en/Cache_definitions> [Diakses 11 Juli 2023]
Moodle. 2023b. Moodle statistics. [online] Tersedia di: <https://stats.moodle.org/> [Diakses 24 Juli 2023]
Moodle. 2023c. Performance recommendations - MoodleDocs. [online] Tersedia di: <https://docs.moodle.org/400/en/Performance_recommendations> [Diakses 24 Juli 2023]
MongoDB. 2023a. MongoDB Clusters | MongoDB. [online] Tersedia di: <https://www.mongodb.com/basics/clusters> [Diakses 30 Juli 2023]
MongoDB. 2023b. In-Memory Storage Engine — MongoDB Manual. [online] Tersedia di: <https://www.mongodb.com/docs/manual/core/inmemory/> [Diakses 24 Agustus 2023]
MongoDB. 2023c. Replication — MongoDB Manual. [online] Tersedia di: <https://www.mongodb.com/docs/manual/replication/> [Diakses 30 Juli 2023]
MongoDB. 2023d. Storage Engines — MongoDB Manual. [online] Tersedia di: <https://www.mongodb.com/docs/manual/core/storage-engines/> [Diakses 24 Agustus 2023]
Mwakisole, K. F., Kissaka, M. M. & Mtebe, J. S. 2019. Cloud computing architecture for elearning systems in secondary schools in Tanzania. The African Journal of Information Systems, 11(4), 299-313.
Ramadhan, I. & Wulandari, L. 2022. Infrastruktur High-Available Learning Management System Universitas Menggunakan Least-Connected Load Balancer. JURNAL MASYARAKAT INFORMATIKA, 13(2), 99-100. doi:10.14710/jmasif.13.2.49176.
Rodrigues, A. G., Demion, B. & Mouawad, P. 2019. Master Apache JMeter-From Load Testing to DevOps: Master performance testing with JMeter. Packt Publishing Ltd, Birmingham.
Paschos, G. S., Iosifidis, G. & Caire, G. 2020. Cache Optimization Models and Algorithms. Foundations and Trends in Communications and Information Theory, 16(3-4), 156-345. doi:10.1561/0100000104.
Roy, R., Potter, S. & Yarrow, K. 2008. Designing low carbon higher education systems: Environmental impacts of campus and distance learning systems. International Journal of Sustainability in Higher Education, 9(2), 116-130. doi:10.1108/14676370810856279.
Roy, S., Williamson, C. & McLean, R. 2018. LMS performance issues: a case study of D2L. International Journal of Computers and Their Applications, 25(3), 113-122.
Sathiyamoorthi, V., Suresh, P., Jayapandian, N., Kanmani, P. & Janakiraman, S. 2020. An Intelligent Web Caching System for Improving the Performance of a Web-Based Information Retrieval System. International Journal on Semantic Web and Information Systems (IJSWIS), 16(4), 26-44. doi:10.4018/IJSWIS.2020100102.
Spherex. 2022. Taking a look at benchmark results for AWS instances - Spherex. [online] Tersedia di: <https://www.spherex.dev/taking-a-look-at-geekbench-results-for-aws-instances/> [Diakses 20 Juli 2023]
Xin, N. S., Shibghatullah, A. S. & Abd Wahab, M. H. 2021. A systematic review for online learning management system. Journal of Physics: Conference Series, 1874(012030). doi:10.1088/1742-6596/1874/1/012030.
Zulfa, M. I., Hartanto, R. & Permanasari, A. E. 2020. Caching strategy for Web application–a systematic literature review. International Journal of Web Information Systems, 16(5), 545-569. doi:10.1108/ijwis-06-2020-0032.
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