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All Journal The Journal of Enhanced Studies in Informatics and Computer Applications Jurnal Sistem Informasi Komputer
Kunti Inayati
Universitas Muhammadiyah Gresik
Computer Science & IT

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Rancang Bangun Sistem Informasi Peminjaman Ruangan (SIPINRU) Berbasis Web Menggunakan Metode Waterfall Kunti Inayati; Susilo Setyo Tri Wibowo; Jordan Ramadani Pamungkas; Umi Chotijah
Jurnal Sistem Informasi Komputer ( SIKOM ) Vol. 3 No. 1 (2026): Volume 3 Nomor 01 Januari 2026
Publisher : Jurnal Sistem Informasi Komputer ( SIKOM )

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Abstract

Room management plays an important role in supporting academic and non-academic activities in higher education institutions. This study aims to design and develop a web-based Room Loan Information System (SIPINRU) that facilitates the room borrowing process in a more efficient and transparent manner. The system is developed using the PHP programming language with MySQL as the database and applies the Waterfall development method. SIPINRU allows students and lecturers to submit room loan requests online without requiring prior login, making the submission process simpler and more accessible. In addition, the application provides real-time updates on the submission status, enabling applicants to quickly obtain clear information regarding approval or rejection without prolonged waiting times. Administrators are responsible for managing room data and verifying loan requests through the system. Black box testing results indicate that all system functions operate as expected according to the defined requirements. Therefore, SIPINRU is expected to improve the effectiveness of room loan management in higher education environments.
Performance-Storage Trade-Off Analysis of MongoDB Indexing Strategies Using Large-Scale E-Commerce Data Kunti Inayati; Umi Chotijah
Journal of Enhanced Studies in Informatics and Computer Applications Vol. 3 No. 2 (2026): JESICA Vol. 3 No. 2 2026
Publisher : Institut Teknologi, Sains, dan Kesehatan RS.DR. Soepraoen Kesdam V/BRW

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47794/jesica.v3i2.45

Abstract

Indexing strategy in document-oriented databases represents a fundamental design decision that directly shapes both query performance and storage consumption, yet empirical evidence quantifying this trade-off at production-grade scale remains limited in existing literature. This study evaluated three indexing configurations in MongoDB, namely no index, single-field index on product identifier, and compound index on product identifier together with order status, across four collection sizes of 1 million, 5 million, 10 million, and 13 million documents derived from a synthetic large-scale e-commerce dataset obtained from Kaggle containing approximately 13 million order-line records. A controlled benchmarking procedure was employed in which each indexing condition was tested under identical query workloads repeated 30 times per configuration, with query execution time, index creation time, and index storage size recorded as evaluation metrics. Results showed that unindexed collections produced full collection scans with mean execution times scaling from 1,247.70 ms at 1 million documents to 33,300.07 ms at 13 million documents, while both indexed conditions reduced execution times to single-digit milliseconds by activating index scan paths. For multi-predicate queries, the compound index outperformed the single-field index by a factor of 6.8 at full scale, recording 1.33 ms against 9.03 ms, while incurring only 1 MB of additional storage overhead. These findings indicate that compound indexing represents the most balanced strategy for high-volume e-commerce query workloads, delivering substantial performance gains at negligible additional storage cost.
Co-Authors Jordan Ramadani Pamungkas Susilo Setyo Tri Wibowo Umi Chotijah