Pengembangan Fitur Pencarian dan Filter Produk pada Aplikasi E-Commerce Gallery Muslim Berbasis Android
Original Full-Text Article
Download published version for reading and archivingAbstract
The primary challenge in inventory management for MSMEs like Gallery Muslim lies in the manual recording system using notebooks and Excel spreadsheets, which is prone to errors and data loss. Yet, structured offline mobile solutions for micro-scale fashion MSMEs with fragmented recording practices remain limited. This research aims to design and develop an Android-based stock management application utilizing a local Room Database for efficient and accurate digital recording. The study focuses on Gallery Muslim, a retail shop specializing in Muslim clothing and school uniforms. Data were collected through interviews, direct observation, and focus group discussions (FGD) with store owners and warehouse staff. Instruments included documentation of recording activities and analysis of feature requirements. The results demonstrate that the application accelerates the stock recording process by up to 50% compared to manual methods (based on initial simulations), enhances data accuracy, and enables offline access without an internet connection. The study concludes that this Android-based local application is highly suitable for MSMEs not yet integrated with online systems, offering a practical tool for small business owners to embark on digital transformation and improve operational efficiency.
Author Biographies
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
How to Cite
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License .
- Share: You are free to copy, distribute, and transmit the work in any medium or format.
- Adapt: You are free to remix, transform, and build upon the work for any purpose, even commercially.
- Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
References
Total: 14 References- Alda, M. (2023). Pengembangan Aplikasi Pengolahan Data Siswa Berbasis Android Menggunakan Metode Prototyping. Jurnal Manajemen Informatika (JAMIKA), 13(1), 11-23. https://doi.org/10.34010/jamika.v13i1.8216.
- Halim, F., & Wijaya, A. H. (2022). Analisis dan Perancangan E-Commerce Berbasis Web Dengan Penerapan Sistem Perekomendasian Menggunakan Metode Collaborative Filtering Serta Metode Up, Down, Cross Selling. ALGOR, 4(1), 28-43. https://doi.org/10.31253/algor.v4i1.1516.
- Hidayat, B. M. H., & Putra, R. E. (2019). Penerapan CNN dengan Filter Gabor sebagai feature extractor untuk Content-Based Image Retrieval. Journal of Informatics and Computer Science (JINACS), 1(01), 16-25. https://doi.org/10.26740/jinacs.v1n01.p16-25.
- Laudon, K. C., & Laudon, J. P. (2012). Essentials of management information systems. Prentice Hall.
- Liana, L. I., & Nudin, S. R. (2020). Implementasi algoritma Best-First Search untuk aplikasi mesin pencari handphone pada e-commerce (Apenphone). Journal of Informatics and Computer Science (JINACS), 2(01), 67-73.
Similar Articles
Articles sharing related keywords and machine learning classifications:
Most read articles by the same author(s)
Other papers published by author(s) in this journal: