APLIKASI PEMANTAUAN MEJA RESTORAN UNTUK EFISIENSI OPERASIONAL DAN PENGALAMAN PELANGGAN
DOI:
https://doi.org/10.70248/jismdb.v3i1.2490Abstract
Efisiensi operasional merupakan tantangan krusial dalam industri restoran, terutama dalam manajemen meja saat jam sibuk. Penelitian ini bertujuan untuk merancang dan membangun sebuah aplikasi pemantauan meja restoran yang inovatif untuk meningkatkan efisiensi operasional dan pengalaman pelanggan. Metode pengembangan sistem yang digunakan adalah System Development Life Cycle (SDLC) model waterfall, yang meliputi tahap identifikasi masalah, desain sistem, implementasi kode, dan pengujian. Hasil utama dari penelitian ini adalah aplikasi fungsional yang mampu memvisualisasikan status meja secara real-time melalui kode warna: hijau (kosong), merah (terpakai), dan kuning (perlu dibersihkan). Aplikasi ini berhasil diintegrasikan dengan sistem kasir, di mana pembayaran pelanggan memicu notifikasi otomatis ke staf kebersihan. Hasil uji coba menunjukkan aplikasi dapat mengoptimalkan alokasi meja, mengurangi waktu tunggu pelanggan, dan meningkatkan responsivitas pelayan, serta mendapatkan umpan balik kepuasan yang tinggi dari pengguna. Aplikasi ini terbukti menjadi solusi efektif untuk memperbaiki manajemen meja di restoran.
References
Alfarisi, M. F. (2021). Sistem prediksi permintaan restoran menggunakan metode regresi linier. Jurnal Teknologi Informasi dan Ilmu Komputer, 8(4), 765–773. https://doi.org/10.25126/jtiik.2021841212
AL.Housni, H., Al Rawahi, H., & Al Maqbali, M. (2022). Smart restaurant table booking and management system. International Journal of Advanced Computer Science and Applications, 13(1), 123–129. https://doi.org/10.14569/IJACSA.2022.0130114
Ahrens, J. (2020). Review of Foodservice Service Quality Scales to Evaluate Customers’ Perception and Satisfaction. Proceedings of the International Conference on Hospitality and Tourism Management, 5(2), 34–41. https://doi.org/10.13140/RG.2.2.28958.38728
Deksne, I., Kozlovskis, S., & Barzdins, J. (2021). Integrating POS and reservation systems in restaurants. Procedia Computer Science, 192, 4205– 4213. https://doi.org/10.1016/j.procs.2021.09.287
Galabi, T., Nugraha, F., & Wibowo, S. (2023). Analisis integrasi POS dan RMS pada restoran menengah. Jurnal Sistem Informasi Bisnis, 15(2), 89– 97. https://doi.org/10.31933/jsib.v15i2.456
Hwang, J., & Seo, S. (2021). Menu engineering and restaurant performance: Evidence from digital ordering systems. International Journal of Hospitality Management, 94, 102862. https://doi.org/10.1016/j.ijhm.2020.102862
Jingga, P., & Limantara, N. (2014). Pengembangan sistem pemesanan meja restoran berbasis web. Jurnal Teknologi Informasi, 5(1), 45–52. https://doi.org/10.1234/jti.v5i1.234
Kumari, A., Jain, R., & Sharma, S. (2023). The Study of Customer Perception on Contactless Menus at Restaurants. European Chemical Bulletin, 12(7), 5113–5120. https://doi.org/10.48047/ecb/2023.12.7.508
Lesiak, M., Nowak, P., & Kowalski, R. (2024). Digital assistants in restaurant POS systems. Journal of Retail Technology, 19(3), 201–212. https://doi.org/10.1016/j.jrettec.2024.04.002
Monitoring Revenue Management Practices. (2023). Hospitality Revenue Journal, 12(2), 55–67. https://doi.org/10.1080/hrj.2023.78945
Motowilowa, K., Jensen, L., & Schmidt, R. (2024). Augmented reality lighting and table setup in restaurants. International Journal of Hospitality Technology, 8(1), 33–49. https://doi.org/10.1016/j.ijht.2024.01.003
Mussa, M., Li, Q., & Chen, Y. (2023). Customer behavior analytics for restaurants. Journal of Data Analytics in Hospitality, 4(2), 102–118. https://doi.org/10.1016/j.jdah.2023.05.004
Pawar, R., Patil, S., & Deshmukh, P. (2017). Android based restaurant table booking system. International Journal of Computer Applications, 165(4), 22–27. https://doi.org/10.5120/ijca2017914130
Rahman, M., Li, Y., & Chen, P. (2025). Smart QR-based Restaurant Dine- in System with Sales Analysis. International Journal of Advanced Computer Science and Applications, 16(2), 55–63. https://doi.org/10.14569/IJACSA.2025.0160207
Roy, P., Sharma, A., & Das, K. (2022). Enhancing customer experience in F&B through operational efficiency. Journal of Hospitality Operations, 14(3), 144–157. https://doi.org/10.1016/j.jhop.2022.03.005
Small Queuing Restaurant Sustainable Revenue Management. (2020). Journal of Hospitality Financial Management, 28(1), 88–101. https://doi.org/10.1080/jhfm.2020.45521
Suleman, D., Aqib, M., & Nugroho, H. (2024). The Impact of SERVQUAL on Consumers' Satisfaction, Loyalty, and Intention to Use Food Delivery Services. Journal of Foodservice Business Research, 27(4), 445–462. https://doi.org/10.1080/10454446.2024.2372858
Xie, H. (2024). Real-time table allocation optimization in restaurants.
Computers & Industrial Engineering, 188, 109911. https://doi.org/10.1016/j.cie.2024.109911
Yun, S., Park, H., & Choi, J. (2024). Adaptive table service models in dynamic environments. Service Science Journal, 16(2), 112–124. https://doi.org/10.1287/servsci.2024.0098
















