Design and Development of Web-based Inventory System with Sales Prediction Using Time Series Forecasting
DOI:
https://doi.org/10.37859/coscitech.v6i3.10575
Abstract
Effective inventory management is a crucial aspect of company operations to predict future stock requirements and product demand. This research aims to design and develop a web-based inventory system with sales prediction using Time Series Forecasting algorithms at CV Adio Loop Engineering. The development method used is waterfall with Long Short-Term Memory (LSTM) approach as a prediction model based on historical inventory transaction data. The system has comprehensive features including dashboard with information on total products, purchases, sales, categories, and suppliers; prediction module for selecting products and prediction types (demand/stock) with time estimation; master data for managing categories, products, and suppliers; transaction modules for purchasing, sales, and inventory; stock movement; low stock alerts; inventory reports; and human resource management with login/logout security system. All modules are equipped with complete CRUD functions. Test results show that the system is capable of providing accurate predictions and improving operational efficiency in inventory management and future stock requirement planning.
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References
J. P. Agboola, F.F., Malgwi, Y.M., Mahmud, M. A. and Oguntoye, “Development of a Web-Based Platform for Automating an Inventory Management of,” vol. 6, no. 5, pp. 57–65, 2022.
A. Salam and Imilda, “Transformasi Digital UMKM Indonesia di Era Industri 5.0: Studi Kasus di Kota Banda Aceh,” Jurnal Manajemen dan Teknologi, vol. 1, no. 1, pp. 1–10, 2024, doi: 10.63447/jmt.v1i1.772.
I. Ayu, A. Fudoli, and M. H. Fahamsyah, “Metode Demand Forecasting dalam menjalankan manajemen operasi pada industri manufaktur,” EKOMABIS: Jurnal Ekonomi Manajemen Bisnis, vol. 3, no. 02, pp. 127–136, 2023, doi: 10.37366/ekomabis.v3i02.286.
D. P. Anggraeni, “Optimisation of Inventory Management Through Time Series Analysis of Inventory Data with Double Exponential Smoothing Method,” Journal of Computer Networks, Architecture and High Performance Computing, vol. 6, no. 3, pp. 1693–1700, 2024, doi: 10.47709/cnahpc.v6i3.4410.
R. Pola Anto et al., “METODE PENELITIAN KUALITATIF: TEORI DAN PENERAPANNYA.”
A. Rahmawati, N. Halimah, K. Karmawan, and A. A. Setiawan, “Optimalisasi Teknik Wawancara Dalam Penelitian Field Research Melalui Pelatihan Berbasis Participatory Action Research Pada Mahasiswa Lapas Pemuda Kelas IIA Tangerang,” Jurnal Abdimas Prakasa Dakara, vol. 4, no. 2, pp. 135–142, Oct. 2024, doi: 10.37640/japd.v4i2.2100.
Y. Sri Rahayu et al., “IMPLEMENTASI METODE WATERFALL PADA PENGEMBANGAN SISTEM INFORMASI MOBILE E-DISARPUS,” 2024.
W. Ningsih and H. Nurfauziah, “PERBANDINGAN MODEL WATERFALL DAN METODE PROTOTYPE UNTUK PENGEMBANGAN APLIKASI PADA SISTEM INFORMAS,” Jurnal Ilmiah Metadata, vol. 5, pp. 83–95, Jan. 2023, Accessed: Nov. 25, 2025. [Online]. Available: https://ejournal.steitholabulilmi.ac.id/index.php/metadata/article/view/311
Ari Fattah Fuaddin, Fisabilla Tidar Yoga Pratama, Fakhrul Akif Maulana Putra, and Ito Setiawan, “Analisis Tingkat Kepuasan Pengguna Sistem Informasi Perpustakaan Dengan Pendekatan Pieces Framework,” Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika, vol. 3, no. 1, pp. 272–282, Jan. 2025, doi: 10.61132/merkurius.v3i1.665.
A. Turserno and R. I. Rosihan, “Analisis Kebutuhan Fungsional Sistem Informasi Manajemen Gudang dengan Metode Pieces (Studi Kasus CV Karya Bangsa) Analysis of Functional Requirements for Warehouse Management Information Systems with the Pieces Method (Case Study of CV Karya Bangsa),” Journal Industrial Manufacturing, vol. 7, no. 1, pp. 1–10, 2022.
