Sistem Informasi Point of Sale Dengan Pencatatan Utang Berjalan Dan Rekomendasi Produk - Muhammad Abdullah; Hanifah Permatasari; Agustina Srirahayu (STIKOM Tunas Bangsa Pematangsiantar, 2026)
Toko Sembako Pak Sabar in Sukoharjo still records sales transactions, customer debts, and stock manually, leading to recording errors, data loss, stock inaccuracies, and operational losses. This study aims to design and build an integrated web and mobile-based Point of Sale (POS) information system with a running-debt recording module and a hybrid product recommendation system combining 30-day internal transaction data and 30-day Google Trends external data. The system was developed using the Waterfall SDLC model. The web admin application uses Laravel, the cashier mobile application uses Flutter, and MySQL as the database. Inter-platform communication uses REST API with token-based authentication via Laravel Sanctum. Testing used Black Box Testing across twelve functional scenarios and API security testing via Postman. Results show the system successfully records transactions, manages stock in real-time, handles complete running-debt mechanisms, generates automatic financial reports, and provides hybrid product recommendations with 80% Precision, 75% Recall, and 77.4% F1-score—higher than the internal-only approach (68% Precision, 62% Recall). All functions performed as required with an average response time below 2 seconds.