Implementasi Aplikasi Laundry Berbasis Machine Learning Untuk Otomatisasi Pengelolaan Nota Transaksi (Studi Kasus Laundry Mamamu)

Abstract

Manual transaction management in laundry businesses often causes various obstacles, such as
difficulty in monitoring transaction status in real-time, ineffective data recording, and the absence
of an integrated laundry status tracking system. The study aims to design and implement a laundry
transaction management application based on modern technology equipped with automation
features, status notifications to customers, and increased efficiency of the laundry collection
verification system using Optical Character Recognition (OCR). The Waterfall method is the development method used in writing this research, this method
includes the stages of needs analysis, design, implementation, and testing. This application will
be developed using Flutter technology for the user interface, Dart as a programming language,
and Firebase as a database. The machine learning model is applied to recognize, manage, and
verify customer transactions automatically.
The results of the study show that this laundry application is able to improve operational
convenience by presenting superior features, such as real-time transaction status, digital recording,
stock management, and income statistics reports. This application also makes it easy for customers
to make orders online and monitor their laundry status. Meanwhile, employees are assisted by
laundry data management features and tools such as OCR for the verification process. With this
implementation, the application is able to support the digitalization of small to medium-scale
laundry businesses, increase productivity, and optimize customer experience.