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All Journal JSAI (Journal Scientific and Applied Informatics) JCOSIS (Journal Computer Science and Information Systems)
Handrie Noprison
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Computer Science & IT

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Pemodelan Aplikasi Kasir Untuk Bisnis Fotografi Berbasis Website Menggunakan Rich Picture, PIECES dan UML Purnomo, Sandi; Handrie Noprison
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7413

Abstract

Technological advances have supported the development of cashier systems in business fields (including photography) to improve security and efficiency in business processes. This technological innovation not only streamlines transactions but also increases security measures in the cashier system in the photography business. ARF Studio, which is currently still using a manual system in running its business, is experiencing many obstacles and the creation of a cashier system is expected to overcome the problem. The research location was conducted at ARF Studio with research time in January and February 2024. The web-based cashier application has features for managing transactions, package data, order data, income recap, and printing receipts.
Implementasi Metode Color Blob Detection Pada Objek Daun Sawi Wahyu Adianto; Dwika Putra, Erwin; Handrie Noprison; Vina Ayumi; Marissa utami; Mariana Purba
JCOSIS (Journal Computer Science and Information Systems) Vol. 1 No. 1 (2024): Mei
Publisher : Institute for Research and Community Service

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61567/jcosis.v1i1.176

Abstract

Tujuan : Sistem aplikasi Mendeteksi Objek Daun Sawi dengan menerapakan Metode Color Blob Detection menggunakan Bahasa pemrograman matlab. Mekanisme pembuatan aplikasi dimulai dari pembuatan rancangan aplikasi, GUI (Grafik User Interface) sampai dengan pembuatan coding. Metode/Design/Pendekatan: model deteksi Objek Daun Sawi dengan menerapakan Metode Color Blob Detection menggunakan Bahasa pemrograman matlab Hasil/Temuan: Hasil pengujian yang dilakukan dengan memiliki tingkat keakuratan paling tinggi yaitu dengan jarak pengambilan sampel objek dengan jarak 50 cm, dan tingkat keakuratan paling rendah dengan jarak pengambilan sampel objek dengan jarak 20 cm. Kebaharuan/Originalitas/Nilai: Tingkat akurasi deteksi daun sawi maka dapat disimpulkan berhasil dengan tingkat keberhasil akurasi 67.7% Keywords: Color Blob Detection, Image Processing, Matlab
Co-Authors Ayumi, Vina Mariana Purba Purnomo, Sandi Putra, Erwin Dwika Wahyu Adianto