Azzah Ulima Rahma
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Sistem Pemesanan Kopi : Coffee Chill Andi Dio Nurul Awalia; Fadilah Husnul Khatimah; Azzah Ulima Rahma; Muhammad Raihan
Indonesian Technology and Education Journal Volume 2 No. 2 Agustus 2024
Publisher : Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/itej.v2i2.403

Abstract

The advancement of technology has made the coffee industry require an effective information system to support marketing and the growth of the coffee chain. The purpose of this research is to develop a web-based ordering information system for coffee shops, called Coffee Chill. This system is designed to provide a practical and enjoyable ordering experience through a user-friendly interface, as well as real-time ordering without queues. This research utilizes interviews and observations as methods to collect data, as well as the Waterfall system development method which includes planning, analysis, design, implementation, and maintenance stages. The planning stage involves analyzing user needs and assessing technical and organizational feasibility. The analysis stage identifies system problems and needs, while the design stage develops system models and architecture. Testing using White Box and Black Box methods is conducted to verify system performance according to specifications. The test results show that this system is highly suitable for development and can improve service and operational efficiency in coffee shops.
Segmentation of Student Lifestyle Patterns for Insomnia Risk Identification Using the K-Means Algorithm Athiyyah Anandira; Azzah Ulima Rahma; Amanda Putri Lestari; Dewi Fatmarani Surianto
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i3.8683

Abstract

Insomnia is a common sleep disorder that occurs in college students due to unbalanced lifestyle patterns. This study aims to categorize students based on their lifestyle patterns and identify the risk of insomnia by applying the K-Means algorithm. Data were obtained from 198 active students of JTIK UNM batch 2021-2024 through a questionnaire. Five main variables were analyzed, such as sleep duration, caffeine consumption, gadget use, number of assignments per week, and hours of sleep. After the researchers transformed and normalized data, the clustering process had resulted in two clusters. The first cluster showed a higher risk of insomnia due to late bedtime and excessive gadget usage, while the second cluster tended to undergo a healthier lifestyle. The Davies-Bouldin Index value of 0.22 indicates superlative clustering qualities. This study provides an overview of student characteristics based on lifestyle and potential risk of insomnia.
Klasifikasi Citra Dengan Pendekatan Transfer Learning Pada Gambar Fauna Terbang Andi Nurul Inaya; Azzah Ulima Rahma; Miftakhul Jannah; Luthfiyah Ramadhani K. Arafah; Lulu Latifa Ishak; Marwan Ramdhany Edy
Jurnal MediaTIK Volume 7 Issue 1, Januari (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v7i1.2785

Abstract

Indonesia, dengan kekayaan alamnya yang luar biasa, menjadi rumah bagi beragam fauna, termasuk burung. Namun, melindungi dan mengkatalogisasi keragaman ini memerlukan metode yang efisien dan akurat. Dalam konteks ini, pendekatan transfer learning menonjol sebagai alat yang dapat meningkatkan klasifikasi citra fauna terbang. Penelitian ini menggunakan Google Colab sebagai lingkungan pengkodean, memanfaatkan kemudahan penyimpanan dan akses data melalui Google Drive. Kami memproses dataset ImageNet dengan metode transfer learning menggunakan bahasa pemrograman Python. Hasil dari penelitian ini diharapkan dapat memberikan kontribusi dalam berbagai aplikasi, termasuk pengenalan objek, deteksi wajah, dan segmentasi objek. Secara khusus, dalam pengembangan perangkat lunak, klasifikasi citra seperti ini dapat diterapkan dalam sistem pengenalan hewan berbasis gambar, keamanan berbasis kamera, atau aplikasi pencarian berdasarkan gambar.