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.
Analisis Penggunaan Aplikasi ChatGPT: Model Pembelajaran Campuran Pada Mahasiswa STEAM Nur Aeni Rahman; Azzah Ulima Rahma; Akbar, Muh
Jurnal Pendidikan Terapan Vol 3, No 2 May (2025)
Publisher : Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/jupiter.v3i2.620

Abstract

Tujuan penelitian ini adalah menganalisis penggunaan aplikasi ChatGPT dalam konteks pembelajaran campuran di disiplin ilmu STEM di perguruan tinggi negeri. Data primer diperoleh dari 72 responden, yang merupakan mahasiswa STEM, melalui kuesioner online pada 24 Oktober 2023. Metode deskriptif digunakan untuk menganalisis karakteristik responden dan merinci tanggapan mereka. Analisis menyatakan bahwa mayoritas responden adalah perempuan dengan rata-rata usia 19 tahun, berasal dari berbagai semester dan angkatan, serta memiliki pendidikan terakhir SMA/SMK/sederajat. Sebagian besar dari mereka memiliki kemampuan komputer menengah, mengakses internet setiap hari, dan menggunakan smartphone. Penggunaan aplikasi Chat GPT dalam pembelajaran campuran STEM dinilai positif dalam aspek penggunaan, efektivitas, masa depan, dan penerapan. Aplikasi ini dianggap dapat memberikan solusi terhadap berbagai masalah, memungkinkan interaksi manusia-mesin yang alami, dan menjadi alat bermanfaat dalam pembelajaran, terutama pada mata pelajaran seperti matematika dan pemahaman bahasa asing atau materi kompleks.
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.