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All Journal Jurnal Pendidikan Terapan Journal of Embedded Systems, Security and Intelligent Systems Indonesian Technology and Education Journal
Athiyyah Anandira
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Humanities Computer Science & IT Education Social Sciences Other

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Mengembangkan Platform HEAL-U: Peningkatan Layanan Konseling Online Untuk Kesejahteraan Pengguna Muhammad Rio Sahri Syawal; Sri Irmayani; Athiyyah Anandira; Sumarno
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.v2i2.409

Abstract

Adolescence is a crucial transitional phase between childhood and adulthood, marked by significant emotional changes. Teenagers often struggle to adapt to these changes, which can lead to serious issues such as depression and anxiety. According to data from the Basic Health Research, approximately 6.1% of the Indonesian population experiences emotional mental disorders. To address this issue, the Heal-U platform was developed, an online counseling system designed to provide mental support for teenagers. The development method used is the waterfall model, starting from planning to system implementation and testing. Testing was conducted using both black-box and white-box approaches to ensure the system's functionality and reliability. The results show that Heal-U can be effectively implemented and has great potential to reduce the rates of depression and suicide among teenagers.
Persepsi Mahasiswa Perguruan Tinggi Kota Makassar terhadap Efektivitas Penggunaan Chatbot AI sebagai Media Bantu Pembelajaran Interaktif Andi Nurul Inaya; Athiyyah Anandira; 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.v3i2.621

Abstract

Teknologi semakin berkembang pesat di era digital ini, dan penggunaan kecerdasan buatan (AI) semakin umum digunakan dalam berbagai bidang, termasuk pendidikan. Salah satu bentuk AI yang digunakan dalam pendidikan adalah chatbot. Maka dari itu, artikel ini menganalisis persepsi mahasiswa perguruan tinggi di kota Makassar terkhusus pada fakultas teknik terhadap efektivitas penggunaan chatbot AI sebagai media bantu pembelajaran interaktif. Penelitian ini menggunakan metode kuantitatif dengan teknik pengumpulan data berupa pengisian kuesioner secara online. Sampel penelitian terdiri dari 76 mahasiswa teknik di Perguruan Tinggi Kota Makassar. Hasil penelitian menunjukkan bahwa mayoritas mahasiswa merasa bahwa chatbot AI membantu dalam proses pembelajaran, memfasilitasi pemerolehan dan berbagi pengetahuan, serta menerapkan pengetahuan dalam kegiatan belajar dan penugasan. Selain itu, mahasiswa juga merasa bahwa chatbot AI memberikan manfaat yang lebih besar dari yang mereka perkirakan dan memenuhi harapan mereka sebagai media bantu pembelajaran. Penelitian ini memberikan wawasan yang mendalam tentang penggunaan chatbot AI dalam konteks pendidikan dan bagaimana persepsi mahasiswa terhadap teknologi ini.
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.
Co-Authors Akbar, Muh Amanda Putri Lestari Andi Nurul Inaya Azzah Ulima Rahma Dewi Fatmarani Surianto Muhammad Rio Sahri Syawal Sri Irmayani Sumarno