Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
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This Author published in this journals
All Journal Journal of Embedded Systems, Security and Intelligent Systems Journal of Digital Technology and Computer Science
Amanda Putri Lestari
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering Engineering

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Task Monitoring Information System: Case Study of Task Minder Implementation in PTIK A Class Students Class 2022 Makassar State University Fauziah; Miftakhul Jannah; Amanda Putri Lestari
Journal of Digital Technology and Computer Science Vol. 2 No. 1 (2024): November 2024
Publisher : Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/digitech.v2i1.20242

Abstract

In the digital age, students face increasing demands to manage various academic assignments and deadlines effectively. Manual task management often leads to missed deadlines, irregularities, and reduced productivity. Therefore, a structured, easy-to-use task monitoring system is needed to support learning efficiency. This research explores Task Minder, a task monitoring system that helps individuals and organizations manage tasks in a structured manner. With user-friendly features such as account creation, task editing, status tracking, and automatic reminders, Task Minder aims to increase productivity and efficiency. A descriptive method is used to describe and analyze this system, through a whitebox approach in the creation of Software Requirements Specification (SRS) documents. Data was collected through interviews, observations, and documentation, then analyzed qualitatively using thematic analysis methods. The results show an increase in user productivity, but also identify some limitations that need to be considered for effective use. Overall, Task Minder makes a real contribution as a digital solution in academic task management, helping students organize work more efficiently, responsively, and integrated with learning needs.
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 Athiyyah Anandira Azzah Ulima Rahma Dewi Fatmarani Surianto Fauziah Miftakhul Jannah