Syafika Zalfanissa Dila
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A Mobile Application for Early Skin Cancer Screening and Skin Health Awareness: A Case Study of Muara Angke Popong Setiawati; Gerry Firmansyah; Dwi Nurmawaty; Andriyanti Asianto; Sandy, Raynaldi; Alnino Dio Putera; Aurel Elviolita Putri; Alandrian Surya Tantra; Syafika Zalfanissa Dila
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.5182

Abstract

This study aimed to develop a mobile application for early skin cancer screening while simultaneously enhancing public awareness of skin health, with a case study conducted in the coastal area of Muara Angke, North Jakarta. The research was motivated by high levels of ultraviolet radiation exposure and limited access to healthcare services, which often lead to delayed skin cancer detection. An empirical quantitative approach was employed by utilizing a Convolutional Neural Network (CNN) based on the ResNet50 architecture, deployed through a cloud based infrastructure and integrated into a Flutter based mobile application. The system was designed using an edge cloud computing approach to address the computational limitations of mobile devices. The results indicated that the application effectively performed preliminary skin lesion screening, provided classification outcomes with confidence scores, and delivered accessible skin health education content. Although the application was not intended to serve as a medical diagnostic tool, it demonstrated significant potential to support early detection efforts and improve community level awareness of skin health. This study contributes to the advancement of mobile health (m-health) by emphasizing the practical implementation of AI based applications tailored to community needs.
No-code workflow automation for meeting minutes generation using scrum Syafika Zalfanissa Dila; Tundjungsari, Vitri
Jurnal Mandiri IT Vol. 14 No. 3 (2026): Jan: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i3.500

Abstract

The increasing frequency of online meetings has intensified the need for efficient and consistent meeting documentation. However, the preparation of meeting minutes is still commonly performed manually, resulting in delayed documentation, inconsistent formats, and increased workload. This study aimed to develop and evaluate a no-code workflow automation system for meeting minutes generation using the Scrum framework. The proposed system integrated a no-code automation platform with an AI-based text summarization service to automatically process meeting transcripts and generate structured meeting minutes consisting of key discussion points, decisions made, and action items. The system was developed using an iterative Scrum-based approach, allowing continuous feedback and refinement throughout the development process. System evaluation focused on efficiency and usability by comparing the automated process with manual documentation. The results showed that the proposed system reduced the meeting minutes preparation time from approximately 30–45 minutes per meeting (manual process) to 2–5 minutes per meeting (automated workflow), while improving consistency and clarity of the output. In addition, the no-code approach enabled non-technical users to operate and maintain the system without requiring programming skills This study demonstrated that combining no-code workflow automation, AI-based text summarization, and agile development practices can provide an effective and practical solution for automating meeting documentation in organizational environments.