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All Journal Communications in Science and Technology JMBI UNSRAT (Jurnal Ilmiah Manajemen Bisnis dan Inovasi Universitas Sam Ratulangi) YUME : Journal of Management Jurnal Pengabdian kepada Masyarakat Nusantara Nusantara Hasana Journal Global Abdimas: Jurnal Pengabdian Masyarakat Inspiration: Jurnal Teknologi Informasi dan Komunikasi Journal of Embedded Systems, Security and Intelligent Systems Jurnal MediaTIK Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Aras, Rezty Amalia
Institut Teknologi Dan Bisnis Kalla
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Nursing Public Health Social Sciences Transportation Other

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PENGEMBANGAN KETERAMPILAN DIGITAL KREATIF SISWA MELALUI WORKSHOP UI/UX DAN PROTOTYPING DENGAN FIGMA DI SMA ATHIRAH KAJAOLALIDO Rezty Amalia Aras; Furqan Zakiyabarsi; Aulia Rahmawati; Hany Alexandra; Muhammad Fachrul Salam
Nusantara Hasana Journal Vol. 5 No. 8 (2026): Nusantara Hasana Journal, January 2026
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v5i8.1871

Abstract

Strengthening creative digital literacy at the high school level is necessary so that students can design digital solutions relevant to user needs and possess basic UI/UX skills to build their portfolios and prepare for study and careers. This activity addressed these needs through a Figma workshop facilitated at Athirah Kajaolalido High School. The workshop used focus group discussions (FGDs) to map needs and design learning scenarios, followed by a two-day workshop. The first day consisted of design thinking and project design sessions. The second day focused on mentoring prototype creation in Figma. The activity resulted in 28 groups of 3–5 students each, producing ideas and prototypes on various themes (education, school services, productivity, the environment, and mental health). Pitching was assessed using eight indicators: problem analysis to solution, user flow, usability, visual aesthetics, design consistency, creativity, pitch structure, and engagement and delivery. The questionnaire results showed an average score of 4.46 for satisfaction with the material, usefulness of the material in helping solve problems, and ease of use of Figma, using a scale of 1–5. The Figma workshop effectively improved students' basic understanding of the digital solution design process and their ability to produce prototypes and present ideas. A follow-up program with longer practice sessions and material reinforcement is recommended to optimize prototype quality and pitching skills.
PELATIHAN DESIGN THINKING DAN PROTOTYPING UI/UX UNTUK IDE STARTUP SISWA SMA Syamsul Rijal; Aulia Rahmawati; Rezty Amalia Aras; Furqan Zakiyabarsi; Hany Alexandria; Muhammad Fachrul Salam; Yogi Hady Afrizal; Andi Jamiati Paramita; Andi Hutami Endang; Kiki Resky Ramdhani Sucipto; Widia Febriyani
Nusantara Hasana Journal Vol. 6 No. 2 (2026): Nusantara Hasana Journal, July 2026
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v6i2.2294

Abstract

The development of digital technology has created a new ecosystem that requires young people, particularly Generation Z, to become not only passive digital consumers but also creators of innovative solutions through the startup ecosystem. An empathy-based Design Thinking approach is considered effective in producing human-centered solutions while shaping resilient, solution-oriented young entrepreneurial character. However, students at SMA SPIDI Maros still faced difficulties in understanding business idea validation and UI/UX prototype design. This community service program aimed to provide Design Thinking and UI/UX Prototyping training to support students' startup idea development while enhancing their digital literacy. The method employed a two-session training and workshop, consisting of a Design Thinking presentation and a UI/UX Prototyping workshop using Figma, implemented through four stages: identifying participant needs, designing materials, conducting the activity, and evaluation with follow-up. The program was held on 28 January 2026 and attended by 32 participants from grades 10 to 12. Evaluation results showed all indicators fell into the "Very Good" category, with the overall usefulness indicator scoring highest at 4.84/5 (97% agreement), while ease of using Figma scored lowest at 4.41/5 due to limited workshop time. These findings underscore the importance of continuous, multi-session mentoring programs for high school students in the future.
A Comparative Study of Decision Tree and Gradient Boosting Tree Algorithms for Predicting College Enrollment Decisions of High School Students Rezty Amalia Aras; Utami Kusuma Dewi; Yabes Dwi Nugroho
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 1 (2026): March 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i1.10611

Abstract

The declining interest of high school students in pursuing higher education has become a major concern in Indonesia's education sector. This study aims to develop a data-driven predictive model to assist schools in identifying students’ decisions regarding further education. The study compares two popular classification algorithms, Decision Tree and Gradient Boosted Tree, using a dataset of 300 high school students comprising 10 attributes such as school accreditation, parental income, interest level, and residential status. The research method involves data preprocessing, model training, and performance evaluation using a confusion matrix to measure accuracy, precision, and recall. The results show that the Decision Tree algorithm achieved an accuracy of 76.67%, with a precision of 78.57% and a recall of 73.33% for the "college" class. Meanwhile, the Gradient Boosted Tree produced an accuracy of 73.33%, with a strength in recall for the "not attending college" class at 80%, but was less optimal in detecting students who pursued higher education. It can be concluded that the Decision Tree outperforms in terms of accuracy and interpretability, making it more suitable for use in school environments as a decision-support tool for early intervention, scholarship programs, and career counseling.
Analisis Pola Lelang di Ebay Menggunakan Metode K-Means Clustering Rezty Amalia Aras; Ilna Nardiyah
Jurnal MediaTIK Volume 7 Issue 2, Mei (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v7i2.2112

Abstract

Platform lelang daring telah menjadi aspek penting dalam perdagangan elektronik, yang menghadirkan peluang besar bagi analisis pola perilaku pengguna. Dalam penelitian ini, kami melakukan analisis pola lelang di platform eBay menggunakan metode klastering K-Means. Data transaksi lelang dikumpulkan dan dianalisis untuk mengidentifikasi pola yang mungkin tersembunyi di dalamnya. Langkah-langkah pembersihan data dilakukan untuk memastikan kualitas data yang optimal. Setelah itu, metode K-Means diterapkan untuk mengelompokkan transaksi lelang berdasarkan karakteristik tertentu. Hasil klastering divisualisasikan untuk memberikan wawasan tentang kelompok-kelompok transaksi yang berbeda. Evaluasi hasil klastering dilakukan dengan mempertimbangkan metrik evaluasi seperti inertia dan Silhouette Score. Temuan dari analisis ini dapat memberikan pemahaman lebih dalam tentang perilaku pengguna dalam melakukan lelang di platform eBay.
COMPARISON OF DATA MINING CLASSIFICATION TECHNIQUES FOR HEART DISEASE PREDICTION SYSTEM Rezty Amalia Aras; Noor Akhmad Setiawan
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 2 No. 2 (2022): Juli : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/teknik.v2i2.672

Abstract

DM is the process of analyzing data from different perspectives and gathering knowledge that can be used for different applications. Classification as one of the data mining techniques used to predict group membership. For example, the healthcare industry. DM provides a set of techniques for discovering hidden patterns from data. In this paper, we examine the heart disease dataset in order to obtain information or patterns that can be useful for making a decision. The test in this paper is a prediction of heart disease using three classification methods, namely OneR, decision tree and naive bayes. The results of this experiment show predictions from each experiment with different levels of prediction accuracy in each method used with 91.48% accuracy for the decision tree, 85.18% for naive Bayes and 76.3% for OneR.
Decision Support System (DSS) dengan Berorientasi -Solver Rezty Amalia Aras
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 2 No. 1 (2022): Maret : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/teknik.v2i1.917

Abstract

A Decision Support System (DSS) or decision support system is part of a computer-based information system (including knowledge-based/knowledge management systems) that is used to support decision-making within an organization or company. can also be said as a computer system that processes data into information to make decisions on specific semi-structured problems. In this paper, we try to solve a simple DSS with Microsoft Excel by using Solver.
Co-Authors Aditya Alfarizi, Dimas Afrizal, Yogi Hadi Akbar, Andi Makkulai Al Faqih, Shofwan Al Isra Denk Rimakka Andi Hutami Endang, Andi Hutami ANDI JAMIATI PARAMITA Aulia Rahmawati Darwis, Analta Dwi Nugroho H, Yabes Febriyani, Widia Furqan Zakiyabarsi Hanung Adi Nugroho Hany Alexandra Hany Alexandria Hutami Endang Igi Ardiyanto Ilna Nardiyah Kiki Resky Ramdhani Sucipto Muhaimin Nur, Muhammad Noor Akhmad Setiawan Ramdhani Sucipto, Kiki Reski Resky Ramdhani Sucipto, Kiki Resky Ramdhani, Kiki Rimakka, Al Isra Denk Sari, Emmy Puspita Siswahyudianto Sucipto, Kiki Resky Ramdhani Sukri Ahmad, Muhammad Syamsul Rijal Syamsul Rijal Tri Lestari Utami Kusuma Dewi Yabes Dwi Nugroho Yogi Hady Afrizal