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Sosialisasi Keamanan Siber untuk Pelajar: Upaya Meningkatkan Literasi Digital di Era Modern Muhammad Al Makky; Nicholas Efesus Barus; Chelsea Georgia Sevilla Wonmaly; Muhammad Roghib Roghib; Yerick Rafaldy De Fretes; Muhammad Faris Fathoni
JAPATUM: Jurnal Pemanfaatan Teknologi untuk Masyarakat Vol 3 No 1 (2024): Maret 2024
Publisher : MATRADIPTI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59328/JAPATUM.2024.3.1.97

Abstract

Kegiatan "Sosialisasi Cyber Security untuk Pelajar" bertujuan untuk meningkatkan kesadaran dan pengetahuan pelajar SMA mengenai keamanan siber. Seminar ini diadakan sebagai upaya edukasi terhadap ancaman digital yang semakin meningkat, khususnya di kalangan pelajar, yang merupakan kelompok rentan. Dengan pendekatan interaktif dan diskusi mendalam, kegiatan ini diharapkan dapat membantu pelajar memahami ancaman siber, langkah-langkah pencegahan, dan solusi penanganan jika terjadi insiden (Santoso, 2021). Melalui pemahaman yang lebih baik, para pelajar diharapkan menjadi pengguna teknologi yang lebih bijak dan aman dalam menghadapi era digital.
Dress Code Selection Recommender System Based on Smartphone Adhitya, Venus Lidzikri; Irsan, Muhamad; Fathoni, Muhammad Faris; Zakaria, Diky
Journal of Electrical, Electronic, Information, and Communication Technology Vol 6, No 1 (2024): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.6.1.82934

Abstract

In the era of rapidly developing information technology, the existence of smartphones has become an integral part of everyday life. Appearance and choice of dress code play a crucial role in a person's self-image. Therefore, this research aims to design a smartphone-based dress code selection recommendation system. This system will use clothing usage data, user preferences, and event context to provide relevant dress code recommendations. With this solution, it is hoped that users can easily and efficiently choose the appropriate dress code, increase self-confidence, and create a pleasant dressing experience. This research contributes to the development of smartphone-based applications to support users' lifestyle and personal appearance. This application not only provides dress code inspiration, but also makes it easier for users to make decisions regarding clothing choices. Model testing using Machine Learning with the K-Nearest Neighbor (KNN) algorithm shows satisfactory accuracy, precision and recall, namely 83.67%, 83.82% and 99.34%. This application has the potential to be a useful tool helping users live an informed fashion lifestyle and according to personal preferences, and also minimize the waste of time that would occur when choosing clothes.