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Studi Komparatif Efektivitas Pembelajaran Bahasa Jepang melalui LuvLingua dan YouTube di Era Belajar Mandiri Digital
Kayla Attya Ramadhani
; Fikri Saputra
; Muhammad Yordi Septian
; Fadhlan Zaki Darmansyah
; Humannisa Rubina Lestari
Jurnal Rumpun Ilmu Bahasa dan Pendidikan
Vol 3
, No 3
(2025)
The rapid advancement of digital technology has transformed the landscape of language learning, particularly in the post-pandemic era where self-directed learning through mobile applications and online platforms is increasingly common. This study explores the effectiveness of two popular digital tools LuvLingua and YouTube in supporting independent Japanese language learning among Indonesian university students. LuvLingua offers a structured, gamified approach suitable for beginners, while YouTu...
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Analisis Usaha Totebag Custom Ramah Lingkungan sebagai Solusi Inovatif untuk Mengurangi Sampah Plastik
Ari Dian Prastyo
; Glorian Hilarius Kiantin Beda
; Fikri Saputra
; Wien Kuntari
Jurnal Riset dan Inovasi Manajemen
Vol 3
, No 1
(2024)
The issue of plastic waste has become a global environmental challenge, with Indonesia being one of the largest contributors. This study aims to analyze the business opportunity of eco-friendly custom tote bags as an innovative solution to reduce plastic waste in society. The research adopts the Business Model Canvas (BMC) framework to design strategies for a business that encompasses nine key elements. Findings reveal that custom tote bags made from eco-friendly materials such as muslin and can...
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Utilization of Digital Drawing Program With Hand Tracking Using the Mediapipe Framework
Jovita Nabilah Azizi
; Ester Olivia Silalahi
; Rafli Damara
; Muhammad Farhan Fahrezy
; Fikri Saputra
; Gema Parasti Mindara
; Endang Purnama Giri
International Journal of Multilingual Education and Applied Linguistics
Vol 1
, No 4
(2024)
This research focuses on the use of hand tracking technology in a drawing program based on the MediaPipe framework. The aim of this study is to develop a digital drawing system that can track hand movements in real-time without additional input devices like a mouse or stylus. This technology utilizes computer vision algorithms to detect and track the user's hand movements, which are then translated into strokes on the screen. The study employs a descriptive-qualitative method with a software exp...
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