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All Journal TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri Jurnal E-Komtek JURPIKAT (Jurnal Pengabdian Kepada Masyarakat)
Meilia Nur Indah Susanti
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Education Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences

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Journal : Jurnal E-Komtek

 1 
Application of Villamil-Molina in Virtual Reality Environmental Information on The ITPLN Campus Herman Bedi; Abdurrasyid; Meilia Nur Indah Susanti; Indrianto; M Yoga Distra Sudirman; Rahma Farah Ningrum; Yessy Asri; Joey Andrew Fransisco Sihombing; Azizah Arip Rambe
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 1 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i1.1700

Abstract

This study aims to apply Virtual Reality (VR) as an information medium in the ITPLN campus environment, focusing on the Villamil-Molina analysis method. The 3DVista app will be used as a VR content development platform. The research will evaluate accessibility, educational effectiveness, user acceptance, content availability, financial aspects, security, privacy, and environmental impact. The study results are expected to provide an in-depth understanding of the potential of VR, identify obstacles, and present recommendations to improve its implementation in the ITPLN campus environment by utilizing 3DVista applications. Villamil-Molina follows structured steps, uses the right creativity, and provides a satisfying experience for users.
Sistem Berbasis Penalaran Kasus untuk Deteksi Penyakit Tourette Syndrome Abdurrasyid; Indrianto, Indrianto; Meilia Nur Indah Susanti; Rima Rizqi Wijayanti
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2232

Abstract

Tourette Syndrome (TS) is a neurological disorder affecting children under 18, with an estimated prevalence of over 150,000 cases annually in Indonesia and 1% globally. Misdiagnosis rates of 20-30% complicate effective management. TS involves involuntary, repetitive tics, ranging from sudden movements or sounds to aggressive behaviors, posing significant challenges for diagnosis and treatment. This study utilizes an expert system with a case-based reasoning (CBR) approach to improve TS diagnosis. Interviews with TS patients and specialists provided data on symptoms and diagnostic structures. A weighting mechanism and an accumulation formula were implemented to deliver accurate diagnostic outcomes and first aid suggestions, optimized for minimal computing resources without reliance on extensive datasets. Testing on 10 patients, under expert supervision, demonstrated the system's ability to accurately diagnose and classify TS. The system effectively simulates expert-level TS detection, offering precise diagnosis and recommendations, potentially enhancing early intervention and reducing diagnostic errors.
Co-Authors Abdurrasyid Azizah Arip Rambe Darma Rusjdi Dewi Arianti Wulandari Efy Yosrita Herman Bedi Herman Bedi Agtriadi, Herman Bedi Indrianto Indrianto Indrianto Joey Andrew Fransisco Sihombing M Yoga Distra Sudirman Max Teja Ajie Ningrum, Rahma Farah Rahmad Evan Rima Rizqi Wijayanti Rizqia Cahyaningtyas Yessy Asri