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All Journal IJIS - Indonesian Journal On Information System Journal of System and Computer Engineering
Syamsuddin, Faris
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Computer Science & IT Decision Sciences, Operations Research & Management

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EFEKTIVITAS MEDIA EDUKASI VIRTUAL REALITY TERHADAP PENINGKATAN PENGETAHUAN DAN SIKAP PENGELOLAAN SAMPAH 3R: STUDI QUASI-EKSPERIMENTAL DI KOTA TERNATE Arief, Assaf; Fuad, Achmad; ., Rosihan; Syamsuddin, Faris
IJIS - Indonesian Journal On Information System Vol 10, No 2 (2025): SEPTEMBER
Publisher : POLITEKNIK SAINS DAN TEKNOLOGI WIRATAMA MALUKU UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36549/ijis.v10i2.423

Abstract

Pengelolaan sampah di Kota Ternate menghadapi tantangan serius dengan rendahnya kesadaran masyarakat hasil survei responden (82,4%) dan minimnya edukasi pengelolaan sampah (75,2%). Penelitian ini bertujuan menginisiasi efektivitas teknologi Virtual Reality (VR) imersif sebagai media edukasi untuk meningkatkan pengetahuan dan sikap masyarakat terhadap pengelolaan sampah berkelanjutan berbasis 3R (Reduce, Reuse, Recycle). Desain penelitian menggunakan mixed-method dengan pendekatan quasi-eksperimental pre-post design. Sampel awal terdiri dari 55 responden masyarakat Kota Ternate yang dipilih secara purposive sampling. Data dikumpulkan melalui kuesioner terstruktur dan wawancara mendalam, kemudian dianalisis menggunakan statistik deskriptif dan analisis tematik. Evaluasi awal menunjukkan respon positif terhadap implementasi VR, dengan 98% responden menyatakan setuju bahwa VR dapat meningkatkan pemahaman pengelolaan sampah. Fitur panduan 3R menjadi yang paling diminati (94,5%). Identifikasi masalah utama pengelolaan sampah meliputi kurangnya kesadaran masyarakat, minimnya fasilitas pengolahan, dan keterbatasan edukasi. Teknologi VR menunjukkan potensi signifikan sebagai media edukasi inovatif untuk transformasi perilaku pro-lingkungan di kawasan kepulauan, meskipun memerlukan pengembangan lebih lanjut untuk implementasi skala luas.Keywords: Virtual Reality, Edukasi Lingkungan, Pengelolaan Sampah 3R, Teknologi Imersif, Kota Ternate
Peramalan Beban Listrik Harian di Kota Ternate Menggunakan ELM Ilyas, Andi Muhammad; Rahman, Muhammad Natsir; Aswat, Aldi; Syamsuddin, Faris; Suparman, Suparman; Ashad, Bayu Adrian; Siswanto, Agus
Journal of System and Computer Engineering Vol 7 No 1 (2026): JSCE: January 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i1.2465

Abstract

The continuously increasing growth of electricity demand necessitates accurate and systematic planning of electric power systems to ensure power flow quality and system reliability. Ternate City, as one of the major activity centers in North Maluku Province, has experienced a substantial rise in electricity consumption, thereby requiring an effective and reliable load forecasting approach. This study aims to predict the daily electricity load in Ternate City using the Extreme Learning Machine (ELM) method. The analysis is conducted using historical electricity load data, which are processed through data preprocessing stages, dataset partitioning into training and testing sets, and ELM-based modeling. The performance of the proposed model is evaluated using the Mean Absolute Percentage Error (MAPE). The results indicate that the MAPE values for the training dataset range from 5.84% to 13.63%, corresponding to very good to good performance categories. Meanwhile, the testing dataset yields MAPE values ranging from 13.45% to 33.09%, which fall within the good to sufficient performance categories. Furthermore, the prediction results are able to accurately capture daily electricity load fluctuation patterns from Monday to Sunday, including peak load periods. Based on these findings, the ELM method demonstrates strong potential as a reliable approach to support electric power system planning and to enhance the quality and reliability of electricity supply in Ternate City.
Co-Authors ., Rosihan ACHMAD FUAD Agus Siswanto Assaf Arief, Assaf Aswat, Aldi Bayu Adrian Ashad Rahman, Muhammad Natsir Suparman Suparman