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Journal of Sustainable Innovation Engineering
Published by Institute Of Advanced Knowledge and Science
ISSN : -     EISSN : 30898609     DOI : https://doi.org/10.69693/sustainable
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering
Journal of Sustainable Innovation Engineering is published by the Institute Of Advanced Knowledge and Science in helping academics, researchers, and practitioners to disseminate their research results. Journal of Sustainable Innovation Engineering is a blind peer-reviewed journal dedicated to publishing quality research results in the field of sustainable engineering and innovative technologies. All publications in the Journal of Sustainable Innovation Engineering Journal are open access which allows articles to be available online for free without any subscription. Journal of Sustainable Innovation Engineering is a national journal with e-ISSN: 3089-8609, and is have fee of charge in the submission process and review process. Journal of Sustainable Innovation Engineering publishes articles periodically four a year, in March, July, and November. Journal of Sustainable Innovation Engineering uses Turnitin plagiarism checks, Mendeley for reference management and supported by Crossref (DOI) for identification of scientific paper.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 13 Documents
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Geometric Evaluation of the Influence of Bends on Road User Suitability: A Systematic Literature Review Risnandar, Moch Aris; Mahesa, Riski; Juliar, Eka; Isradi, Muhammad
Journal of Sustainable Innovation Engineering Vol. 1 No. 3 (2025): November
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/sustainable.v1i3.15

Abstract

Tujuan dari studi ini adalah untuk mengevaluasi pengaruh karakteristik geometri tikungan jalan terhadap kepatuhan pengguna jalan menggunakan pendekatan Tinjauan Literatur Sistematis (SLR). Pencarian literatur dilakukan di berbagai basis data ilmiah, menghasilkan total awal 1.457 artikel. Setelah penyaringan dan evaluasi, 31 artikel dipilih dan ditinjau secara menyeluruh. Temuan studi menunjukkan bahwa komponen geometris seperti radius tikungan, superelevasi, dan jarak pandang henti berdampak signifikan pada keselamatan dan kenyamanan pengguna jalan. Sejumlah studi menunjukkan bahwa tikungan yang dirancang di bawah spesifikasi standar meningkatkan risiko kecelakaan, terutama di lingkungan yang tidak ramah pengguna. Geometri jalan yang selaras dengan persepsi dan harapan pengguna meningkatkan rasa aman dan nyaman saat berkendara. Studi ini menekankan bahwa desain tikungan berbasis bukti dan terstandarisasi secara teknis sangat penting untuk mendukung keselamatan lalu lintas.
Innovative Edge Detection Approaches for Arabic Character Recognition in Kitab Kuning Images: A Comparison of Sobel, Prewitt, and Canny takyudin, takyudin
Journal of Sustainable Innovation Engineering Vol. 1 No. 3 (2025): November
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/sustainable.v1i3.20

Abstract

The preservation of Kitab Kuning manuscripts as part of Islamic intellectual heritage requires digitalization and image enhancement to ensure readability and sustainability. One of the essential stages in digital manuscript processing is edge detection, which plays an important role in extracting the structural shape of Arabic characters. This study aims to compare the performance of three classical edge detection methods—Sobel, Prewitt, and Canny—in detecting the edges of Arabic characters in Kitab Kuning manuscript images. Each manuscript image was preprocessed through grayscale conversion and Gaussian filtering before applying the three edge detection algorithms. The resulting edge images were evaluated using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM). The experimental results show that the Canny method consistently produces lower MSE values, higher PSNR, and more stable SSIM compared to Sobel and Prewitt, resulting in clearer, smoother, and more accurate edge structures resembling the original Arabic characters. Prewitt demonstrates moderate performance, while Sobel tends to generate rougher edges and is more sensitive to noise. Based on these findings, the Canny method is recommended as the most effective approach for Arabic character edge detection in the digital preservation of Kitab Kuning manuscripts, supporting better quality enhancement and long-term usability of digital Islamic manuscripts
Deepfakes, Public Trust, and Online Discourse: Sentiment Analysis of Responses to the “Guru Beban Negara” Hoax Clarification on Social Media Ashdaq, Muhammad; Jannah, Ummul Radiatul; Yourike, Yourike; Putri, Rezky Amalia; Mandasari, Nur Fitriayu
Journal of Sustainable Innovation Engineering Vol. 1 No. 3 (2025): November
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/sustainable.v1i3.22

Abstract

The rapid advancement of artificial intelligence technologies has introduced a new form of digital threat in the form of deepfakes, which have the potential to accelerate the spread of hoaxes and undermine public trust in official information. One notable and controversial example is the “Guru Beban Negara” hoax, which generated diverse and polarized reactions on social media platforms, despite the issuance of an official clarification by the authorities. This phenomenon suggests that institutional responses do not always succeed in mitigating negative public perceptions once misinformation has circulated widely. This study aims to examine public sentiment toward the official clarification by analyzing user comments on YouTube using the Naïve Bayes Classifier algorithm. Data were collected through web scraping techniques and subsequently processed through several preprocessing stages, including cleansing, normalization, tokenization, and stemming, to ensure data quality and analytical reliability. The findings reveal a strong predominance of negative sentiment among the 2,252 comments analyzed. The sentiment classification model achieved an accuracy rate of 73%, with the distribution indicating that most users expressed negative reactions, while only a small proportion conveyed positive sentiment. These results indicate that official clarifications have not been fully effective in alleviating negative public perceptions associated with deepfake-based hoaxes, particularly within the context of social media discourse.

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