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All Journal JUITA : Jurnal Informatika Seminar Nasional Informatika (SEMNASIF) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Insect (Informatics and Security): Jurnal Teknik Informatika EDUKATIF : JURNAL ILMU PENDIDIKAN Al-Tamimi Kesmas: Jurnal Ilmu Kesehatan Masyarakat (Journal of Public Health Sciences) Jurnal Mantik Mobile and Forensics JITU : Journal Informatic Technology And Communication Idealis : Indonesia Journal Information System Jurnal Adijaya Multidisiplin Jurnal Informatika: Jurnal Pengembangan IT
Wicaksono Yuli Sulistyo
Universitas Siber Muhammadiyah, Indonesia
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Public Health Social Sciences Other

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Deteksi Tepi Menggunakan Metode Operator Prewitt dan Kirsch pada Citra Uang Kertas Sulistyo, Wicaksono Yuli; Arifah, Amalina Nur; Pratiwi, Septia Ayu
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.6292

Abstract

The importance of edge detection in image processing, especially on banknote objects, prompted this research to carry out an analysis of two edge detection methods, namely the Prewitt and Kirsch operators. five images of banknotes with different denominations (2000, 5000, 10000, 20000 and 50000) were taken as research objects. The edge detection method is implemented using MATLAB, utilizing both Prewitt and Kirsch operators. Image quality assessment uses PSNR, Histogram and Pixel value parameters. The comparison results show that the Prewitt and Kirsch operators provide optimal edge detection results, producing clear and sharp edges in the banknote image. The edge detection quality assessment was carried out through the PSNR metric, and both showed PSNR values above 30 dB, indicating good quality in terms of clarity and accuracy. Comparison of the Histogram and Pixel values shows that the Kirsch method has a higher Histogram and the Prewitt method has a higher Pixel value.
Evaluasi Tingkat Keamanan Informasi SIA UIN SUKA Berdasarkan Indeks KAMI (Information Security ) 4.0. Muhammad Haedar Zhafran Hidayatullah; Wicaksono Yuli Sulistyo; Septia Ayu Pratiwi
JITU Vol 9 No 1 (2025)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v9i1.1802

Abstract

Informasi adalah asset organisasi yang sangat berharga. Oleh sebab itu informasi menjadi salah satu objek serangan untuk dieksploitasi. Tujuan utama keamanan sistem informasi adalah menjaga 3 (tiga) atribut yaitu kerahasiaan (confidentiality), keutuhan (integrity) dan ketersediaan (availability). UIN Sunan Kalijaga memiliki unit kerja yang mempunyai tugas dan kewajiban untuk mengelola dan memberikan informasi. Perlu dilakukan evaluasi keamanan sistem informasi untuk mendapatkan gambaran kondisi kesiapan dan kematangan keamanan informasi. Indeks keamanan informasi disingkat KAMI adalah alat evaluasi yang dirilis oleh Kementrian Komunikasi dan Informasi yang berfungsi untuk menganalisa tingkat keamanan informasi di instansi. Didapati tingkat kematangan keamanan informasi di UIN Sunan Kalijaga masih tergolong rendah dan butuh perbaikan untuk kekurangan yang ditemukan di sistem manajemen keamanan informasi.
Analisis Perbandingan Tool FTK Imager dan PhotoRec dalam Pemulihan Data Flashdrive Berbasis Metode Statik Forensik Muhammad Immawan Aulia; Panggah Widiandana; Wicaksono Yuli Sulistyo; Siti Hartinah; Muhammad Azam Hasani
JITU Vol 9 No 1 (2025)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v9i1.1814

Abstract

Penelitian ini bertujuan untuk mengevaluasi efektivitas dua tools digital forensik, yaitu FTK Imager dan PhotoRec, dalam proses recovery file dari hasil imaging data. Hasil penelitian menunjukkan bahwa FTK Imager berhasil melakukan recovery secara utuh terhadap enam file audio dan satu file teks, dengan format nama file dan nilai hash yang identik dengan bukti digital asli. Sebaliknya, PhotoRec hanya berhasil melakukan recovery terhadap empat file audio dan satu file teks, dengan dua file audio menunjukkan perbedaan nilai hash dibandingkan dengan aslinya. Temuan ini menunjukkan bahwa FTK Imager memiliki tingkat akurasi dan keandalan yang lebih tinggi dalam proses pemulihan data digital dibandingkan dengan PhotoRec, terutama dalam menjaga integritas data yang direkonstruksi.  
An Exploration of Digital Sentiment and Individual Knowledge as Predictors of Tuberculosis Vaccination Decisions: A Social Media and Survey-Based Study Desy Eliana; Wicaksono Yuli Sulistyo; Muhamad Rosidin
Al Tamimi Kesmas: Jurnal Ilmu Kesehatan Masyarakat (Journal of Public Health Sciences) Vol 14 No 1 (2025): Al-Tamimi Kesmas: Jurnal Ilmu Kesehatan Masyarakat (Journal of Public Health Sci
Publisher : Institut Kesehatan dan Teknologi Al Insyirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35328/kesmas.v14i1.2991

Abstract

Tuberculosis (TB) remains a major communicable disease in Indonesia with consistently high incidence rates, making vaccination a key preventive strategy. However, resistance toward the TB vaccine persists due to limited public knowledge and the influence of negative sentiments circulating on social media. This study aimed to examine the relationship between individual knowledge and vaccination decisions, while also analyzing public sentiment toward the TB vaccine on social media as an early indicator for designing epidemiological interventions. A mixed-methods approach was applied, combining a cross-sectional survey involving 100 respondents—which assessed TB knowledge, exposure to vaccine-related social media content, and BCG vaccination status—with sentiment analysis using the Naive Bayes algorithm on 26 social media posts from Twitter, TikTok, and Instagram. Logistic regression results indicated that higher knowledge about TB (OR = 1.76, 95% CI: 1.17–2.67) and increased exposure to social media content (OR = 1.46) were significantly associated with positive vaccine decision-making. Among the analyzed posts, 53.8% conveyed positive sentiment, 26.9% were neutral, and 19.2% expressed negative views, with positive sentiments predominantly found in educational content shared by healthcare professionals. These findings highlight the alignment between individual knowledge and digital public sentiment in influencing vaccination decisions, underscoring the importance of integrating health education and digital data monitoring in TB prevention effort.
Co-Authors Anton Yudhana Arifah, Amalina Nur Aulia, Muhammad Immawan Desy Eliana Hidayatullah, Muhammad Haedar Zhafran Imam Riadi Imam Riadi Khairina Eka Setyaputri Muhamad Rosidin Muhammad Azam Hasani Muhammad Haedar Zhafran Hidayatullah Muhammad Immawan Aulia Panggah Widiandana Pratiwi, Septia Ayu Purwanti, Bernadeta Siti Rahayu Rosidin, Muhamad Septia Ayu Pratiwi Siti Hartinah Widiandana, Panggah