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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JBIO: jurnal biosains (the journal of biosciences) AGRIKA PROMUSIKA: Jurnal Pengkajian, Penyajian, dan Penciptaan Musik Jurnal Informatika dan Teknik Elektro Terapan THE JOURNAL OF MUHAMMADIYAH MEDICAL LABORATORY TECHNOLOGIST Jurnal Masharif al-Syariah: Jurnal Ekonomi dan Perbankan Syariah JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL PENGABDIAN KEPADA MASYARAKAT YUME : Journal of Management Jurnal Informatika Global Jurnal Analis Medika Biosains (JAMBS) Jurnal Ilmiah Akuntansi dan Finansial Indonesia Jurnal Review Pendidikan dan Pengajaran (JRPP) Biopendix: Jurnal Biologi, Pendidikan dan Terapan Jurnal Abdimas Madani dan Lestari (JAMALI) Jurnal PORKES Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Advanced in Information and Industrial Technology (JAIIT) Hijai - Journal on Arabic Language and Literature Jurnal Computer Science and Information Technology (CoSciTech) ABDI MASSA: Jurnal Pengabdian Nasional JAKA (Jurnal Akuntansi, Keuangan dan Auditing) Arcitech: Journal of Computer Science and Artificial Intelligence Journal of Artificial Intelligence and Digital Business Al-Aqwam: Jurnal Studi Al-Qur'an dan Tafsir Al-Fahmu: Jurnal Ilmu Al-Qur'an dan Tafsir VISA: Journal of Vision and Ideas AJER : Advanced Journal of Education and Religion Malacca: Journal of Management and Business Development
Hidayat, Muhammad Taufiq
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Public Health Social Sciences Other

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In Silico Detection of Antimicrobial Resistance and Virulence Genes in Methicillin Resistant Staphylococcus aureus Clinical Isolates: A Comparative Genomics Approach Hidayat, Muhammad Taufiq; Prayekti, Endah; Romdloni, Muhammad Afwan; Syah, Seggaf Achmad
BIOPENDIX: Jurnal Biologi, Pendidikan dan Terapan Vol 13 No 1 (2026): Biopendix: Jurnal Biologi, Pendidikan & Terapan
Publisher : Program Studi Pendidikan Biologi FKIP Unpatti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/biopendixvol13issue1page7-13

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) remains a formidable threat in both community and healthcare settings, thanks to its ability to evade β-lactam antibiotics and accumulate resistance to multiple drug classes. Here, we sequenced and compared the genomes of 13 recent clinical MRSA isolates alongside two well-characterized reference strains (N315 and NCTC 8325). By applying the ResFinder and VirulenceFinder pipelines, we rapidly cataloged each strain’s antibiotic resistance and virulence repertoire. Every MRSA isolate carried the hallmark mecA gene, and most also harbored blaZ, which encodes penicillinase. Resistance determinants for aminoglycosides (aac(6′)-Ie-aph(2″), aph(3′)-III), macrolides (erm(C), mph(C)), and chloramphenicol (cat variants) appeared in various combinations across the collection. On the virulence side, genes for α- and γ-hemolysins (hla, hlgABC) were universal, and nearly all strains possessed phage-encoded immune-evasion factors (sak, scn). The total count of virulence genes ranged from ten to fourteen per genome, peaking in two particularly gene-rich isolates. Our findings highlight the genetic diversity of MRSA, where multidrug resistance and a broad toxin arsenal coexist. Moreover, this study underscores the speed and reliability of in silico screening tools for antimicrobial-resistance surveillance and comparative genomics. Future work should integrate laboratory assays and patient data to link these genomic profiles to clinical outcomes.
Analisis Rekomendasi Media Promosi PPDB SMA Nurul Falah Pekanbaru dengan Algoritma K-Means Clustering Hidayat, Muhammad Taufiq; Emansa Hasri Putra; Dini Nurmalasari
Computer Science and Information Technology Vol 6 No 3 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i3.10499

Abstract

The advancement of information technology has significantly transformed how educational institutions conduct promotional activities and student admissions. The shift toward digital behavior among society requires schools to adopt more adaptive and data-driven marketing strategies. SMA Nurul Falah Pekanbaru, as one of the private high schools, has experienced a decrease in student enrollment after the Covid-19 pandemic. Conventional promotional methods such as banners, billboards, and printed brochures have proven less effective in reaching prospective students. This research aims to analyze the effectiveness of promotional media based on student characteristics using the K-Means Clustering algorithm as a segmentation method. The dataset was obtained from three years of PPDB registration records, including demographic, socioeconomic, school origin, and promotion media information. The analysis process involved several stages, namely data preprocessing, exploratory data analysis (EDA), determination of the optimal number of clusters using the Elbow and Silhouette methods, and the development of a web-based recommendation system using Python, PHP, and MySQL. The results indicate that the optimal number of clusters is k=4 with a Silhouette Score of 0.351. The four clusters represent distinct behavioral patterns in accessing educational information, with digital media emerging as the most effective channel. The developed recommendation system provides decision support for the school in designing promotional strategies that are more efficient, measurable, and accurately targeted through data analytics-based insights.
Co-Authors Achmad Maqsudi, Achmad Achyar Zein, Achyar Amelia, Neneng Musyrifatul Andini, Ary Anugrah Nur Warthadi Astuti, Rahayu Fuji Aulady, M. Ferdaus Noor Azrul Rizki Busro, B. Destriana, Rachmat Eko Hari Rachmawanto Emansa Hasri Putra Ersalina Nidianti Fahmi, Muhammad Fuadhil Fakurazi, Sharida Ferdiansyah, Mudi Fiyadila, Rizka Gilang Nugraha Herman Yuliansyah, Herman Husnel Anwar Matondang, Husnel Anwar Junaidi, Teuku karman karman Katili, Wardiman W Khurin, Nazilatul Kurniawan, Ardhian Tomy Lavenia, Mirana Maharani Pertiwi Koentjoro Mahiruna, Adiyah Maki Zamzam Makruf, Mukhamat Rif’an Maula, Ahmad Inzul Miftahul Jannah Mochammad Imron Awalludin Muhammad Afwan Romdloni Muhammad Arifin Muhammad Hilmi Muhammad Ziyad Ulhaq Murdaningtias, Silma Mustofa, Alifudin Navis, Khiliah NGATIMIN, NGATIMIN Nila Sari Novera Herdiani, Novera Nurhasan, Muhammad Nuriana Nurmalasari, Dini Prayekti, Endah Putri Lestari, Ajeng Anindhita Putri, Anisa Qonita Putri, Ngiluhtara Aditiya Qulub, Latifatul Rastafael, Yoel Retno Susanti Rini, Puspita Rizki Maulana Ishaq Rohman, Abd. Salimi, Syafrina Maulidyatus Sandi, Tri Sari, Yuni Nur Malita Setyo Nugroho Shobihatus Syifak Sugeng Wanto Suheriyanto Suksmanatyo Sumiati Sumiati Sunaryo, Merry Syafiul Muzid Syah, Seggaf Achmad Syahrial Fuadi Syahrul Kurniawan Tri Utami Usman Valian Yoga Pudya Ardhana Vera Septi Sistiasih Wahyudi, Brian Fitri Wardatul Jannah, Wardatul Widya Novita Sari Yulianto Yulianto, Fernando Candra Zain, Salfa Salsabilah Zakaria, Zainal Arifin