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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Ilmiah Kedokteran Wijaya Kusuma Jurnal Sistem Cerdas JURNAL MAHAJANA INFORMASI Jurnal Teknologi Informasi Cyberku NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Kenduri: Jurnal Pengabdian Dan Pemberdayaan Masyarakat Jurnal Intelek Dan Cendikiawan Nusantara Jurnal TNI Angkatan Udara International Journal of Law, Crime and Justice PESHUM Medistra Medical Journal (MMJ)
Ahmad Ilham
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Aerospace Engineering Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy 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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Peningkatan Kompetensi Guru di SMK Muhammadiyah 2 Malang melalui Pelatihan Pengembangan Media Pembelajaran Berbasis Kecerdasan Buatan Faiq Madani; Ahmad Ilham; Muhammad Sam’an; Rima Dias Ramadhani; Akhmad Fathurrohman; Safuan Safuan; Muhammad Munsarif; Lukman Assaffat; Wendy Sarasjati; Dhendra Marutho
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 6 No. 1 (2026): Februari: NUSANTARA Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v6i1.7796

Abstract

This study aims to evaluate the effectiveness of the Artificial Intelligence-Based Learning Media Development Program (P3MP-AI) in enhancing teachers’ technological and pedagogical competencies at SMK Muhammadiyah 2 Malang. The program employed a descriptive approach using both quantitative and qualitative methods, including pre-test and post-test assessments, as well as direct observation of the training process. A total of 30 teachers from various disciplines actively participated in the program conducted on August 12, 2025. The evaluation results revealed an increase in the participants’ average scores from 100 to 130 out of a maximum of 150, indicating a significant improvement in their understanding of AI concepts and applications in education. Beyond competency enhancement, the training also fostered teachers’ confidence, creativity, and ability to integrate AI-based tools into interactive learning media. However, several challenges were identified, such as limited technological resources and time constraints in classroom implementation. Overall, this program has made a tangible contribution to strengthening teachers’ digital literacy and can serve as a replicable professional development model for other vocational schools seeking to advance AI-based educational transformation.
7. A COMPARATIVE ANALYSIS OF SPUKTA REGULATIONS: A STUDY OF VLOS OPERATIONAL PROCEDURES IN CONTROLLED AIRSPACE BETWEEN THE FAA, EASA, AND DGCA INDONESIA Muchammad Furqon; Ahmad Ilham; Ferdy Susanto; Kamal Muchdatas; Suroso; Salsabila
Jurnal TNI Angkatan Udara Vol 5 No 1 (2026): Jurnal TNI Angkatan Udara Triwulan Pertama
Publisher : Staf Komunikasi dan Elektronika, TNI Angkatan Udara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62828/jpb.v5i1.198

Abstract

This study aims to critically analyze and compare the SPUKTA VLOS operationalprocedure framework in the Control Area established by three major aviation authorities: theFederal Aviation Administration (FAA), the European Union Aviation Safety Agency (EASA),and the Directorate General of Civil Aviation (DGCA) Indonesia. The integration of SmallUnmanned Aircraft Systems (SPUKTA) or drones into civil airspace, particularly in the ControlArea (CTR), requires strict and uniform operational procedures. The most common Visual Lineof Sight (VLOS) operations pose a high risk in controlled airspace if not properly regulated.Using a descriptive qualitative method with comparative content analysis of primary regulatorydocuments (FAA Part 107, EASA Reg. (EU) 2019/947, pm 37 of 2020 and PM 63 of2021/CASR Part 107 Indonesia), the comparison focuses on five key procedural variables:Operational Clearance Mechanism, Operational Altitude Limit, Pilot CommunicationRequirements, Time Window Provisions, and Pre-flight Procedures. The results show thatwhile the FAA and EASA offer mature systems (automated LAANC vs. risk-based Geozone),the Indonesian DGCA relies on manual permitting processes and local authority discretion.This disparity indicates a gap in regional automation and standardization. This studyrecommends that the Indonesian DGCA consider implementing a real-time authorizationsystem and digital Geozone to improve compliance and efficiency of VLOS SPUKTAoperations in the Control Area.
Breast Cancer Classification Using Support Vector Machine Method and RBF Kernel Function Based on Clinical Data, Cancer Stage, and Immunohistochemistry Results Sherly Nur Ekawati; wati, mudy; Arya Iswara; Ahmad Ilham; Astri Aditya Wardhani
Jurnal Ilmiah Kedokteran Wijaya Kusuma Vol. 15 No. 1 (2026): March 2026
Publisher : Universitas Wijaya Kusuma Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30742/jikw.v15i1.4908

Abstract

Background: Breast cancer is one of the leading causes of cancer-related deaths among Indonesian women. Early detection and classification of molecular subtypes are crucial for determining appropriate therapy. Accurate determination of biological subtypes of breast cancer is essential for selecting optimal treatment strategies. This research aims to build and evaluate a breast cancer subtype classification model using the SVM with an RBF kernel. The subtypes classified include Luminal A, Luminal B, HER2+, and Triple Negative Breast Cancer, utilizing a combination of patient clinical data (age, tumor size, and tumor location), cancer stage, and the expression status of hormonal receptors ER and PR. The methodological steps include data preprocessing, feature selection, model training with cross-validation, and performance evaluation using metrics such as accuracy, precision, recall, F1-score, and the ROC-AUC curve. The results showed that the majority of patients' ages were in the range of 40–60 years, with dominant tumor sizes between 1 and 3 cm. Luminal A and B subtypes were more frequently observed in patients aged ≥50 years and at early stages, whereas HER2+ and TNBC were mostly observed in patients under 50 years with advanced stages. The established baseline SVM-RBF model achieved high accuracy (91%) but performed poorly at detecting minority subtypes, such as HER2+, with a recall = 0 and an F1-score = 0, indicating model bias toward the majority class. This study demonstrates that the SVM algorithm with the RBF kernel is effective for modeling breast cancer subtype classification using clinical data, cancer stage, and immunohistochemistry results.
Co-Authors A. Khoirul Anam Abdul Kudus Zaini Akhmad Fathurrohman Angelika Arya Iswara Astri Aditya Wardhani Asvia Rahayu Bahari Putra, Fajar Rahardika Catur Supriyanto Dhendra Marutho Didit Hermawan Faiq Madani Farida Yusuf Ferdy Susanto Heru Pranoto Islamiah Istikharah Kamal Muchdatas Lukman Assaffat M. Ridwan S. Ahmad Mifta Apriliah Miftah Arifin Muchammad Furqon Muhammad Idaham Muhammad Munsarif Muhammad Rizki Setyawan Muhammad Sam’an Nurul Fajri Ramadhani, Rima Dias RIMAYANI Romi Satria Wahono Safuan Safuan Salsabila Sherly Nur Ekawati Sitepu, Rahmadani Surahmanto Suroso Wahyu Mahaputra wati, mudy Wendy Sarasjati