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All Journal Jurnal Informatika Jurnal Abdimas Indonesia : Jurnal Abdimas Indonesia KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Jurnal Minfo Polgan (JMP) Jurnal Sistim Informasi dan Teknologi OKTAL : Jurnal Ilmu Komputer dan Sains Journal Collabits
Roy Mubarak
Universitas Mercu Buana
Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Peningkatan Kompetensi Tata Kelola TI Melalui Pelatihan Itil 4 Foundation Implementasi Praktis di Lingkungan Masyarakat Bayu Waseso; Roy Mubarak
Jurnal Abdimas Indonesia Vol. 5 No. 1 (2025): Januari-Maret 2025
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34697/jai.v5i1.1314

Abstract

ITIL 4 Foundation merupakan kerangka kerja yang digunakan untuk tata kelola layanan teknologi informasi (TI) dalam menciptakan, menyampaikan, dan meningkatkan nilai layanan TI secara berkelanjutan. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan kompetensi tata kelola layanan TI melalui pelatihan berbasis ITIL 4 Foundation. Pelatihan mencakup prinsip-prinsip utama seperti Service Value System (SVS) dan Service Value Chain, yang relevan dengan transformasi digital masyarakat. Evaluasi pre-test dan post-test menunjukkan peningkatan pemahaman peserta mengenai konsep tata kelola layanan TI. Studi kasus implementasi pelatihan ini menunjukkan bahwa ITIL 4 memiliki potensi strategis untuk mendorong inovasi dan efisiensi operasional di komunitas. Hasil kegiatan diharapkan dapat membantu masyarakat dalam menerapkan ITIL 4 untuk meningkatkan kualitas layanan TI.
Penerapan Bahasa Pemrograman HTML Python sebagai perangkat pendukung dalam pelayanan Masyarakat Pada Tim PKK Kelurahan Duri Kepa Kebon Jeruk Jakarta Barat Mohamad Yusuf; Roy Mubarak; Rushendra Rushendra; Siti Maesaroh; Nungky Awang Candra
Jurnal Abdimas Indonesia Vol. 5 No. 1 (2025): Januari-Maret 2025
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34697/jai.v5i1.1327

Abstract

Tim Pemberdayaan dan Kesejahteraan Keluarga (PKK) di Kecamatan Duri Kepa berperan penting dalam menyebarkan informasi dan mendukung pengambilan keputusan tentang kesehatan masyarakat. Dengan meningkatnya kebutuhan akan solusi berbasis web, pengetahuan tentang teknologi seperti HTML, CSS, dan Python menjadi semakin krusial. Teknologi ini memungkinkan pengembangan sistem informasi yang lebih interaktif dan efektif, bahkan untuk pemula. Untuk menghadapi tantangan ini, program pelatihan telah disiapkan untuk memberikan anggota PKK keterampilan yang diperlukan dalam pengembangan web. Pelatihan ini menerapkan metode pembelajaran interaktif dan langsung di laboratorium universitas, dengan penekanan pada praktik HTML dan Python. Metode ini memberikan kesempatan bagi peserta untuk menerapkan keterampilan yang diperoleh dalam proyek berbasis web yang relevan dengan tugas mereka di PKK. Hasil dari kegiatan ini menunjukkan bahwa pelatihan berlangsung sukses dan peserta menunjukkan antusiasme yang tinggi. Mereka merasa nyaman dalam mengikuti pelatihan dan mampu menggunakan pengetahuan tentang HTML dan Python untuk membuat aplikasi sederhana. Program ini diharapkan dapat meningkatkan efektivitas intervensi kesehatan di tingkat komunitas serta mendukung pengambilan keputusan yang berbasis data dan berkelanjutan dalam konteks kesehatan masyarakat.
The Impact of Digital Transformation on Talent Recruitment Strategies in Modern Human Resource Management Sunardi Ginting; Karno Diantoro; RR Roosita Cindrakasih; Roy Mubarak; Suseno
Jurnal Minfo Polgan Vol. 12 No. 2 (2023): Artikel Penelitian 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v12i2.13410

Abstract

Along with technological advances, digital transformation has become a major phenomenon in various sectors, including in the business world and human resource management (HRM). HRM is undergoing a major revolution in addressing digital transformation. This research aims to examine the impact of digital transformation on talent recruitment strategies in modern human resource management. The method includes a thorough examination of literature using qualitative analysis, with the aim of gaining a comprehensive comprehension of the topic spanning from 2017 to 2023. The study results show that digital transformation has significantly changed the paradigm of talent recruitment in human resource management (HRM). From the use of digital platforms to the application of artificial intelligence (AI) and data analytics, companies must constantly adapt to stay competitive and attract the best talent. More efficient recruitment processes, empowerment of job seekers, and the possibility of work flexibility are positive outcomes of this transformation. However, ethical challenges such as bias in algorithms and the protection of personal data also need serious attention.
The Role of ChatGPT in Business Information Systems to Support Strategic Decision Making in Medium-Scale Enterprises Karno Diantoro; Era Sari Munthe; Agus Herwanto; Roy Mubarak; Nanik Istianingsih
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13673

Abstract

Medium-scale companies often operate in dynamic and competitive business environments. Faced with market changes and new opportunities, timely and accurate strategic decisions are key to maintaining and enhancing the competitiveness of the company. This research aims to examine the role of ChatGPT in business information systems to support strategic decision-making in medium-scale enterprises. The research method employed is a literature review with a qualitative approach and descriptive analysis. Descriptive analysis will be used to present information from systematically selected articles from Google Scholar within the timeframe of 2014-2024. The study results indicate that in the continuously evolving digital era, medium-scale companies increasingly rely on technology to address increasingly complex business challenges. One innovation playing a significant role in today's business landscape is the presence of ChatGPT. As an artificial intelligence model capable of understanding and generating text naturally, ChatGPT has a significant impact on business information systems and supports strategic decision-making in these companies.
Using Tensorflow for Clean and Messy Room Image Classification with Python Gilas Adi Saputra; Damar Pratama Ristadias Hariyanto; Roy Mubarak
Journal Collabits Vol. 3 No. 2 (2026)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v3i2.27274

Abstract

Image classification is a fundamental computer vision task that can support automated visual monitoring in domestic, educational, and workplace environments. This study develops a transparent baseline pipeline using TensorFlow 2.x, Keras, and Python to distinguish clean and messy room images. The dataset contains 192 training images, with 96 images in each class, and 20 validation images, with 10 images in each class. All images are resized to 150 x 150 pixels and normalized to a 0-1 range. Rotation, horizontal flipping, and shearing are applied only to the training data, while validation images are normalized without random transformation. The sequential convolutional neural network contains four convolution-pooling blocks, a fully connected layer, and a sigmoid output for binary classification. Qualitative testing with two external images produced labels that were consistent with visual observation: the cluttered room was classified as messy and the organized room as clean. These demonstrations confirm that the pipeline operates from image input to class prediction, but they do not establish broad generalization or perfect accuracy. The main contribution is a reproducible small-data workflow that documents dataset distribution, preprocessing, augmentation, model parameters, validation procedures, and prediction thresholds. The study is limited by the small validation set, the absence of a large independent test set, and the lack of direct comparison with pretrained models. Future studies should evaluate transfer learning, larger datasets, repeated trials, and metrics such as precision, recall, F1-score, and confusion matrices.
Co-Authors Abdul Hamid Uzman Abrar Hiswara Bambang Utomo Bayu Waseso Damar Pratama Ristadias Hariyanto Era Sari Munthe Fifi Julfiati Gilas Adi Saputra H Jazuli Mukhtar H Jazuli Mukhtar Ham Idris Tumenggung Herwanto, Agus I Putu Dody Suarnatha Ichwan Nugroho Ichwan Nugroho Istianingsih, Nanik Karno Diantoro Mohamad Yusuf Muhamad Febryan Muhamad Ziaul Haq Nalis Hendrawan Nungky Awang Candra Nursalim Purbaratri, Winny RR Roosita Cindrakasih Rushendra, Rushendra Siti Maesaroh Sunardi Ginting Suseno