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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) International Journal of Advances in Intelligent Informatics BAREKENG: Jurnal Ilmu Matematika dan Terapan Martabe : Jurnal Pengabdian Kepada Masyarakat Jurnal Samudra Ekonomi dan Bisnis Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Mediasosian : Jurnal Ilmu Sosial dan Administrasi Negara SEMAR IJECS: Indonesian Journal of Empowerment and Community Services Jurnal Dharma Bhakti Ekuitas Journal Competency of Business PELS (Procedia of Engineering and Life Science) Journal of Community Empowerment Journal of Transportation and Society Empowerment
Prasetyo, Heri
Department Of Informatics, Faculty Of Informatics And Data Science, Universitas Sebelas Maret, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Medical Image Segmentation Using a Global Context-Aware and Progressive Channel-Split Fusion U-Net with Integrated Attention Mechanisms Alfath Roziq Widhayaka; Heri Prasetyo
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 8 No 1 (2026): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v8i1.1371

Abstract

Medical image segmentation serves as a key component in Computer-Aided Diagnosis (CAD) systems across various imaging modalities. However, the task remains challenging because many images have low contrast and high lesion variability, and many clinical environments require efficient models. This study proposes CFCSE-Net, a U-Net-based model that builds upon X-UNet as a baseline for the CFGC and CSPF modules. This model incorporates a modified CFGC module with added Ghost Modules in the encoder, a CSPF module in the decoder, and Enhanced Parallel Attention (EPA) in the skip connections. The main contribution of this paper is the design of a lightweight architecture that combines multi-scale feature extraction with an attention mechanism to maintain low model complexity and increase segmentation accuracy. We train and evaluate CFCSE-Net on four public datasets: Kvasir-SEG, CVC-ClinicDB, BUSI (resized to 256 × 256 pixels), and PH2 (resized to 320 × 320 pixels), with data augmentation applied. We report segmentation performance as the mean ± standard deviation of IoU, DSC, and accuracy across three random seeds. CFCSE-Net achieves 79.78% ± 1.99 IoU, 87.21% ± 1.72 DSC, and 96.70% ± 0.59 accuracy on Kvasir-SEG, 88.11% ± 0.86 IoU, 93.42% ± 0.55 DSC, and 99.04% ± 0.09 accuracy on CVC-ClinicDB, 69.33% ± 2.66 IoU, 78.80% ± 2.65 DSC, and 96.30% ± 0.51 accuracy on BUSI, and 92.27% ± 0.52 IoU, 95.92% ± 0.30 DSC, and 98.06% ± 0.16 accuracy on PH2. Despite its strong performance, the model remains compact with 909,901 parameters and low computational cost, requiring 3.24 GFLOPs for 256 × 256 inputs and 5.07 GFLOPs for 320 × 320 inputs. These results show that CFCSE-Net maintains stable performance on polyp, breast ultrasound, and skin lesion segmentation while it stays compact enough for CAD systems on hardware with low computational resources.
Leveraging Generative Artificial Intelligence to Enhance the Quality of Adaptive Learning at the Junior High School Level in Surakarta City Winarno; Heri Prasetyo; Wiranto; Sari Widya Sihwi; Herdito Ibnu Dewangkoro; Tarno; Anik Indriyani
IJECS: Indonesian Journal of Empowerment and Community Services Vol. 7 No. 1 (2026): IJECS: Indonesian Journal of Empowerment and Community Services
Publisher : Universitas Veteran Bangun Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32585/ijecs.v7i1.8005

Abstract

ABSTRACT The primary and secondary education curriculum in Indonesia changes almost every year. These changes lead to administrative adjustments in teaching and learning documents. Consequently, teachers tend to spend less time focusing on delivering instructional content and ensuring meaningful student learning, and instead devote substantial effort to reformatting lesson plans (RPP), student activity reports (LKPD), and other administrative documents. In many cases, these documents remain largely unchanged from year to year, with minimal innovation. To address this issue, a more efficient approach is required to enable teachers to innovate in designing instructional materials, lesson plans, student worksheets, and assessment instruments. The aim of this community engagement initiative is to enhance pedagogical and digital literacy in the use of generative AI to assist teachers in drafting learning objectives, structuring classroom activities, generating guiding questions, developing variations in instructional strategies, and producing effective teaching materials tailored to students’ needs. This activity was implemented using the ADDIE framework (Analysis, Design, Development, Implementation, and Evaluation). The results indicate that participants demonstrated a strong understanding of the material and an improvement in their cognitive knowledge. Specifically, 41.67% of participants reported that the material was easy to understand, while 58.33% stated that it was very easy to understand. Furthermore, 75% of participants indicated that the facilitator delivered the material very well, and 25% rated the delivery as good. A recommendation for future initiatives is the need for ongoing support through a post-training mentoring programme to ensure an understanding of the ethical use of generative AI. Keywords: generative AI, education, prompt, adaptif learning.
Deep residual neural networks for inverse halftoning Heri Prasetyo; Muhamad Aditya Putra Anugrah; Alim Wicaksono Hari Prayuda; Chih-Hsien Hsia
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 6: December 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i6.24230

Abstract

This paper presents a simple technique to perform inverse halftoning using the deep learning framework. The proposed method inherits the usability and superiority of deep residual learning to reconstruct the halftone image into the continuous-tone representation. It involves a series of convolution operations and activation function in forms of residual block elements. We investigate the usage of pre-activation function and standard activation function in each residual block. The experimental section validates the proposed method ability to effectively reconstruct the halftone image. This section also exhibits the proposed method superiority in the inverse halftoning task compared to that of the handcrafted feature schemes and former deep learning approaches. The proposed method achieves 30.37 dB and 0.9481 on the average peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) scores, respectively. It gives the improvements around 1.67 dB and 0.0481 for those values compared to the most competing scheme.
Pelatihan Cyber Security Sebagai Pengetahuan Dasar Keamanan Untuk Peningkatan Security Awarness Winarno Winarno; Wiranto Wiranto; Bambang Harjito; Heri Prasetyo; Sari Widya Sihwi
SEMAR (Jurnal Ilmu Pengetahuan, Teknologi, dan Seni bagi Masyarakat) Vol 14, No 1 (2025): Mei
Publisher : LPPM UNS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/semar.v14i1.99770

Abstract

Dalam beberapa tahun terakhir di tahun 2024 banyak terjadi insiden keamanan, baik kebocoran, hacking, defacing dan lain-lainnya. Hal ini terjadi dikarenakan masyarakat di Indonesia banyak yang kurang akan security awarness. Kesadaran keamanan siber yang masih kurang ini menjadi permasalahan serius. Seperti yang disampaikan oleh Bapak Sandi Indonesia yaitu ingatlah bahwa kekhilafan satu orang saja cukup sudah menyebabkan keruntuhan negara. Oleh karena itu karena pentingnya hal tersebut, sebagai solusi untuk peningkatannya adalah menyelenggarakan pelatihan cyber security. Dalam pelaksanaan kegiatan ini menggandeng beberapa lembaga dalam negeri dan luar negeri yaitu Diskominfo SP Kota Surakarta, UPTD Solo Technopark dan Rapixus. Inc. Taiwan. Pelatihan meliputi pemberian teori dasar mengenai cyber security dan praktik melakukan penetrasi, attack dan menanggulangi serangan. Hasil dari pelatihan ini didapat bahwa 87,9% peserta mendapatkan kebaruan pengetahuan, 87,9% mendapatkan kemanfaatan dan 61,4% peserta merasakan kemudahan menerima materi
Co-Authors Abiaz Fazel Maula Sandy Alfath Roziq Widhayaka Alim Wicaksono Hari Prayuda Anik Indriyani Antoni Wibowo Arif Senja Fitrani Azzahra, Ummi Fajarina Bambang Harjito, Bambang Basuki, Akbari Indra Berton Arie Putra Akardihas Chih-Hsien Hsia Dewi Retno Sari Saputro, Dewi Retno Didi Rosiyadi Elidasari, Devi Erliyani, Dian Fathur Rohman, Muhammad Anang Fifi Swandari Herdito Ibnu Dewangkoro Hermansyah Hermansyah Heru Priyanto Horng, Shi Jinn Hsia, Chih-Hsien Indah Safiira, Putri Iwan Setiawan Khairina, Fadiah Kristin Anita Indriyani Muhamad Aditya Putra Anugrah Prasetya Anggrahini, Wahyu Prissando, Fendy Artha Rintis Hadiani Rr. Eko Giyartiningrum Sari Widya Sihwi Sari Widya Sihwi, Sari Widya Sarira, Beatrix Datu setiono setiono Sidiq, Krisna Sulistiyowati, Ely Surifah Surifah Tarno Teguh Pramono Wahono Wahono Wibowo, Gusti Ngurah Adhi Wijaya, Anugrah Winarno Winarno Winarno Winarno Winarno Wiranto Wiranto Wiranto Yudha, Ery Permana Yuli Aryani, Desi