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PENGARUH IMPLEMENTASI IDEOLOGI PANCASILA DALAM PEMBENTUKAN JIWA KEWARGANEGARAAN GENGERASI MUDA DI INDONESIA Maula Sandy, Abiaz Fazel; Najicha, Fatma Ulfatun
Borneo Law Review Vol 7, No 2 (2023): Desember 2023
Publisher : Fakultas Hukum Universitas Borneo Tarakan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35334/bolrev.v7i2.4660

Abstract

AbstrakJurnal ini membahas pengaruh implementasi ideologi Pancasila dalam pembentukanjiwa kewarganegaraan generasi muda di Indonesia. Studi ini bertujuan untukmenyelidiki peran pendidikan, pengaruh nilai-nilai Pancasila, tantangan danhambatan, serta rekomendasi dan strategi untuk meningkatkan implementasiideologi Pancasila. Metode penelitian yang digunakan adalah studi pustaka dananalisis kualitatif terhadap literatur terkait. Hasil penelitian menunjukkan bahwapendidikan memegang peran krusial dalam membentuk jiwa kewarganegaraangenerasi muda, dengan pendidikan kewarganegaraan yang memperkuat pemahamandan pengamalan nilai-nilai Pancasila menjadi faktor penting dalam proses ini. Nilainilai Pancasila memiliki pengaruh yang signifikan terhadap sikap dan perilaku generasi muda, yang tercermin dalam sikap inklusif, toleran, dan bertanggung jawab sebagai warga negara yang baik. Namun, implementasi ideologi Pancasila juga dihadapkan pada berbagai tantangan dan hambatan, seperti kurangnya pemahaman masyarakat, perbedaan interpretasi, pengaruh globalisasi, dan polarisasi politik. Oleh karena itu, rekomendasi dan strategi diperlukan untuk memperkuat implementasi ideologi Pancasila, termasuk peningkatan pendidikan kewarganegaraan, kampanye publik yang intensif, kerjasama antarstakeholder, dan pemanfaatan media massa dan teknologi informasi. Implementasi ideologi Pancasila dalam pembentukan jiwa kewarganegaraan generasi muda perlu melibatkan komitmen kuat dari semua pihak terkait, dengan tujuan memastikan bahwa nilai-nilai Pancasila tetap relevan dan menjadi landasan moral dan etika yang kuat dalam membangun bangsa yang berkeadilan, demokratis, dan berbudaya. Kata kunci: Implementasi ideologi Pancasila, Jiwa kewarganegaraan muda,Pendidikan kewarganegaraan.AbstractThis journal This abstract discusses the influence of Pancasila ideology implementationin shaping the civic consciousness of the younger generation in Indonesia. The studyaims to investigate the role of education, the influence of Pancasila values, challengesand barriers, as well as recommendations and strategies to enhance the implementation of Pancasila ideology. The research methodology employed includes literature review and qualitative analysis of relevant sources. The findings indicate that education plays a crucial role in shaping the civic consciousness of the younger generation, with civic education that strengthens the understanding and practice of Pancasila values being a vital factor in this process. Pancasila values have a significant influence on the attitudes and behaviors of the younger generation, reflected in their inclusive, tolerant, and responsible attitudes as good citizens. However, the implementation of Pancasila ideology also faces various challenges and barriers, such as the lack of public understanding, differing interpretations, the impact of globalization, and political polarization. Therefore, recommendations and strategies are necessary to strengthen the implementation of Pancasila ideology, including enhancing civic education, intensive public campaigns, collaboration among stakeholders, and utilizing mass media and information technology. The implementation of Pancasila ideology in shaping the civic consciousness of the younger generation requires strong commitment from all relevant parties, with the aim of ensuring that Pancasila values remain relevant and serve as a strong moral and ethical foundation in building a just, democratic, and cultured nation. Keywords: Implementastion of Pancasila ideology, Civic Consciousness of the youngergeneration, Civic education.
HALF-MAFUNET: A Lightweight Architecture Based on Multi-Scale Adaptive Fusion for Medical Image Segmentation Maula Sandy, Abiaz Fazel; Prasetyo, Heri
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.v8i1.1357

Abstract

Medical image segmentation is a critical component in computer-aided diagnosis systems but many deep learning models still require large numbers of parameters and heavy computation. Classical CNN-based architectures such as U-Net and its variants achieve good accuracy, but are often too heavy for real deployment. Meanwhile, modern Transformer-based or Mamba-based models capture long-range information but typically increase model complexity. Because of these limitations, there is still a need for a lightweight segmentation model that can provide a good balance between accuracy and efficiency across different types of medical images. This paper proposes Half-MAFUNet, a lightweight architecture based on multi-scale adaptive fusion and designed as a simplified version of MAFUNet. The main contribution of this work is combining the efficient encoder structure of Half-UNet with advanced fusion and attention mechanisms. Half-MAFUNet integrates Hierarchy Aware Mamba (HAM) for global feature modelling, Multi-Scale Adaptive Fusion (MAF) to combine global and local information, and two attention modules, Adaptive Channel Attention (ACA) and Adaptive Spatial Attention (ASA), to refine skip connections. In addition, this model incorporates Channel Atrous Spatial Pyramid Pooling (CASPP) to capture multi-scale receptive fields efficiently without increasing computational cost. Together, these components create a compact architecture that maintains strong representational power. The model is trained and evaluated on three public datasets: CVC-ClinicDB for colorectal polyp segmentation, BUSI for breast tumor segmentation, and ISIC-2018 for skin lesion segmentation. All images are resized to 256×256 pixels and processed using geometric and intensity-based augmentations. Half-MAFUNet achieves competitive performance, obtaining mean IoU around 84 85% and Dice/F1-Score around 90 92% across datasets, while using significantly fewer parameters and GFLOPs compared to U-Net, Att-UNet, UNeXt, MALUNet, LightM-UNet, VM-UNet, and UD-Mamba. These results show that Half-MAFUNet provides accurate and efficient medical image segmentation, making it suitable for real-world deployment on devices with limited computational resources.