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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) ASEAN Journal of Halal Study
Annisaa Nurul Ramadhani Novelika
Universitas Indonesia
Computer Science & IT Engineering

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Burned Area Segmentation Using Random Band Selection and Ensemble Encoder Annisaa Nurul Ramadhani Novelika; Laksmita Rahadianti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): June 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7370

Abstract

Wildfires are increasingly recognized as major environmental hazards that endanger ecosystems, human health, and economic stability. In practice, various monitoring efforts, such as hotspot detection, burned-area indices, and field inspections still depend on reliable spatial information to quantify fire impacts over large regions. Accurate segmentation of burned areas from satellite imagery plays a vital role in supporting post-disaster response and sustainable land management. This paper proposes a novel framework for burned area segmentation using multispectral imagery sampled by Random Subspace Band Selection (RSBS) with a U-Net architecture with an ensemble encoder. The RSBS module generates multiple 3-band subsets from Landsat-8 data, incorporating spectrally informative bands such as Near-Infrared (NIR) or Shortwave Infrared (SWIR). These subsets are used to train U-Net models with an ensemble of encoder backbones ResNet34, ResNet50, DenseNet121, MobileNetV2 and InceptionV4 for spectral and architectural diversity. The final predictions are aggregated using majority voting to enhance robustness and generalization. The framework is evaluated on a publicly available Indonesian burned area dataset encompassing diverse land cover types. Experimental results demonstrate that the proposed ensemble model achieves up to 0.7673 IoU, 0.8734 mIoU, and 0.8683 F1 Score, outperforming the best single-backbone model. These findings confirm that the proposed framework offers a scalable, accurate, and adaptable solution for wildfire damage assessment using satellite data.
Optimizing the Halal Food Industry Cluster as a Pillar of the Indonesian Economy Lutfiyah Rahma Novelika; Annisaa Nurul Ramadhani Novelika
ASEAN Journal of Halal Study Vol. 3 No. 1 (2026): Jurnal AJHS: Juni 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/ajhs.v3i1.42265

Abstract

Indonesia has substantial potential to become a global hub for the halal food industry due to its large Muslim population and increasing demand for halal products in both domestic and international markets. However, the potential of halal food industry clusters, particularly among micro, small, and medium enterprises (MSMEs), has not yet been fully optimized. This study aims to examine strategies for optimizing halal food industry clusters as a pillar of the Indonesian economy. A qualitative approach was employed using primary and secondary data collected through literature reviews and relevant online sources. The data were analyzed descriptively to identify key factors supporting halal industry development. The findings indicate that strengthening halal certification systems, expanding halal industrial zones, increasing halal literacy among MSMEs, enhancing government policy coordination, promoting domestic halal products, and developing international business networks are essential strategies for improving the competitiveness of halal food clusters. Community participation and collaboration among government institutions, industry actors, and consumers also play a crucial role in supporting sustainable halal industry development. The study concludes that an integrated cluster-based approach can strengthen MSME competitiveness, expand market access, and support Indonesia’s ambition to become a leading global halal industry hub while promoting long-term economic sustainability.
Co-Authors Lutfiyah Rahma Novelika Rahadianti, Laksmita