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Exploring the Art Potential of Elementary Teachers: Sponge Painting Workshop: Menggali Potensi Seni Guru SD: Workshop Melukis Pemandangan dengan Media Spons Tangsi; Siti Asmaulul Izmi; Dwi Wahyuni Hamka; Jusbaeni; Sri Riski Wulandari
Jurnal Sipakatau: Inovasi Pengabdian Masyarakat Volume 2 Issue 1 December 2024: Jurnal Sipakatau
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/jsipakatau.v1i6.2454

Abstract

This community service focuses on improving the competence of Pao-Pao State Elementary School teachers in implementing sponge media as an art teaching aid. Through focused training, teachers were intensively trained to master sponge painting techniques and understand the significance of art in the learning process. The evaluation results showed a significant improvement in teachers' ability to create innovative and interesting artworks. Thus, it is expected to stimulate students' creativity and make art learning more fun and interactive. The importance of continuous training in developing the quality of art education at the primary school level is also emphasised in this study. The training not only provides direct benefits for the teachers, but also has a positive impact on the students' learning process and ultimately, on improving the overall quality of education. Abstrak Pengabdian masyarakat ini fokus pada peningkatan kompetensi guru Sekolah Dasar Negeri Pao-Pao dalam mengimplementasikan media spons sebagai alat bantu mengajar seni lukis. Melalui pelatihan yang terarah, para guru dilatih secara intensif untuk menguasai teknik-teknik melukis menggunakan spons serta memahami signifikansi seni dalam proses pembelajaran. Hasil evaluasi menunjukkan adanya peningkatan yang signifikan dalam kemampuan guru dalam menciptakan karya seni yang inovatif dan menarik. Dengan demikian, diharapkan dapat merangsang kreativitas siswa dan membuat pembelajaran seni menjadi lebih menyenangkan dan interaktif. Pentingnya pelatihan berkelanjutan dalam pengembangan kualitas pendidikan seni di tingkat sekolah dasar juga ditekankan dalam penelitian ini. Pelatihan ini tidak hanya memberikan manfaat langsung bagi para guru, tetapi juga berdampak positif pada proses pembelajaran siswa dan pada akhirnya, pada peningkatan kualitas pendidikan secara keseluruhan.
Attention-Enhanced Convolutional Networks for Fine-Grained Batik Motif Classification with Statistical Feature Modeling Abdal, Nurul Mukhlisah; Tangsi
Journal of Mathematics and Applied Statistics Vol. 3 No. 1 (2025): June 2025
Publisher : Yayasan Insan Literasi Cendekia (INLIC) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35914/mathstat.v3i1.309

Abstract

This study examines a hybrid method for classifying fine-grained Indonesian batik motifs under limited data conditions. The research focuses on two objectives: (1) assessing the contribution of attention mechanisms to the extraction of discriminative visual features, and (2) evaluating the role of Gray-Level Co-occurrence Matrix (GLCM) texture descriptors when combined with deep convolutional representations. The proposed approach employs a ResNet-50 backbone equipped with a Convolutional Block Attention Module (CBAM) and integrates second-order GLCM features through a feature-fusion framework. The dataset consists of authentic batik photographs representing 38 motif categories. Model performance is assessed using accuracy, macro-averaged metrics, Cohen’s Kappa, and ablation experiments supported by statistical tests. The model reaches a test accuracy of 75.90%, with a macro F1-score of 0.7598 and a Cohen’s Kappa value of 0.7456. Training and validation curves show stable behavior after the initial epochs. Per-class evaluation indicates that motifs with distinctive structural elements tend to be classified correctly, whereas motifs with subtle or overlapping patterns exhibit lower accuracy. The ablation study records a 4.79% accuracy increase attributed to CBAM and a 3.51% increase associated with GLCM features; both effects fall within statistically significant confidence intervals. The combination of both components yields an 8.38% improvement over the baseline model. Two-way ANOVA identifies main effects for attention and GLCM, with a small interaction term. These results provide information on how spatial attention and statistical texture features contribute to the classification of fine-grained batik motifs within the examined setting.