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All Journal UPGRADE: Jurnal Pendidikan Teknologi Informasi The Journal of Religion and Communication Studies
Apriliani, Cahya
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Religion Humanities Computer Science & IT Education Social Sciences Other

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Social media as a new space for communication and Muslim identity formation Ikasatya, Ririn Anugerah; Apriliani, Cahya
The Journal of Religion and Communication Studies Vol. 3 No. 1: (February) 2026
Publisher : Institute for Advanced Science, Social, and Sustainable Future

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61511/jorcs.v3i1.2026.2696

Abstract

Background: This study discusses the role of social media, particularly Instagram and TikTok, as a space for the formation of Islamic identity among Indonesian Muslim youth amid a highly visual and competitive digital culture. The transformation of religious communication in the digital space marks the emergence of the phenomenon of digital religiosity, where piety is displayed through symbols, visual narratives, and online participation. Methods: A quantitative descriptive approach supported by qualitative analysis was used on 50 Muslim youth respondents who are active social media users. Data were collected through an online survey using a five-point Likert scale and analyzed using descriptive statistics and content analysis of open-ended responses. Findings: The results show that social media plays a significant role in shaping Muslim identity, especially among women aged 20–22 years. Islamic content on social media was found to increase understanding of Islamic values, motivation to worship, and reflective expressions of religiosity. However, the study also found ethical challenges such as digital riya' and algorithmic religiosity, where religious practices can shift to become performative due to the logic of popularity and platform algorithms. Conclusion: Social media functions as a laboratory for religious identity for Muslim youth, mediating between spiritual expression and popular culture while demanding strong religious digital literacy. Novelty/Originality of this article: This study offers a new perspective through the integration of social identity and digital communication theories in the study of Islamic communication, as well as introducing the concept of digital Islamic identity as a form of reflective piety in the online space.
Augmentasi Data Berbasis GAN dan Ekstraksi Fitur EfficientNetB0 dengan XGBoost untuk Meningkatkan Klasifikasi Penyakit Daun Jagung Anugerah Ikasatya, Ririn; Ikasatya, Ririn Anugerah; Apriliani, Cahya; Firdaus, Fathir Jannatul; Pratama, Gede Yogi
Upgrade : Jurnal Pendidikan Teknologi Informasi Vol 3 No 2 (2026): FEBRUARI
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/upgrade.v3i2.6224

Abstract

Corn leaf diseases are one of the main factors contributing to decreased corn productivity. Manual identification of leaf diseases remains subjective, time-consuming, and highly dependent on individual experience. This study aims to improve the performance of image-based corn leaf disease classification through the integration of data balancing techniques, deep feature extraction, and machine learning-based classification methods. The dataset consists of four classes with an imbalanced distribution, namely  Blight with 802 images, Common Rust with 914 images, Gray Leaf Spot with 401 images, and Healthy with 813 images, where GrayLeaf Spot represents the minority class. Data balancing is performed by generating synthetic images using  a convolution-based generative model to increase the number of samples in the minority class. Furthermore, feature extraction is carried out using the EfficientNetB0 architecture, and classification is performed using a gradient boosting-based algorithm. There sults show that the proposed approach improves accuracy from 92.49 percent to 93.29 percent and enhances the model’s ability to recognize the minority class, as indicated by an increase in recall from 69 percent to 78 percent and an improvement in performance balance from 0.76to 0.84. These findings indicate that the proposed method is effective in improving classification performance, particularly for the minority class, without reducing performance on majority classes.
Co-Authors Anugerah Ikasatya, Ririn Firdaus, Fathir Jannatul Ikasatya, Ririn Anugerah Pratama, Gede Yogi