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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Pendidikan Matematika (JUDIKA EDUCATION) JURNAL PENDIDIKAN TAMBUSAI COLLASE (Creative of Learning Students Elementary Education) Neraca Jurnal Ilmu Hukum, Humaniora dan Politik (JIHHP) Journal of Artificial Intelligence and Digital Business Jurnal Manajemen Dan Akuntansi Medan Sahmiyya: Jurnal Ekonomi dan Bisnis Jurnal Interaksi Sosiologi Riwayat: Educational Journal of History and Humanities JRIIN :Jurnal Riset Informatika dan Inovasi Jurnal Akselerasi Merdeka Belajar dalam Pengabdian Orientasi Masyarakat (Jurnal AMPOEN) Satmata: Journal or Historical Education Studies JER Journal of Fisheries & Marine Al-HIbru: Jurnal Ilmu Bahasa Arab dan Pembelajarannya Akhlak: Jurnal Pendidikan Agama Islam Dan Filsafat Journal of International Accounting, Taxation and Information Systems Parabela: Jurnal Ilmu Pemerintahan & Politik Lokal
Machruf, Awalludin
Management Study Program, Faculty Of Business Economics And Digital Technology, Nahdlatul Ulama University Surabaya
Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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The Role of Social Media Marketing Activity in Influencing User Engagement and Brand Loyalty: Brand Ownership through Parasocial Relationships Awalludin, Anjas; Kurniawati
Jurnal Economic Resource Vol. 8 No. 1 (2025): March-August
Publisher : Fakultas Ekonomi & Bisnis Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57178/jer.v8i1.1337

Abstract

The purpose of this study was to identify parasocial activity and social media marketing activities, user engagement, and brand loyalty, with a primary focus on understanding the extent to which parasocial activity and user engagement affect social media marketing activities and brand loyalty in a given context. The research method involves collecting data through a six-month online survey, participating respondents who are users of the product or service to be studied. Regression analysis was used to measure the relationship between variables such as Parasocial Relationship, Social Media Marketing Activity, User Engagement, and Brand Loyalty, at a significance level of 0.05. The results of the analysis showed that there was a positive and significant relationship between parasocial activities and social media marketing activities, and user engagement was positively and significantly related to parasocial activities. However, no significant relationship was found between parasocial activity or user engagement and brand loyalty, suggesting that other factors may also influence the development of brand loyalty. This research provides useful insights for marketing strategies and brand interactions with consumers in the age of social media, emphasizing the importance of understanding how parasocial activity and user engagement can affect certain aspects of brand and consumer relationships.
A Comprehensive Review of Deep Learning Approaches in Fish Classification Using Convolutional Neural Networks From 2015 to October 2025 Nur Muhammad Afiq Anang; Awalludin, Ezmahamrul Afreen
Jurnal Ilmiah Perikanan dan Kelautan 2026: JIPK VOLUME 18 ISSUE 2 YEAR 2026 (JUNE 2026, ISSUE IN PROGRESS)
Publisher : Faculty of Fisheries and Marine Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jipk.v18i2.79656

Abstract

Graphical Abstract Highlight Research 1. Provide insights into the development, methodologies and significant advancements in fish classification research utilizing CNNs. 2. The review discusses the progression of CNN architectures, beginning with earlier models such as AlexNet and advancing to more sophisticated frameworks like ResNet and GoogLeNet. 3. Examines the extensive use of benchmark datasets across many studies and discusses collaborative research efforts that refine models and enhance reproducibility. 4. Guide future research by underscoring best practices, acknowledging less explored areas and encouraging interdisciplinary approaches to monitoring fish biodiversity and managing aquatic ecosystems through deep learning.   Abstract Recent advancements in deep learning have substantially improved the classification of fish species. These innovations present a contemporary and dependable alternative to conventional methodologies, such as image processing and manual identification. Implementing Convolutional Neural Networks (CNNs) has significantly enhanced accuracy, flexibility and scalability within aquatic ecosystems. This comprehensive review evaluates 81 scholarly articles published from January 2015 to October 2025. The analyses were guided by the VICO framework, supported by defined inclusion and exclusion criteria, data extraction and synthesis and the PRISMA process to ensure systematic selection of relevant studies. It aims to provide insights into the development, methodologies, and significant advancements in fish classification research utilizing CNNs. The review discusses the progression of CNN architectures, beginning with earlier models such as AlexNet and advancing to more sophisticated frameworks like ResNet and GoogLeNet, as well as transformer and hybrid CNN model such as the Vision Transformer (ViT) and the Convolutional Vision Transformer (ConViT). It highlights the adoption rates, training performance and contexts of use. Additionally, it examines the extensive use of benchmark datasets across many studies and discusses collaborative research efforts that refine models and enhance reproducibility. A thorough comparison of classification accuracy, dataset composition and trends in model choice offers a clearer picture of the current impact of deep learning in this area. Furthermore, this review identifies crucial challenges, including the lack of data for rare species, issues related to low-resolution image recognition and the need for standardization in model evaluation. The insights offered aim to guide future research by underscoring best practices, acknowledging less explored areas and encouraging interdisciplinary approaches to monitoring fish biodiversity and managing aquatic ecosystems through deep learning.
The Influence of Work Motivation and Workload on Employee Performance: Literature Review Exabiaggi, Rizal Dhani; Awalludin, Muhammad As’ad; Ramdani, Alif Dimas; Hasin, Farid Bima; Putra, Riyan Sisiawan
Journal of International Accounting, Taxation and Information Systems Vol. 1 No. 2 (2024): May
Publisher : CV. Proaksara Global Transeduka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70865/jiatis.v1i2.50

Abstract

In a company, employees are one of the most important elements in achieving company goals. An employee's performance is certainly influenced by several factors that a manager needs to know. Managers must know the strengths and weaknesses of each manager in order to maximize potential and minimize employee deficiencies. Motivation is one of the things that influences human behavior. Motivation is also called a driver, desire, supporter or need, a need that can make someone enthusiastic and motivated to reduce. This research aims to find out whether there is an influence of motivation and workload on employee performance.
Co-Authors Abdiyanto Abdiyanto Abidatun Mu’awanah, Nurul adisti, tria Ahmad Maftuh Sujana Akbar, Fatih Hidayat Alfian, fiqri Alya Citra Salsabila Amanda, Suci Anang, Nur Muhammad Afiq Asdar Maknung, Muh. Awalludin, Subhan Ajiz Bagja Maulana Burhannurdin Nabih Kurniawan Chaiyun Nafiah, Ilmi Darwis, Muhajir Eka Pratama, Ahmad Yudha Elsya Wahyuni Exabiaggi, Rizal Dhani Farida Rohmah Fatimah Az Zahra Harianja, Callysta Marcella Hasin, Farid Bima Hayu Maharani, Dama Gandes Helman Manay, Helman Hilmi Al Hazmi Hidaya Janah, Nuryatul khairunisa, Nuke Ferli Khairunisa Kurniawati Maulidya, Raisya Ayu Mitro Subroto Muhammad Rifal Nurfalah Mulyanty, Dety Munandar, Eris Nur Muhammad Afiq Anang Nurhidayat, Rifky Nurmalya Kardina, Rizki Padilillah, Rahma Ramdani, Alif Dimas Riyan Sisiawan Putra Rusmana, Apit Sabrina, Laila Sadali, Ayatullah Saidah, Wirdati Santika, Ganjar Sari, Eka Anisa SITI MARYAM Soetji Lestari Sri Wahyuni Suci Sulistiawati Sucitra Dinika Akbar Sutrisno Mohamad Tamamudin Tria Adisti Ariyani, Amalia Rahmawati Verry Ferdian Putra Widia Ningsih, Widia Wijayanti, Lono