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Social Entrepreneurship in Islamic Perspective Role of Islamic Values, Environmental Values and Social Enterprise Attitudes Kurjono, Kurjono; Juliana, Juliana; Kamil, Anton Abdulbasah; Mardiani, Rika; Setiawan, Yana; Samlawi, Faqih
Islamic Research Vol 8 No 1 (2025): Islamic Research
Publisher : Perhimpunan Intelektual Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47076/jkpis.v8i1.332

The purpose of this research is to analyze the influence of Islamic values, environmental values, and social entrepreneurial attitudes on the social entrepreneurial intentions of Indonesian students. The research population consists of all UPI students from various faculties. Meanwhile, for the sample size of the research, 160 UPI students who have taken entrepreneurship courses were selected. Data collection was conducted using a questionnaire distributed via a Google Form link. The research results show that Islamic values and environmental values have a positive and significant impact on social entrepreneurship intentions. Islamic values have a positive and significant impact on social entrepreneurship, and environmental values also have a positive and significant impact. Similarly, social entrepreneurship attitudes have a positive and significant impact on social entrepreneurship intentions. Social entrepreneurship attitudes mediate the influence of Islamic values on social entrepreneurship intentions and mediate the influence of environmental values on social entrepreneurship intentions. Thus, social entrepreneurship attitudes partially mediate both variables, namely Islamic values and environmental values. Based on these findings, it is necessary to revitalize the entrepreneurship education curriculum by incorporating aspects of social entrepreneurial attitudes into entrepreneurship courses at universities. Maintaining guidance for students on environmental values and enhancing social entrepreneurship attitudes through socially-based business activities.

Social Entrepreneurship in Islamic Perspective Role of Islamic Values, Environmental Values and Social Enterprise Attitudes Kurjono, Kurjono; Juliana, Juliana; Kamil, Anton Abdulbasah; Mardiani, Rika; Setiawan, Yana; Samlawi, Faqih
Islamic Research Vol 8 No 1 (2025): Islamic Research
Publisher : Perhimpunan Intelektual Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47076/jkpis.v8i1.332

The purpose of this research is to analyze the influence of Islamic values, environmental values, and social entrepreneurial attitudes on the social entrepreneurial intentions of Indonesian students. The research population consists of all UPI students from various faculties. Meanwhile, for the sample size of the research, 160 UPI students who have taken entrepreneurship courses were selected. Data collection was conducted using a questionnaire distributed via a Google Form link. The research results show that Islamic values and environmental values have a positive and significant impact on social entrepreneurship intentions. Islamic values have a positive and significant impact on social entrepreneurship, and environmental values also have a positive and significant impact. Similarly, social entrepreneurship attitudes have a positive and significant impact on social entrepreneurship intentions. Social entrepreneurship attitudes mediate the influence of Islamic values on social entrepreneurship intentions and mediate the influence of environmental values on social entrepreneurship intentions. Thus, social entrepreneurship attitudes partially mediate both variables, namely Islamic values and environmental values. Based on these findings, it is necessary to revitalize the entrepreneurship education curriculum by incorporating aspects of social entrepreneurial attitudes into entrepreneurship courses at universities. Maintaining guidance for students on environmental values and enhancing social entrepreneurship attitudes through socially-based business activities.

Economy and banking sector performance: Spillover effect of Uncertainty of Covid-19 on Non-performing loans of Turkish Agricultural sector Olorogun, Lukman Ayinde; Kamil, Anton Abdulbasah
Data Science: Journal of Computing and Applied Informatics Vol. 9 No. 1 (2025): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v9.i1-19905

This spillover index research paper tries to find connectedness between Non-performing loans (NPL) and Covid-19 global pandemic specifically in the Turkish agricultural sector. The research covers variables of NPL, Geopolitical risk index (GPR), Fishing, Agriculture, Non-performing loans to total assets (NPL_TCL), Return on assets (ROA), Return on equity (ROE). The data for this research includes a monthly time series dataset covering between Dec. 2004–April 2020. To perform the statistical analysis descriptive statistics, correlation matrix with its T-statistics and probabilities, and Dielbold and Yilmaz index were adopted to uncover the level of connectedness among the group. The descriptive statistics results of the group reveal that all variables understudy were contributing factors to the increase of NPL of the banking sector in general. Specifically, the agricultural sector’s NPL has a significant effect on the banking sector’s aggregate NPLs. The correlation analysis indicated that there is a higher correlation between NPL and agriculture, Fishing, Timber, and a moderate average correlation between NPL and Hunting. Similarly, a moderate high correlation amongst individual agricultural sectors i.e. Hunting, Fishing, Agriculture, Timber and as well as higher correlation between ROA and ROE that are under consideration. This shows that there is somehow acceptable interconnectedness among the group. The results of the spillover index effects through Dielbold and Yilmaz procedure revealed a total spillover effect 57.3%. Whereas, another unexplained effect in this study is 43.7% which might be as a result random noise in the dataset due to impact of Covid-19 pandemic. This research is significant as it is first of its kind on a proof of spillover from the empirical viewpoints as it related to Turkey on level of spillover and its impacts on the NPLs of the banking sector measuring the agricultural sector’s contribution.

A CRITICAL EXAMINATION OF THE NEOCLASSICAL ECONOMIC PARADIGM AND ITS EXPLANATORY POWER ON GLOBAL INCOME INEQUALITY Anton Abdulbasah Kamil; Dede Hertina
Count : Journal of Accounting, Business and Management Vol. 2 No. 2 (2024): October: COUNT: Journal of Accounting, Business and Management
Publisher : CV. Fahr Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61677/count.v2i2.547

This study critically examines the theoretical limitations of the neoclassical economic paradigm in explaining global income inequality, particularly in the context of a post-pandemic, digitized, and ecologically unstable world. The research aims to deconstruct core neoclassical assumptions—such as marginal productivity theory, rational individualism, and market neutrality—and assess their relevance to contemporary inequality dynamics. Employing a qualitative method through a structured literature review of 50 high-impact academic and institutional sources, this study uses thematic content analysis to synthesize interdisciplinary critiques from political economy, ecological economics, and post-colonial theory. The findings reveal that neoclassical models fail to account for structural drivers of inequality, such as historical legacies, institutional asymmetries, digital labor dynamics, and capital accumulation beyond productivity. While neoclassical economics remains influential in shaping global development agendas, its ideological persistence often legitimizes unequal outcomes rather than resolving them. The novelty of this research lies in its conceptual framework, which integrates fragmented critiques into a cohesive theoretical challenge to economic orthodoxy and links inequality to global issues like platform labor, climate migration, and fiscal erosion. As global inequality deepens despite overall economic growth, this study highlights the urgent need to shift towards more pluralistic and inclusive economic thinking. In conclusion, rethinking foundational economic theory is critical to formulating policies that promote equity, sustainability, and justice on a global scale.

Application of EfficientNet Transfer Learning with Incremental Fine-Tuning for Road Damage Detection Riki Winanjaya; Abdi Rahim Damanik; Anton Abdulbasah Kamil
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v9i1.50124

Image-based road damage detection is an essential component of intelligent infrastructure monitoring systems. However, conventional transfer learning often fails to adapt pre-trained models to domain-specific characteristics such as fine-crack textures, illumination variations, and perspective distortions. This study proposes an EfficientNet-based road damage classification model that leverages incremental fine-tuning and multi-stage data augmentation to enhance feature adaptation and model robustness. The experiments were conducted using the Road Damage Detection dataset from Kaggle, comprising 1,400 labeled images across several road damage classes. The dataset was partitioned into 80:10:10 splits for training, validation, and testing, with stratification. The proposed approach gradually unfreezes EfficientNet layers through a structured incremental fine-tuning schedule while applying staged augmentation to expand data diversity. Experimental results show that the baseline EfficientNet transfer learning model achieved 78.26% accuracy, whereas the proposed model improved performance to 97.10% accuracy, with 97.60% macro precision, 97.20% macro recall, and 97.30% macro F1-score. The results demonstrate that incremental fine-tuning effectively enhances feature adaptation to road damage textures, while multi-stage augmentation improves model robustness. These findings indicate that the proposed approach provides an effective strategy for improving deep-learning-based road damage detection systems in real-world infrastructure monitoring applications.

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