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All Journal Medicinus : Jurnal Kedokteran International Journal of Entrepreneurship & Technopreneur (INJETECH) Jurnal Wicara Desa
Sofiana, Dina
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Agriculture, Biological Sciences & Forestry Humanities Economics, Econometrics & Finance Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health Social Sciences Other

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The Role of Technology Integration in ASEAN Young Entrepreneurs Collaboration: Opportunities and Challenges in the Ecosystem Sofiana, Dina; Soegoto, Dedi Sulistiyo; Yunanto , Rio
International Journal of Entrepreneurship & Technopreneur (INJETECH) Vol. 5 No. 1 (2025): INJETECH, June 2025
Publisher : Universitas Komputer Indonesia

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Abstract

The development of digital technology has changed the business landscape in ASEAN, enabling young entrepreneurs to collaborate across countries. This study analyzes the role of technology integration in driving business collaboration and opportunities and challenges in the digital ecosystem. A qualitative approach based on literature studies and case analysis is used to explore the role of digital platforms such as startup hubs, fintech, and marketplaces in expanding market access and innovation. The results show that technology integration supports the growth of young entrepreneurs' businesses through platforms such as Gojek, Tokopedia, and AirAsia Super App. There are still challenges, such as digital infrastructure gaps, regulatory differences, and cultural factors, which are still obstacles to cross-country collaboration. This study recommends harmonizing ASEAN digital policies, improving technology infrastructure, and developing digital-based education and mentoring programs to strengthen the young entrepreneurial ecosystem in ASEAN.
PEMBUATAN POJOK BACA SEBAGAI UPAYA PENGUATAN BUDAYA LITERASI SISWA DI SDN KULEM, DESA PENGONAK, PRAYA TIMUR Jurnal Wicara; Hakimi, Muhammad; Sukmarani, Ni; Prabawati, Putu; Dharma, I; Wulandari, Alfira; Sofiana, Dina; Febina, Putri; Kanti, Putri; Abdianzah, Muhammad; Afuw, Afiifah
Jurnal Wicara Vol 3 No 6 (2025): Jurnal Wicara Desa
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/bwge1r28

Abstract

The Community Service Program (KKN) is one form of student service to the community, aiming to make a tangible contribution to improving the quality of education. The KKN activity carried out at SDN Kulem, Pengonak Village, East Praya District, was focused on implementing a reading corner as an effort to strengthen students' literacy culture. The main objectives of this activity are to cultivate reading interest and familiarize students with the reading materials available at school. The problem of low reading interest among students necessitates innovative learning spaces that are engaging, easily accessible, and tailored to children's needs. The method used is the creation of a reading corner in the classroom, utilizing the school's existing facilities and reading collection. The results of the implementation show a positive response from the students, indicated by their increased enthusiasm in utilizing the reading corner as a means of reading outside of class hours. The implementation of reading corners has proven effective as a strategic effort in building a school ecosystem that supports literacy, while also being a concrete step in fostering a reading culture from an early age.
Applications of Artificial Intelligence in Peripheral Neuropathy: A Systematic Review Sutha, Anak Agung Ngurah Agung Bayu; Sharon; Rahman, Dea Nabila; Amanah, Salma Rizqi; Wicaksono, Teguh Budi; Sofiana, Dina; Hermawan, Galih Muchlis
Medicinus Vol. 13 No. 1 (2023): October
Publisher : Fakultas Kedokteran Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/med.v13i1.10778

Abstract

Background: Peripheral neuropathy (PN) is a common complication of metabolic and systemic diseases, particularly diabetes mellitus, resulting in sensory loss, pain, and motor impairment. Conventional diagnostic tools often detect PN only after irreversible nerve injury. Artificial intelligence (AI), especially machine learning (ML), has emerged as a promising tool for early diagnosis and risk prediction by integrating clinical, imaging, and genetic data. Methods: Following PRISMA 2020 guidelines, PubMed, EMBASE, IEEE Xplore, and Scopus were systematically searched up to September 2025. Studies applying ML or deep learning algorithms to PN were included, while reviews, grey literature, and studies lacking methodological details or performance metrics were excluded. Result: Our study included participants with diabetic, chemotherapy-induced, or pain-related neuropathies. Deep learning models, such as multilayer perceptrons and neural networks, achieved diagnostic accuracies of 87–93%, while classical algorithms including random forest, XGBoost, and SVM reported AUCs of 0.80–0.93. Radiomics-based SVMs using ultrasound showed external validation AUCs of 0.70–0.90. Key predictors included HbA1c, diabetes duration, lipid profile, and BMI. Conclusions: Machine learning demonstrates strong potential for improving the prediction, diagnosis, and phenotypic classification of PN. However, heterogeneity in datasets and limited external validation restrict clinical translation. Future work should focus on standardized data, multicenter validation, and interpretable AI models to facilitate integration into clinical practice.
Co-Authors Abdianzah, Muhammad Afuw, Afiifah Amanah, Salma Rizqi Dharma, I Febina, Putri Hermawan, Galih Muchlis Jurnal Wicara Kanti, Putri Muhammad Hakimi Prabawati, Putu Rahman, Dea Nabila Sharon Soegoto, Dedi Sulistiyo Sukmarani, Ni Sutha, Anak Agung Ngurah Agung Bayu Teguh Budi Wicaksono Wulandari, Alfira Yunanto , Rio