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All Journal SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan
Fitri Yani, Mega
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Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management

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Data Mining: Clustering and Correlation Analysis of Marine Potential: Insights from Capture Fisheries, Coral Reef Quantity, and Plankton Abundance Muhdiantini, Cindy; Fitri Yani, Mega; Auliya Rahman, Ilham; Maryati, Ati
SITEKNIK: Information Systems, Engineering and Applied Technology Vol. 2 No. 1 (2025): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14699240

Abstract

Indonesia, sebagai negara kepulauan dengan wilayah laut yang luas, memiliki potensi besar dalam memanfaatkan sumber daya laut, seperti terumbu karang, mangrove, budidaya, dan penangkapan ikan laut. Pemanfaatan yang berkelanjutan tidak hanya berdampak positif pada ekosistem laut tetapi juga meningkatkan kesejahteraan masyarakat. Untuk mendukung pengelolaan berkelanjutan, diperlukan analisis data mendalam guna mengidentifikasi pola dan hubungan yang relevan. Data mining menjadi alat efektif untuk menggali pola yang tersembunyi, terutama melalui teknik clustering. Analisis clustering dilakukan terhadap data perikanan tangkap, kuantitas terumbu karang, dan kelimpahan plankton guna menemukan kelompok homogen dalam dataset. Proses ini diawali dengan pemilihan data sesuai kriteria, dilanjutkan dengan preprocessing untuk menyaring data redundan. Hasilnya, terdapat tiga cluster utama: cluster 0 berfokus pada terumbu karang, cluster 1 pada jumlah ikan tangkap, dan cluster 2 pada kelimpahan plankton.
Trends and Innovations in CRM for Patient Management: A Literature Review Muhdiantini, Cindy; Fitri Yani, Mega; Ibnu Zulkarnain
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 2 No. 2 (2025): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15180642

Abstract

Customer Relationship Management (CRM) in healthcare services has evolved rapidly with advancements in information technology. CRM not only functions as a patient relationship management tool but also as a solution to enhance data-driven care, service personalization, and operational efficiency. Current trends in CRM involve the utilization of Artificial Intelligence (AI) and Machine Learning (ML), integration with wearable devices for real-time health monitoring, the use of Big Data for analyzing population health trends, as well as the adoption of telemedicine and mobile health applications connected to CRM. This study aims to review the latest developments in CRM for patient management and its impact on healthcare systems.
Co-Authors Auliya Rahman, Ilham Ibnu Zulkarnain Maryati, Ati Muhdiantini, Cindy