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All Journal Elkom: Jurnal Elektronika dan Komputer Jurnal Transformatika AGRICOLA KREDO : Jurnal Ilmiah Bahasa dan Sastra Jurnal Agro Industri Perkebunan Jurnal Kreativitas PKM Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Jurnal Agrotropika MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknologi Informasi dan Komunikasi Teknik: Jurnal Ilmu Teknik dan Informatika ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal Of World Science Journal of Engineering, Electrical and Informatics (JEEI) Sehat Rakyat: Jurnal Kesehatan Masyarakat INFORMATIKA Sajak: Jurnal Penelitian dan Pengabdian Sastra, Bahasa, dan Pendidikan Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Publikasi Ilmu Komputer dan Multimedia Jurnal Teknik Informatika dan Teknologi Informasi Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Journal of Technology Informatics and Engineering Majority Science Journal Jurnal Padamu Negeri Ignite: Journal Islamic Global Network for Information Technology and Entrepreneurship EDUKASI : Jurnal Penelitian dan Artikel Pendidikan
Priyadi Priyadi
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Journal : Journal of Technology Informatics and Engineering

 1 
The Efficient Approach in Peer-to-Peer Systems to Achieve High Efficiency Lukman Santoso; Marcus Gunadi Wibawa; Muhamad Syarifudin; Priyadi Priyadi; Titi Christiana
Journal of Technology Informatics and Engineering Vol 1 No 2 (2022): August: Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i2.137

Abstract

Peer-to-peer systems nowadays are widely used because of the scalability and high reliability. File replication and consistency maintenance are widely used techniques to achieve high system performance. These techniques are connected to each other. The connection of these techniques is consistency maintenance is needed in file replication to keep the consistency between a file and the replicas. Traditional file replication and consistency maintenance methods need a high cost. The usage of IRM (Integrated file Replication and Consistency Maintenance inP2P systems) which will achieve high efficiency at a significantly lower cost can be used to solve this problem. IRM reduces redundant file replicas, consistency maintenance overhead, and unnecessary file updates.
The Efficient Approach in Peer-to-Peer Systems to Achieve High Efficiency Lukman Santoso; Marcus Gunadi Wibawa; Muhamad Syarifudin; Priyadi Priyadi; Titi Christiana
Journal of Technology Informatics and Engineering Vol. 1 No. 2 (2022): August: Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i2.137

Abstract

Peer-to-peer systems nowadays are widely used because of the scalability and high reliability. File replication and consistency maintenance are widely used techniques to achieve high system performance. These techniques are connected to each other. The connection of these techniques is consistency maintenance is needed in file replication to keep the consistency between a file and the replicas. Traditional file replication and consistency maintenance methods need a high cost. The usage of IRM (Integrated file Replication and Consistency Maintenance inP2P systems) which will achieve high efficiency at a significantly lower cost can be used to solve this problem. IRM reduces redundant file replicas, consistency maintenance overhead, and unnecessary file updates.
Enhancing Big Data Processing Efficiency in AI-Based Healthcare Systems: A Comparative Analysis of Random Forest and Deep Priyadi, Priyadi; Migunani, Migunani; Sasmoko, Dani
Journal of Technology Informatics and Engineering Vol. 3 No. 3 (2024): December (Special Issue: Big Data Analytics) | JTIE: Journal of Technology Info
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i3.205

Abstract

This research focuses on optimizing the speed of Big Data processing using Artificial Intelligence (AI) in healthcare applications. The study integrates Random Forest (RF) and Deep Learning (DL) algorithms with cloud-based computing systems to improve data processing efficiency. The dataset includes both structured data, such as Electronic Health Records (EHR), and unstructured data, like medical images. The results show that RF performs better with structured data, achieving a lower Mean Squared Error (MSE) and higher R-squared (R²) than traditional methods. Meanwhile, DL achieves superior accuracy and Area Under the Curve (AUC) in processing unstructured data. By utilizing the distributed computing power of Spark on a cloud platform, the processing speed was significantly enhanced, as demonstrated by a statistically significant reduction in processing time (p < 0.05) observed through a t-test analysis comparing Spark-based computing with traditional methods. Despite these improvements, challenges such as data privacy and infrastructure costs remain. Despite these improvements, challenges such as data privacy and infrastructure costs remain. This research provides a robust framework for real-time healthcare data analysis, highlighting its potential to improve decision-making processes and patient outcomes in medical services.
Co-Authors Agus Priyadi Agus Priyadi Agustinus Budi Santoso Ahmad Suadi Ahmad Zaenudin Ahmad Zainudin Alber, Alber Ambarsari, Ambarsari Ana Fitrotun Nisa Andik Prakasa Hadi Andika, Robby Asnawi Asnawi Asnidar Asnidar Ati Suryana, Dinda Auliahaq, Dafa Agta Bagus Sudirman Budi Santoso Danang Danang Dani Sasmoko Daniel Rudjiono Dendy Kurniawan Diyas Adikrisna Dulbari, Dulbari Eka Satria Wibawa Eko Sediyono Elvi Sunarsih Erni Erni Haris Ihsanil Huda Holil, Maskur Imaliya, Tri Indra Ava Dianta Intan Kumalasari Julaeny Mia Anggraeni, Anggraeni Kamsul, Kamsul Khairil Anwar Kuncoro, Wreda Agung Kusumajaya, Robby Andika Lukman Santoso Lukman, Santoso Maksuk Marcus Gunadi Wibawa Maya Utami Dewi, Maya Utami Migunani Migunani Mohammad Kanzunnudin, Mohammad Muhamad Syarifudin Mukhlis, Muhammad Murtono Murtono Nadiavalen Faradhomas , Qonnas Navianti, Diah Nuris Dwi Setiawan Priyadi , Agus Priyono, Diah Wasis Putri, Sherly Pradipta Arshyindi Raden Mohamad Herdian Bhakti Rahmadi, Rizky Regista Lidyani Rejeki , Rara Sri Artati Reni Veliyanti Rochman, Fajar Rusito S Siswanto Saputra T, Fider Shomary, Sudirman Sopianti, Maya Sri Yulianto Joko Prasetyo subarjo, Subarjo Sutarsa, I Ketut Teguh Setiadi Titi Christiana Wardani, Oki Puspita yatmin, yatmin Yuliawan, Tri Yuniharto, Bonifatius Sigit