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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING METIK JURNAL Haga Journal of Public Health (HJPH)
RICO WIJAYA DEWANTORO
universitas Prima Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Public Health

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Analysis Of Right And Wrong Use Of Mask Based On Deep Learning Rico Wijaya Dewantoro; Sonni Yudha Nugraha Arfan; Reyhan Achmad Rizal
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.7582

Abstract

Pandemic COVID-19 makes it important to apply the proper and correct use of masks. The correct use of a mask where its use can cover the nose mouth and chin. One of the problems in using masks is that there are still many people who have not used masks properly and correctly. The importance of the correct use of masks because the transmission of the Covid-19 itself does not only occur through splashes when sneezing or coughing between humans but can also occur when talking or breathing by spreading through fluid particles less than 0.0002 inches (5 microns) in diameter called aerosols that are emitted when people talk. From these problems  it is necessary to have a computational-based analysis system to be able to identify patterns and make decisions and perform certain tasks automatically so that the results obtained are more efficient and objective. In this study, a deep learning method with a resnet  50 will be used to obtain the correct and incorrect results of using masks. The results of this study indicate that the deep learning method with resnet 50 is able to achieve 98.41% accuracy in classifying the correct and incorrect use of masks.
Manfaat sistem informasi geografis terhadap penyakit dengue: Scoping Review Andrian Reinaldo Crispin; Mido Ester J Sitorus; Defacto Firmawati Zega; Pratik Bibhishan Kamble; Rico Wijaya Dewantoro
Haga Journal of Public Health (HJPH) Vol. 1 No. 1 (2023): November 2023
Publisher : YAYASAN VICTORY HAGA INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62290/hjph.v1i1.13

Abstract

Latar Belakang: Demam dengue merupakan penyakit yang masih menjadi masalah kesehatan masyarakat dibanyak negara saat ini. Akibat masih tingginya prevalensi dengue maka perlu pemanfaatan Sistem Informasi Geografis (SIG) untuk memprediksi kejadian penyakit dengue. Penelitian ini bertujuan untuk menyelidiki dan merangkum manfaat SIG untuk penyampaian informasi penyebaran penyakit dengue. Metode: Penelitian ini dilakukan dengan menggunakan metode scoping review. Pencarian literatur dilakukan pada database terindeks Google Scholar, Scopus dan PubMed, dalam bahasa Inggris. Terdapat 440 jurnal penelitian dan hanya 11 yang memenuhi kriteria inklusi. Dari 11 jurnal tersebut dikumpulkan informasi berupa rentang tahun publikasi 2013-2023, judul jurnal, desain penelitian, populasi penelitian, intervensi, hasil, dan manfaat SIG untuk penyakit dengue. Analisis data dilakukan secara kualitatif dengan menyajikan data dan menyusun laporan penelitian. Hasil: Penggunaan SIG terhadap penyebaran dengue dapat bermanfaat untuk mengidentifikasi situasi terkini dengue di suatu wilayah, dan memastikan wilayah yang berpotensi terdampak wabah dengue dengan menentukan klaster spasial kejadian dengue pada skala lokal, memprediksi kasus dengue yang lebih baik serta membantu proses pemantauan dan pengawasan yang lebih baik terhadap masyarakat yang terdampak, serta memfasilitasi pengambilan keputusan dalam pencegahan dan pengendalian penyakit dengue. Kesimpulan: Penggunaan SIG memiliki peran penting untuk memprediksi, mengidentifikasi, membantu proses pemantauan dan pengawasan serta pengendalian penyakit dengue.
Penerapan Algoritma EDDSA dalam Menjamin Keamanan dan Keaslian Dokumen Elektronik Berbasis Konsensus Proof of Work Rico Wijaya Dewantoro; Hendra Tampan Mangatur Sagala; Angelina Tambunan; Medima Ronauli Sitorus; Putri V Sui Minarti Pane
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/dtyxpr72

Abstract

The exchange of digital documents remains vulnerable to alteration, forgery, and manipulation due to third-party attacks and the weaknesses of centralized systems. This study aims to implement the Edwards-curve Digital Signature Algorithm (EdDSA), integrated with blockchain technology based on the Proof of Work (PoW) consensus mechanism, to ensure the security, integrity, and authenticity of electronic documents. The novelty of this research lies in the integration of the EdDSA digital signature mechanism with a Proof of Work consensus-based blockchain to create an electronic document verification system. The research method used is experimental, involving the development of a blockchain-based system using the Python programming language and the Flask framework on a local network simulation consisting of 5 nodes. Each document is processed using the SHA-256 hash function to generate a unique digital fingerprint, which is then digitally signed using EdDSA before being validated through a Proof of Work consensus mechanism and stored on the blockchain network. Research results show that the system achieves a 100% success rate in document verification and manipulation detection, with the EdDSA algorithm generating consistent 64-byte signatures, an average signing time of 0.00048 seconds, and a verification time of 0.00108 seconds. An average block size of 863 bytes and a mining time of 1.02 seconds on a 5 node network demonstrate the system’s efficiency and strong performance. Thus, the combination of EdDSA and a Proof of Work-based blockchain has proven capable of forming a secure, transparent, and decentralized electronic document security system that enhances trust in the use of electronic documents.
Co-Authors Andrian Reinaldo Crispin Angelina Tambunan Defacto Firmawati Zega Hendra Tampan Mangatur Sagala Medima Ronauli Sitorus Mido Ester J Sitorus Pratik Bibhishan Kamble Putri V Sui Minarti Pane Reyhan Achmad Rizal Sonni Yudha Nugraha Arfan