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All Journal BEES: Bulletin of Electrical and Electronics Engineering Journal of Informatics, Electrical and Electronics Engineering
Nasution, Della Fatricia
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Rancang Bangun Sistem Presensi Biometrik Sidik Jari Berbasis IoT dengan Arduino Node MCU Kusuma, Rizky Tri; Solikhun, Solikhun; Saputra, Widodo; Windarto, Agus Perdana; Nasution, Della Fatricia
BEES: Bulletin of Electrical and Electronics Engineering Vol 4 No 3 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v4i3.4636

Abstract

Presence is a procedure or process that needs to be carried out by all employees or members of a company or agency. The attendance register is a reference and benchmark for assessing, measuring, and determining the quality and quantity of each member or employee of the company or agency. Presentations carried out manually are considered less effective and efficient in terms of time and usage. So it is necessary to build an intelligent attendance system, one of which is by creating an intelligent attendance system that uses IoT-based fingerprint recognition technology with an Arduino controller and outputs to an Internet or intranet server. Based on the results obtained in the research, administrators can float their side servers freely. The time for sending data from the presence device to the server uses the POST method, with an average time of 8 seconds on an intranet network with a maximum distance of 25 meters from the wireless router or access point. By creating this attendance system, it makes it easier for the Surya Pematangsiantar Education Foundation to record the attendance of teachers and staff, especially SMK units.
Analisis Penerapan Data Mining Terhadap Kasus Positif Covid-19 Menggunakan Metode K-Means Clustering Azhari, Ridhan; Hartama, Dedy; Lubis, Muhammad Ridwan; Nasution, Della Fatricia; Windarto, Agus Perdana
Journal of Informatics, Electrical and Electronics Engineering Vol. 3 No. 2 (2023): Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v3i2.1760

Abstract

This study has problems such as the absence of the use of the K-means clustering algorithm for data on positive COVID-19 cases in the Indonesian province. The purpose of this study is to apply the K-means clustering method in finding the closest distance to produce the lowest and highest clusters of data on positive COVID-19 cases in the Indonesian province. K-means is one of the algorithms in the non-hierarchical Clustering technique that tries to partition the existing data in the form of one or more clusters. The results obtained from the k-means clustering method produced 2 clusters, namely the lowest cluster C1 = 30 items while the highest cluster C2 = 4 items. This research can be used as a reference and can be further developed with other clustering methods or algorithms such as k-medoid in order to get a comparison of results and steps to use algorithms related to clustering.
Co-Authors Agus Perdana Windarto Azhari, Ridhan Hartama, Dedy Kusuma, Rizky Tri Muhammad Ridwan Lubis Solikhun Solikhun, Solikhun Widodo Saputra