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All Journal Jurnal Teknoinfo Journal of Applied Sciences and Advanced Technology Journal of Engineering and Information Technology for Community Service
Syarif Hidayatullah
Universitas Pakuan
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Mathematics Social Sciences Other

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IDENTIFIKASI BIOMETRIKA MENGGUNAKAN EKSTRAKSI MINUTIAE PADA CITRA SIDIK JARI Gustian Rama Putra; Boldson Herdianto Situmorang; Syarif Hidayatullah
Jurnal Teknoinfo Vol 17, No 1 (2023): Vol 17, No 1 (2023): JANUARI
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v17i1.2376

Abstract

Biometrik berbasis citra sidik jari merupakan teknik pengenalan diri dengan menggunakan sidik jari untuk mewakili identitas seseorang. Sidik jari merupakan ciri identitas seseorang secara tepat dan aman karena tidak ada kesamaan dan tidak dapat dipalsukan. Tujuan penelitian ini adalah mengembangkan sistem identifikasi biometrik berbasis citra sidik jari dengan memanfaatkan kamera ponsel untuk akuisisi citra sidik jari. Hal ini didasari oleh kemudahannya karena hampir setiap orang memiliki telepon genggam sehingga sistem identifikasi seseorang berdasarkan sidik jari dapat digunakan kapanpun dan dimanapun. Penelitian dilakukan dengan menggunakan gambar yang dihasilkan dari kamera ponsel dengan spesifikasi kamera 2, 5 dan 8 mega piksel. Metode yang digunakan dalam pengolahan citra terdiri dari metode minutiae crossing number untuk proses ekstraksi ciri dan metode minutiae based matching untuk proses pengukuran kemiripan. Hasil penelitian menyimpulkan bahwa kamera ponsel dengan spesifikasi 5 dan 8 mega piksel dapat digunakan untuk proses akuisisi citra pada sistem biometrik berbasis sidik jari. Proses ekstraksi ciri hasil citra menggunakan metode minutiae crossing number dan proses pengukuran kecocokan menggunakan metode minutiae based matching menghasilkan nilai akurasi sebesar 92,8% pada kamera 5 mega piksel dan 95,3% pada kamera 8 mega piksel. Nilai akurasi tergantung dari hasil tahap akuisisi citra, pre-processing, nilai threshold pada proses identifikasi dan jumlah citra yang digunakan pada data training di database.
Desain Canva Sebagai Media Promosi Usaha Mikro dan Media Informasi di Desa Bantarsari Gustian Rama Putra; Arie Qurania; Yusma Yanti; Puspa Citra; Syarif Hidayatullah; Hermawan Hermawan; Victor Ilyas Sugara; Asep Saepulrohman; Agung Prajuhana Putra; Kotim Subandi; Adriana Sari Aryani; I Wayan Sriyasa
Journal of Engineering and Information Technology for Community Service Vol 1, No 3 (2023): Volume 1, Issue 3, January 2023
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jeit-cs.v1i3.210

Abstract

Digital information media in this era has very good potential, especially in developing micro-businesses to introduce their products, besides that information media is also needed to provide education and information to socialize, this is very necessary for the government in the district to develop village results and information that can be conveyed clearly to the community. Community service carried out by the Computer Science Study Program of Pakuan University aims to provide training to village office staff and junior and senior high school students in Bantarsari Village to be able to apply Canva as a medium for promoting micro-business and related information media, socialization, disaster prevention, appeals and other notifications in Bantarsari Village
Alert Control Model for Exposure of COVID-19 in Industrial Closed Work Space Hermawan Hermawan; Kotim Subandi; Adriana Sari Aryani; Syarif Hidayatullah; Dinar Munggaran Akhmad; Victor Ilyas Sugara
Journal of Applied Sciences and Advanced Technology Vol 5, No 3 (2023): Journal of Applied Sciences and Advanced Technology
Publisher : Faculty of Engineering Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/jasat.5.3.105-112

Abstract

The Covid-19 pandemic has changed the industrial management system, including the regulation of labor. Most of the work in the industry cannot be done through work from home, but must still be in production units. In a number of cases, clusters of COVD 19 were found in the industry, forcing the industry to have to lock down. The problem of the lack of a model for controlling the spread of COVID 19 in the manufacturing industry is the basis for this research. The model designed in this study is also expected to be relevant in the new normal era for the manufacturing industry. The modeling and application of COVID-19 control research in the manufacturing industry is carried out through four stages, namely identification and characterization of work patterns, model design and validation, model implementation and verification, and model comparison testing. At the stage of identification and characterization of work patterns using the methods as guided by the International Labor Organization. The design phase and model validation used the Epidemic Mathematics approach and the Shewhart Control Chart. The application of the model in the industry is in accordance with the guidelines for working in a factory during the COVID-19 Pandemic according to the World Health Organization. The comparative test of the model will be processed using the diversity test. The data used is collected from the company in the form of simple tracing monitoring data for workers before entering the work area and shortly before leaving the work area, COVID 19 test data if any, employee health data, and other data if relevant to support this research. The data obtained is used for model design, both the employee health control model and the COVID-19 distribution model in the work area. The model is made with a scope that is limited only to the industrial work environment, not including outside facilities. Contamination to employees may occur when employees return home or are outside the factory. The model also does not adopt the presence of employees who are being treated for COVID-19 healing in a healing facility. In the Shewhart Control Chart model, it is hoped that a control limit can be obtained that can be used to monitor fluctuations in employee health, the diagram will be designed for daily monitoring of workers. Out-of-control data becomes a warning to carry out a reliability test (Capability) and to trace sources of contamination obtained by employees.
Co-Authors Adriana Sari Aryani Agung Prajuhana Putra Arie Qur’ania Asep Saepulrohman Boldson Herdianto Situmorang Dinar Munggaran Akhmad Gustian Rama Putra Hermawan Hermawan I Wayan Sriyasa Kotim Subandi Puspa Citra Victor Ilyas Sugara Yusma Yanti