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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) JURMA : Jurnal Program Mahasiswa Kreatif

Pramuko, Andik Eko Kristus

Universitas Ibn Khaldun Bogor

Author-ID : 5290635

Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences

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Articles

Penerapan PENERAPAN NEAR FIELD COMMUNICATION PADA SISTEM PEMBAYARAN OTOMATIS TRANSPORTASI BUS BERBASIS INTERNET OF THINGS Yuri Nur Kholipa; Dahlia Widyaestoeti; Andik Eko Kristus Pramuko
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 7 No. 2 (2021)
Publisher : Universitas Widyatama

The payment system goes from a manual to a cash transaction to a digital payment system. Automatic payment systems with NFC technology designed on this research. Analysis of business processes and systems analysis. Unified modelling language is designed using the waterfall method, database design, and user interface. The result of this study is a web that can read passenger data from applying NFC, cut off the passenger balance and the automatically transfer of notification on a telegram application with the help of a iot that serves as a connectivity. The assessment of the black box testing on the system with the user module value degree is 0.91.

Kendali Penumpang Otomatis Transportasi Bus Menggunakan Near Field Communication Berbasis Internet of Things Frischa Razzaq Praditya; Dahlia Widhyaestoeti; Andik Eko Kristus Pramuko
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 7 No. 2 (2021)
Publisher : Universitas Widyatama

Automatic Passenger Control of Bus Transportation Using Near Field Communication Based on Internet of Things. Automatic bus transportation passenger control is a system that helps control the number of bus passengers. This system consists of a series of Arduino Mega 2560 microcontrollers, NodeMCU connected to the existing wifi at each bus stop. NFC reader PN532 as a reader of the NFC tag which functions as a passenger id. Passengers boarding the bus must tap the NFC tag on the NFC reader on the bus. The system counts the number of passengers who tap. When the passenger gets off the NFC tag must be on tap back on the NFC reader, the system automatically reduces the number of passengers on the bus. Data processed by the system displayed in the form of information on the LCD on the bus. The results of this study indicate that the sample tag has been successfully read by NFC reader. The data is then processed by the system and stored in a database.

Income Recovery of Metal Craftsmen Affected by Covid 19 in Bogor District Bayu Adhi Prakosa; Meita Arifany; Ade Hendri Hendrawan; Andi Eko Kristus Pramuko
Jurma : Jurnal Program Mahasiswa Kreatif Vol 7 No 1 (2023): Juni 2023
Publisher : LPPM UIKA Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/jurma.v7i1.1710

Increasing cases of COVID-19 are affecting metal craftsmen in small and medium enterprises in Tarikolot Village, Bogor Regency, Indonesia. There is growing research on the use of E-Commerce platforms. But in this study, in Tarikolot Village, Bogor, there is no research on village E-Commerce in marketing products from metal craftsmen. Through in-depth interviews, this research aims to uncover this assumption. How will this situation become more productive? Where, how, to what degree and for what reasons can metalworkers affected by COVID-19 use Village E-Commerce. This research gives researchers and practitioners an idea whether E-Commerce applications can be extended to metal craftsmen or even general affected craftsmen. This research builds a web-based Village E-Commerce application architecture through a descriptive research approach by analyzing the results of questionnaires and interviews. This research uses a descriptive model with data sources being in-depth interviews and a scale of E-Commerce business usage in marketing metal products. The importance of this research is the idea of designing a website-based E-Commerce application for managing metal craftsmen products. There are about 400 more metal craftsmen and 200 more metal craftsmen affected by COVID-19. The findings illustrate to researchers and practitioners that the application of E-Commerce can be expanded to improve marketing and market expansion of village metal crafts.

Enhanced Performance Evaluation of VGG16 and ResNet50 for Deepfake Detection Using Local Ternary Pattern Rizqullah, Ghifari Ferdian; Eosina, Puspa; Pramuko, Andik Eko Kristus
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15582

Deepfake video generation has become increasingly sophisticated, posing challenges for detection methods that rely solely on convolutional neural networks (CNNs without explicit texture enhancement). Many existing approaches have limited robustness in capturing subtle texture inconsistencies caused by manipulation, compression, and noise. This study investigates the integration of Local Ternary Pattern (LTP)–based texture enhancement with transfer learning models for deepfake video detection. Specifically, VGG16 and ResNet50 architectures are evaluated using the Celeb-DF (v2) dataset. LTP is employed to extract fine-grained texture features due to its higher robustness to illumination variations and noise compared to conventional descriptors such as Local Binary Pattern (LBP). Video frames are processed individually and used to train CNN classifiers, followed by evaluation at both frame and video levels. Experimental results show that ResNet50 outperforms VGG16, achieving a test accuracy of 93% with a validation loss of 0.2228, while VGG16 reaches an accuracy of 88% with a validation loss of 0.2636. Further testing on 20 withheld videos demonstrates that ResNet50 correctly classifies all samples, whereas VGG16 misclassifies two real videos, indicating lower robustness to real-video misclassification. These results demonstrate that LTP-based texture enhancement effectively supports CNN-based deepfake detection and that deeper architectures benefit more from enriched texture representations. This study provides empirical insights into improving robustness and reliability in deepfake video classification.

Co-Authors Bayu Adhi Prakosa Dahlia Widhyaestoeti Eko Hadi Purwanto Frischa Razzaq Praditya Hendrawan, A. Hendri Meita Arifany Puspa Eosina Rizki Maulana Hidayat Rizqullah, Ghifari Ferdian Yuri Nur Kholipa

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