Article Per Year (5 Year)
p-Index From 2021 - 2026
1.037
P-Index
This Author published in this journals
All Journal Journal of Computer Networks, Architecture and High Performance Computing Deli Sains Informatika Hanif Journal of Information Systems Pengabdian Deli Sumatera
Aulia Ichsan
Universitas Deli Sumatera
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Education Library & Information Science Social Sciences

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
PEROLEHAN OPTIMASI NILAI ICMP BERSTANDART (TIPHON) MENGGUNAKAN METODE QUEUE TREE DAN PCC Aulia Ichsan
Deli Sains Informatika Vol. 2 No. 1 (2022): Artikel Riset Desember 2022
Publisher : LPPM Universitas Deli Sumatera

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dalam sebuah jaringan internet terdapat kualitas layanan yang diberikan kepada penggunanya. Dari berbagai layanan yang diberikan ada yang baik ada pula yang tidak. Tidak sedikit dalam sebuah jaringan internet banyak pengguna yang mengeluh dengan memperoleh nilai bandwidth yang lemah, saling tumpang tindih dan banyak lagi. Sehingga pengguna jaringan internet tidak merasa kenyamanan bandwidth yang baik Hal ini merupakan dampak yang seharusnya di minimalisir, untuk meminimalisir hal tersebut dibutuhkan suatu metode tertentu, metode yang digunakan adalah mengkombinasikan metode queue tree dan per connection queue (PCQ) metode ini menghasilkan layanan internet lebih komleks, terstruktur, sama rata dan stabil. Disamping itu nilai yang diperoleh dalam pengujian pada skripsi ini adalah nilai dari ICMP (Internet Control Message Protocol) dan memenuhi standart TIPHON (Telecommunications and Internet Protocol Harmonization Over Networks) baik troughput, delay, jitter dan packet loss. Pengujian yang dilakukan merupakan hasil dari virtual mandiri mengunakan router mikrotik dan beberapa fakultas di lingkungan UISU. Kata kunci: Layanan internet, parameter uji ICMP, TIPHON
Android-Based Practical Work Student Registration Form Application System Design Aulia Ichsan; Mhd. Zulfansyuri Siambaton; Khairuddin Nasution
Hanif Journal of Information Systems Vol. 1 No. 1 (2023): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v1i1.4

Abstract

This system is designed to improve the efficiency of the attendance process through the use of information technology. The system allows students to register for attendance online through an android-based mobile application. Implementation involves developing an application with registration and attendance recording features, as well as student data management. Evaluation involves user feedback to improve performance and functionality. The support of PT PLN (Persero) is very important in the implementation of this system. The hope is that this online attendance system can improve the efficiency, accuracy, and reliability of the attendance process for practical work students at PT PLN (Persero) and provide guidance for other organizations in utilizing information technology.
Enhancing Multi-Layer Perceptron Performance with K-Means Clustering Doughlas Pardede; Aulia Ichsan; Sugeng Riyadi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3600

Abstract

Machine learning plays a crucial role in identifying patterns within data, with classification being a prominent application. This study investigates the use of Multilayer Perceptron (MLP) classification models and explores preprocessing techniques, particularly K-Means clustering, to enhance model performance. Overfitting, a common challenge in MLP models, is addressed through the application of K-Means clustering to streamline data preparation and improve classification accuracy. The study begins with an overview of overfitting in MLP models, highlighting the significance of mitigating this issue. Various techniques for addressing overfitting are reviewed, including regularization, dropout, early stopping, data augmentation, and ensemble methods. Additionally, the complementary role of K-Means clustering in enhancing model performance is emphasized. Preprocessing using K-Means clustering aims to reduce data complexity and prevent overfitting in MLP models. Three datasets - Iris, Wine, and Breast Cancer Wisconsin - are employed to evaluate the performance of K-Means as a preprocessing technique. Results from cross-validation demonstrate significant improvements in accuracy, precision, recall, and F1 scores when employing K-Means clustering compared to models without preprocessing. The findings highlight the efficacy of K-Means clustering in enhancing the discriminative power of MLP classification models by organizing data into clusters based on similarity. These results have practical implications, underlining the importance of appropriate preprocessing techniques in improving classification performance. Future research could explore additional preprocessing methods and their impact on classification accuracy across diverse datasets, advancing the field of machine learning and its applications
Analysis of Logistic Regression Regularization in Wild Elephant Classification with VGG-16 Feature Extraction Aulia Ichsan; Sugeng Riyadi; Doughlas Pardede
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 2 (2024): Articles Research Volume 6 Issue 2, April 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i2.3789

Abstract

The research article explores the intersection of image-based wildlife classification and logistic regression regularization, focusing on the classification of wild elephant species. It begins by highlighting the significance of ecological research in biodiversity monitoring and conservation and introduces Convolutional Neural Networks (CNNs) as potent tools for feature extraction from images. The VGG-16 model is particularly emphasized for its ability to capture hierarchical representations of visual features crucial for classification tasks. The integration of VGG-16 feature extraction with logistic regression regularization is proposed as a compelling approach, offering a balance between sophisticated feature representation and efficient classification algorithms. The literature review delves into image-based wildlife classification, emphasizing the role of CNNs, especially VGG-16, in extracting discriminative features. It discusses the fusion of VGG-16 features with logistic regression and the challenges in this field, such as dataset annotation and environmental variability. The method section outlines the dataset acquisition, feature extraction using the VGG-16 architecture, and model configuration using logistic regression with lasso and ridge regularization. The process of finding the optimal regularization parameter (lambda) and model evaluation through cross-validation is detailed. Results showcase the optimal lambda values for lasso and ridge regularization and compare the performance of logistic lasso and logistic ridge models. Misclassification analysis reveals factors influencing classification accuracy, including feature variability and contextual complexity. The discussion reflects on the implications of the findings, emphasizing the importance of lambda selection and addressing challenges in wildlife classification. It suggests avenues for further research, such as advanced modeling techniques and feature engineering approaches. In conclusion, the study contributes to advancing wildlife classification efforts by leveraging state-of-the-art techniques and sheds light on opportunities to enhance classification accuracy in wildlife conservation.
DIGITALISASI PAGUYUBAN WARGI SUNDA SUMATERA UTARA: IMPLEMENTASI WEBSITE DAN DATABASE Aulia Ichsan; Irwan Daniel; Doughlas Pardede; Sugeng Riyadi
Pengabdian Deli Sumatera Vol 4 No 1 (2025): Artikel Pengabdian Juli 2025
Publisher : LLPM Universitas Deli Sumatera

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Paguyuban Wargi Sunda Sumatera Utara (PWS Sumut) merupakan organisasi kultural yang menjadi wadah bagi masyarakat Sunda di Sumatera Utara untuk melestarikan identitas budaya, mempererat ikatan sosial, serta menguatkan peran aktif komunitas dalam kehidupan berbangsa dan bernegara. Namun dalam era digitalisasi informasi yang terus berkembang pesat, organisasi ini menghadapi tantangan serius berupa keterbatasan sistem dokumentasi, pengelolaan data anggota yang belum terstruktur secara digital, minimnya kehadiran online yang dapat menjangkau komunitas lebih luas, serta rendahnya efisiensi komunikasi dan koordinasi antar pengurus dan anggota yang tersebar di berbagai wilayah Sumatera Utara. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk melaksanakan digitalisasi menyeluruh bagi PWS Sumut melalui pembangunan website organisasi berbasis Content Management System (CMS) dan implementasi sistem database keanggotaan yang terintegrasi. Kegiatan dilaksanakan pada Sabtu, 18 Januari 2025 di Convention Hall Gedung Perpustakaan Universitas Medan Area (UMA), dalam rangkaian Seminar Nasional Kebangsaan bertema Penerapan Falsafah Sunda Dalam Ketahanan Sosial Budaya Nasional Di Era Digitalisasi Informasi. Metode pelaksanaan meliputi pelatihan teknis, demonstrasi langsung, dan pendampingan implementasi sistem. Hasil kegiatan menunjukkan bahwa PWS Sumut berhasil memiliki website resmi yang memuat profil organisasi, agenda kegiatan, berita, galeri, serta database keanggotaan yang dapat dikelola secara digital oleh pengurus. Lebih dari 87,5% peserta pelatihan menyatakan mampu mengoperasikan sistem secara mandiri, dan lebih dari 91,7% menyatakan puas terhadap keseluruhan kegiatan. Digitalisasi ini diharapkan meningkatkan efektivitas komunikasi organisasi, memperluas jangkauan komunitas Sunda di Sumatera Utara, dan mendukung pelestarian nilai budaya Sunda di era digital.
Co-Authors Doughlas Pardede Irwan Daniel Mhd Zulfansyuri Siambaton Sugeng Riyadi Sugeng Riyadi