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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Journal of Computer Networks, Architecture and High Performance Computing Pengabdian Deli Sumatera
Doughlas Pardede
Universitas Deli Sumatera
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Economics, Econometrics & Finance Education Materials Science & Nanotechnology Physics Social Sciences

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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.
Digital Green Education through Green Chemistry Supports the Green Economy by Improving Science Skills and Entrepreneurial Character Hamela Sari Sitompul; Intan Maulina; Doughlas Pardede
Jurnal Penelitian Pendidikan IPA Vol 11 No 10 (2025): October
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i10.12332

Abstract

Green education is integrated into chemistry learning to support the green economy, as it offers numerous applications in everyday life, including waste management and sustainable reforestation programs. Based on the Merdeka Curriculum, one aspect of chemistry learning in grade 10 is green chemistry, which explores global issues and problem-solving. Science skills are closely linked to green education in chemistry learning, as students gain scientific knowledge and attitudes from the theories they learn. All these efforts are directed toward achieving the Sustainable Development Goals (SDGs). The research used a quasi-experimental Design. The study had two groups, the experimental and the control groups. The sample was SMA Negeri 1 Gunung Meria, Deli Serdang Regency students. The research instruments used were essay tests and observations. The results of the posttest t-test analysis between the control and the experimental group at a significance level of 0.05, then 0.00 <0.05, then Ho is rejected and Ha is accepted. The results of the students' entrepreneurial character scores can be seen in Figure 1, where the experimental class has an average score of 77.70 and the control class 42.85. The results of the study can be concluded that education has a significant influence on students' science process skills. Students' entrepreneurial character shows a substantial difference, in that in the experimental class, there is good development.
RANCANG BANGUN WEBSITE MENGGUNAKAN CONTENT MANAGEMENT SYSTEM (CMS)/WORDPRESS UNTUK UMKM Aulia Ichsan, S.T., M.Kom.; Said Hambali Takhir; Doughlas Pardede; Sugeng Riyadi; Mhd Harry Azhari As’ad
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

Pelaku usaha mikro, kecil, dan menengah (UMKM) di Indonesia masih banyak yang belum memanfaatkan teknologi digital, khususnya website, sebagai sarana pemasaran dan pengembangan bisnis. Permasalahan utama yang dihadapi adalah keterbatasan pengetahuan teknis serta anggapan bahwa pembuatan website memerlukan keahlian pemrograman yang tinggi. Kegiatan pengabdian kepada masyarakat ini bertujuan memberikan pelatihan praktis kepada pelaku UMKM dalam membangun website secara mandiri menggunakan Content Management System (CMS) WordPress. Kegiatan dilaksanakan pada Sabtu, 27 September 2025, pukul 09.00 WIB di Aula Lantai I Gedung Universitas Deli Sumatera, dengan melibatkan lima dosen sebagai mentor/coach. Metode yang digunakan meliputi ceramah interaktif, demonstrasi langsung, dan praktik mandiri peserta. Hasil kegiatan menunjukkan peningkatan pemahaman dan kemampuan peserta dalam membuat serta mengelola website menggunakan WordPress. Peserta mampu menginstalasi WordPress, memilih tema, menambahkan konten, serta mengelola halaman bisnis secara mandiri. Kegiatan ini diharapkan mendorong digitalisasi UMKM sehingga meningkatkan jangkauan pasar dan daya saing usaha.
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

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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 Aulia Ichsan Aulia Ichsan, S.T., M.Kom. Hamela Sari Sitompul Intan Maulina Irwan Daniel Mhd Harry Azhari As’ad Said Hambali Takhir Sugeng Riyadi Sugeng Riyadi