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All Journal Journal of Islamic Pharmacy Journal of Islamic Medicine International Journal of Informatics and Computation Jurnal Pengembangan Sistem Informasi dan Informatika J-Intech (Journal of Information and Technology) Prosiding Seminar Nasional Inovasi Teknologi Terapan Journal Of Artificial Intelligence And Software Engineering Jurnal Inovasi Teknologi Terapan Journal of Technology and Engineering
Evvin Faristasari
Politeknik Manufaktur Negeri Bangka Belitung
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Library & Information Science Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences

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Journal : Journal Of Artificial Intelligence And Software Engineering

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Laplacian Kernel and Deep Learning for Palmprint Classification Duli, Sirlus Andreanto Jasman; Wisesa, Bradika Almandin; Faristasari, Evvin; Peprizal, Peprizal; Putri, Vivin Mahat; Fadila, Resma
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): Juni On-Progress
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.6978

Abstract

Palmprint classification is a robust biometric method for personal identification due to its uniqueness and stability. This study explores the use of deep learning combined with the Laplacian Kernel and Deep Morphological Processing Network (DMPN) for palmprint classification. We trained the proposed system on a dataset of palmprint images collected from 10 participants, each contributing 10 palm images. The results demonstrated that the model achieved an accuracy of 90%, with weighted precision, recall, and F1-score all at 0.9007, indicating a well-balanced classification performance. Additionally, the model achieved a weighted precision of 0.9045, emphasizing its ability to minimize false positives. The average Equal Error Rate (EER) of 0.0917 indicates an effective balance between the false acceptance rate (FAR) and false rejection rate (FRR). The system was tested under various conditions, including different orientations, lighting, and backgrounds, demonstrating its robustness in real-world scenarios. This study also compares the results with recent palmprint classification techniques, such as deep learning, GANs, and few-shot learning, and discusses potential improvements, including incorporating multi-spectral data fusion and few-shot learning to enhance performance in real-world applications.
Developing an NLP-Based Chatbot for Waste Management Education in Sungailiat Wisesa, Bradika Almandin; Mahat Putri, Vivin; Faristasari, Evvin; Jasman Duli, Sirlus Andreanto; Lionza, Rahmat
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i3.7522

Abstract

Penelitianinimemaparkanpengembangan dan evaluasi menyeluruh terhadap chatbot berbasis Natural Language Processing (NLP) yang dirancang untuk meningkatkan pendidikan pengelolaan sampah di Bank Sampah Sungailiat, Indonesia. Dengan mengintegrasikan logika fuzzy untuk pencocokan Pertanyaan yang Sering Diajukan (FAQ) secara akurat dan memanfaatkan model NLP berbasis transformer, DialoGPT-medium, chatbot inimemberikan respons yang relevan secara kontekstual terhadap pertanyaan pengguna mengenaioperasional bank sampah, termasuk pemilahan sampah, proses daur ulang, dan insentif ekonomi. Penelitian ini menangani masalah rendahnya kesadaran masyarakat terhadap praktik pengelolaan sampah yang tepat, yang menghambat partisipasi efektif dalam program daurulang. Sistem hibrida ini mencapai akurasi respons sebesar 85% dalam p engujian pengguna, divalidasi melalui analisis matriks konfusi yang mendetail. Temuan utama menunjukkan peningkatan signifikan dalam keterlibatan pengguna, retensi pengetahuan, dan kesadaran masyarakat, menunjukkan potensi chatbot sebagai solusi pendidikan lingkungan yang berbasis teknologi dan dapat diskalakan untuk konteks serupa di seluruh Indonesia
Co-Authors Abd. Rasyid Syamsuri Ade Putra Maulana Ade Amin, Fita Avrista Vilusi Better Swengky Bradika Almandin Wisesa Daniel, Rodo Enggar Hero Istoto Fadila, Resma Hero Istoto, Enggar Indra Irawan Jasman Duli, Sirlus Andreanto Lionza, Rahmat Peprizal, Peprizal Putri, Vivin Mahat Silvia Agustin Silvia Agustin Sirlus Andreanto Jasman Duli Sukma, Shafril Muliawan Wathan, M.Hizbul Yudhi