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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Najah: Journal of Research and Community Economics Studies and Banking Journal
Furqon, Ainul
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Humanities Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Public Health Other

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Impelementasi AI Chatbot Sebagai Support Assistant Website Universitas Nurul Jadid Menggunakan Algoritma BiLSTM Rianto, M. Erfan; Furqon, Ainul
Najah: Journal of Research and Community Service Vol. 2 No. 3 (2024): September 2024
Publisher : Kalam Nusantara Institute

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

Abstract

This research aims to implement an AI-based chatbot as a virtual assistant to support information services at Nurul Jadid University. The chatbot is designed using the Bidirectional Long Short-Term Memory (BiLSTM) algorithm, a deep learning model capable of understanding and responding to conversations naturally. With this chatbot, it is expected to improve the efficiency and effectiveness in providing information to the public, as well as being the first step for Nurul Jadid University in utilizing AI technology to improve service quality. Furthermore, this research will also analyze the extent to which AI-based chatbots can help reduce the workload of administrative staff in answering questions frequently asked by the public and prospective students. The chatbot is expected to be the first line of defense in answering basic questions, allowing administrative staff to focus on more complex tasks. The results of this research are expected to be a reference for other universities in implementing AI-based chatbots to improve information and communication services with the community.
Islamic Social Finance and Poverty Alleviation Furqon, Ainul; Nurhayat, Nurhayat; Mukhid, Mukhid
Economics Studies and Banking Journal (DEMAND) Vol. 1 No. 5 (2024): Economics Studies and Banking Journal (DEMAND)
Publisher : Penelitian dan Pengembangan Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62207/ghjxrq94

Abstract

Islamic social financing, including zakat, waqf, and infaq, has attracted attention as a potential tool in poverty alleviation, especially in Muslim-majority countries. This research aims to analyze the effectiveness of Islamic social financing in reducing poverty in Muslim-majority countries compared to non-Muslim countries. The research method used was PRISMA to systematically review the literature from relevant articles. The research results show that Islamic social financing has significant potential in reducing poverty and income inequality. The implication of this research is the importance of improving the management and distribution of zakat, waqf and infaq funds to maximize their impact on social and economic welfare.
Peningkatan Usaha Kelompok Nelayan di UMKM Rusamin dengan IMS (Integrated Management System) Berbasis Web Codeigniter Tholib, Abu; Furqon, Ainul; Rahman, Taufiqur
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 3, No 3 (2022)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/trilogi.v3i3.5115

Abstract

UMKM konvensional masih terkendala dalam hal promosi dan pemasaran produk, sehingga banyak pembeli yang berada diluar kota masih kurang mengetahui produk apa saja yang diproduksi sehingga omset penjualan tidak meningkat selain itu juga sering terjadi kekeliruan dan kesalahan dalam mencatat transaksi penjualan yang dilakukan yang dapat menyita waktu dalam pembuatan laporannya. Pengelolaan data penjualan juga belum optimal karena belum adanya distribusi data ke masing-masing bagian sehingga sering terjadi ketidakcocokan data antara bagian gudang. metode penelitian yang dilakukan menggunakan data penelitian kualitatif, yaitu penelitian yang dilakukan melalui Observasi dan wawancara di UMKM Rusamin. Hasil  penelitian ini menunjukkan bahwa penggunaan aplikasi  Framework Codeigniter dengan berbasis web di UMKM Rusamin dapat memudahkan pihak manajemen dalam monitoring penjualannya.
Detection of Eight Skin Diseases Using Convolutional Neural Network with MobileNetV2 Architecture for Identification and Treatment Recommendation on Android Application Furqon, Ainul; Malik, Kamil; Fajri, Fathorazi Nur
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 2 (2024): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i2.28817

Abstract

Skin diseases are common in Indonesia due to the tropical climate, high population density, and low public awareness about skin health. These diseases are often caused by infections, chemical contamination, or other external factors and typically develop internally before becoming visible, with contact dermatitis being the most frequently reported condition. To address this issue, this research proposes the use of Artificial Intelligence (AI), specifically Convolutional Neural Network (CNN) with the MobileNetV2 architecture, to detect eight types of skin diseases, namely cellulitis, impetigo, athlete's foot, nail fungus, ringworm, cutaneous larva migrans, chickenpox, and shingles. MobileNetV2 was chosen for its efficiency and high accuracy in mobile applications. The methodology involves developing a detection system using CNN MobileNetV2, integrated into an Android application to identify skin diseases and provide treatment recommendations. The dataset was collected, labeled, resized, and normalized to meet the model requirements. After training, the model was tested using a separate dataset to ensure its generalization ability and was finally integrated into the Android application. This application allows users to detect skin diseases and receive treatment advice directly. The research results show that the CNN MobileNetV2 model achieves high accuracy in classifying the eight types of skin diseases, with stable performance over several training epochs. Evaluation of the test dataset revealed an overall accuracy of 97%, with high precision, recall, and F1-score for all disease classes. The application achieved an accuracy of 84% on general data, demonstrating its practical utility. However, the need for real-time updates of treatment information was identified as a limitation. This research advances skin disease detection technology and improves public access to accurate healthcare services. Future studies should focus on real-time treatment information updates and expanding the range of detectable diseases to enhance skin disease application.
Co-Authors Abu Tholib Fathorazi Nur Fajri Malik, Kamil Mukhid, Mukhid Nurhayat Nurhayat, Nurhayat Rianto, M. Erfan Taufiqur Rahman, Taufiqur