Claim Missing Document
Check
Articles

Found 13 Documents
Search

Implementasi Retrieval Augmented Generation dalam Sistem Chatbot Dermatologi Berbasis Website Kharisma, Ivana Lucia; Hidayat, Muhammad Syarif; Somantri, Somantri; Kamdan, Kamdan
Jurnal Teknik Informatika dan Sistem Informasi Vol 11 No 3 (2025): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v11i3.12258

Abstract

Indonesia’s tropical climate, poor sanitation, and limited access to medical services especially in remote areas are key factors contributing to the high prevalence of skin diseases. Direct access to dermatologists remains difficult for many people. This study aims to develop a dermatological consultation Chatbot using a Retrieval Augmented Generation (RAG) approach, leveraging the LangChain framework, the LLaMA model, and the Qdrant vector database. The dataset includes 30 types of skin diseases sourced from the National Library of Medicine. The preprocessing stage involved whitespace normalization, removal of special characters, and handling of missing values to ensure data consistency before vectorization. Evaluation results showed high scores for Faithfulness (0.9429) and LLMContextRecall (0.9600), indicating that the responses were relevant and aligned with the source documents. However, a relatively low Precision score (0.4720) suggests a need for improved information accuracy. The Chatbot is integrated with the Chainlit platform, offering an interactive user interface that supports login, conversation history, and user feedback features to facilitate system development based on user input. The system demonstrated fast retrieval times (0.08–0.29 seconds), though answer generation remains slow due to CPU infrastructure limitations (255–283 seconds). Future improvements should focus on enhancing answer accuracy, optimizing the model's performance, enriching the medical reference dataset, and adding automated medical validation features to ensure the reliability of consultations. Therefore, this Chatbot system is expected to serve as a cost-effective and efficient alternative for providing initial information on skin conditions to individuals with limited access to healthcare services.
Argumentasi Fatwa Dar Al-Ifta Al-Mashriyyah tentang Shalat Jum’at dalam Jaringan (Daring) Fahmi Hasan Nugroho; Muhammad Syarif Hidayat
Khazanah Hukum Vol. 3 No. 2 (2021): Khazanah Hukum Vol 3, No 2 August (2021)
Publisher : UIN Sunan Gunung Djati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kh.v3i2.11924

Abstract

Penelitian ini menganalisis argumentasi fatwa dari Dar al-Ifta al-Mashriyyah terkait shalat Jum’at yang dilaksanakan melalui jaringan, baik bermakmum melalui radio maupun melalui panggilan video online. Penelitian ini menemukan bahwa Dar al-Ifta al-Mashriyyah menyatakan bahwa shalat yang dilakukan melalui jaringan radio ataupun internet tidak sah dilaksanakan karena tidak memenuhi syarat sah shalat jum'at yaitu dilakukan secara berjamaah serta imam dan makmum berada di tempat yang sama. Argumentasi terkuat yang diajukan oleh Dar al-Ifta al-Mashriyyah adalah tiga argumentasi ijma’, yaitu ijma’ bahwa khutbah adalah syarat sah shalat Jum’at, ijma’ bahwa shalat Jum’at harus dilaksanakan secara berjamaah, dan ijma’ bahwa shalat Jum’at hanya dapat dilaksanakan di masjid. Selain argumentasi ijma’, Dar al-Ifta al-Mashriyyah juga berargumentasi dengan sunnah Rasulullah dalam pelaksanaan shalat Jum’at dan sejumlah argumentasi lain. Penelitian ini merupakan penelitian hukum normatif dengan pendekatan klinis hukum (istinbath al-hukm). Data yang dikaji dalam penelitian ini adalah lima buah fatwa Dar al-Ifta al-Mashriyyah yang dirilis antara tahun 1950 hingga tahun 2020
The Impact of AI Virtual Tutor ‘DeepSeek’ on Students’ Writing Proficiency Muhammad Syarif Hidayat; Zaitun
INTERACTION: Jurnal Pendidikan Bahasa Vol. 13 No. 1 (2026): INTERACTION: Jurnal Pendidikan Bahasa
Publisher : Program Studi Pendidikan Bahasa Inggris, Universitas Pendidikan Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36232/interactionjournal.v13i1.4231

Abstract

This study investigated the impact of the AI virtual tutor DeepSeek on students’ writing proficiency among tenth-grade students of a Madrasah Aliyah in Pamulang, Indonesia, using a quantitative pre-test–post-test design with a sample of 31 students. Students completed five essay-based writing tasks measuring content, organization, vocabulary, language use, and mechanics. Their scores were analyzed using the Wilcoxon Signed Rank Test to determine the significance of improvement after four weeks of DeepSeek-assisted practice. The results showed a statistically significant increase in overall writing performance, indicating that real-time feedback from DeepSeek supported students’ self-regulation, accuracy, and clarity in writing. The novelty of this study lies in examining DeepSeek an emerging AI tutor that has received very limited empirical investigation within an authentic classroom setting, offering new evidence of its pedagogical value compared to more commonly studied tools such as ChatGPT or Quillbot. The study concludes that DeepSeek is a valuable instructional aid and recommends its integration into English writing instruction to complement traditional teaching.