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Journal : El-Mujtama: Jurnal Pengabdian Masyarakat

Implementasi Aplikasi Chatbot Informasi Pelayanan Kelurahan Keputih, Surabaya Edelani, Renovita; Satriyanto, Edi; Nadhori, Isbat Uzzin; Susetyoko, Ronny; Barakbah, Aliridho; Karlita, Tita; Muliawati, Tri Hadiah; Fadliana, Alfi; Maulana, Wahyu Ikbal; Insani, Fawzan; Fauzi Nafi'Ubadah, Kriza; Haikal Yuniarta Krisgianto, Ricko; Saputra, Muhammad Krisnanda Vilovan; Ridho, Bistiana Syafina; Ni'Ma, Najma Akmalina; Damayanti, Anita; Febrianto, Ardiansyah Indra; Alde, Muhammad Riski
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 5 No. 2 (2025): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v5i2.6272

Abstract

In today's era of digital transformation, the government, particularly Kelurahan Keputih, is aware of the community's need for information regarding the management of kependudukan and non-kependudukan documents. Given their busy lifestyles, residents require a medium to access information related to these matters. This service information is needed to improve bureaucratic efficiency, accelerate information access, and reduce the burden of manual administrative work. Therefore, researchers have developed an AI-based Intelligent Chatbot application using Large Language Modeling (LLM) technology to assist both employees and residents of Kelurahan Keputih in obtaining information related to the management of kependudukan and non-kependudukan services. The implementation of this Chatbot utilizes the Hugging Face library and the LangChain model, one of the Llama models developed by Meta. This Kelurahan Keputih Service Information Chatbot application is named "BambuBot". This application benefits the residents of Keputih by providing them with interactive, comprehensive, and easily accessible information regarding services for managing kependudukan and non-kependudukan documents, as well as platforms for processing these documents.
Penerapan Aplikasi Klasifikasi Hukum Tajwid Menggunakan Image Processing Kindarya, Fabyan; Kusumaningtyas, Entin Martiana; Barakbah, Aliridho; Permatasari, Desy Intan; Al Rasyid, M. Udin Harun; Ramadijanti, Nana; Fariza, Arna; Syarif, Iwan; Sa'adah, Umi; Saputra, Ferry Astika; Ahsan, Ahmad Syauqi; Sumarsono, Irwan; Yunanto, Andhik Ampuh; Edelani, Renovita; Primajaya, Grezio Arifiyan; Kusuma, Selvia Ferdiana
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 4 No. 2 (2024): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v4i2.1930

Abstract

Tajwid is an important science that regulates the way of reading the verses of the Al-Qur’an properly. Learning Tajwid means knowing the meaning that corresponds to the correct recitation. Learning to read the Al-Qur’an tends to be done traditionally in a place of learning or by calling a teacher to the house. Learning in this way has some drawbacks, such as the limited availability of trained and competent teachers because not all areas have sufficient access to these teachers. Dependence on schedules and locations can be a constraint for students with limited mobility or busy schedules. The role of the teacher is still important in learning tajwid, especially in providing effective explanations, guidance, and feedback. However, to overcome these shortcomings, integration with independent and technology-based learning methods can help improve the accessibility, flexibility, and quality of tajwid learning. The classification of tajwid laws using image processing allows users to see the results of inputting images of verses of the Al-Qur’an into the type of detected nun sukun tajwid and how to recite it. The initial stage of this system in detecting tajwid laws from uploaded images is the input of images by users, which can be done in two ways, namely by directly taking pictures using a smartphone camera or uploading images from the gallery. This is followed by the OCR process to detect the Arabic text contained in the image and provide diacritics for that Arabic text. Finally, letter classification is carried out after nun sukun and classification of tajwid laws contained in accordance with the detected letters after nun sukun. This system has an accuracy rate of 92.18% from the classification results that have been carried out.
Co-Authors A.A. Ketut Agung Cahyawan W Abd. Rasyid Syamsuri Achmad Basuki Achmad Basuki Achmad Basuki Achmad Basuki Achmad Basuki Aditya Afgan Hermawan Adnan Rachmat Anom Besari Afifah, Izza Nur Afrida Helen Afrida Helen Afrida Helen, Afrida Agata, Dias Agus Kurniasari, Arvita Ahsan, Ahmad Syauqi Alde, Muhammad Riski Alfi Fadliana Amali, Darari Nur Amalia Wirdatul Hidayah Amang Sudarsono, Amang Andhik Ampuh Yunanto Andy Yuniawan ANITA DAMAYANTI Anom Besari, Adnan Rachmat Arna Fariza Arvita Agus Kurniasari Arvita Agus Kurniasari Aziz, Adam Shidqul Bayu Dwiyan Satria Bima Sena Bayu Dewantara Budi Santosa Dadet Pramadihanto Dadet Pramadihanto Darari Nur Amali Desi Amirullah, Desi Desy Intan Permatasari, Desy Intan Devira Nanda Kuswhara Devira Nanda Kuswhara, Devira Nanda Dewanto, Raden Sanggar Dias Agata Edelani, Renovita Edi Satriyanto Edi Wahyu Widodo Elizabeth Anggraeni Amalo Entin Martiana Kusumaningtyas Fahrudin, Tresna Maulana Fauzi Nafi'Ubadah, Kriza Febrianto, Ardiansyah Indra Ferry Astika S Ferry Astika Saputra Galih Hendra Wibowo Haikal Yuniarta Krisgianto, Ricko Hamida, Silfiana Nur Hermawan, Aditya Afgan Hidayah, Amalia Wirdatul Hidayah, Nadila Wirdatul Hisyam, Masfu Huda, Achmad Thorikul I Made Akira Ivandio Agusta Idris Winarno Idris Winarno Ihda Rasyada Ilham Iskandariansyah Indah Yulia Prafitaning Tiyas Indah Yulia Prafitaning Tiyas, Indah Yulia Prafitaning Indra Adji Sulistijono Insani, Fawzan Irene Erlyn Wina Rachmawan Irene Erlyn Wina Rachmawan Irene Erlyn Wina Rachmawan, Irene Erlyn Wina Irsal Shabirin Isbat Uzzin Nadhori, Isbat Uzzin Iwan Syarif iwan Syarif Kindarya, Fabyan Kohei Arai Kohei Arai Kohei Arai Kurniasari, Arvita Agus Kusuma, Dedy Hidayat Kusuma, Selvia Ferdiana Louis Nashih Uluwan Arif M Tafaquh Fiddin Al Islami M Udin Harun Al Rasyid, M Udin Harun Mahardhika, Yesta Medya Marlisa Sigita Marlisa Sigita, Marlisa Masfu Hisyam Maulana, Wahyu Ikbal Mayangsari, Mustika Kurnia Mirza Ghulam Rifqi Mirza Ghulam Rifqi Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq, Mohammad Nur Mu'arifin, Mu'arifin Muarifin . Muarifin ., Muarifin Muarifin Muarifin Muh Subhan Muhammad Alfian Muhammad Rois Muhammad Wahyu Nugroho Sakti Nadila Wirdatul Hidayah Nana Ramadijanti, Nana Ni'Ma, Najma Akmalina Nur Rosyid Mubatada'i Nur Rosyid Mubtadai Nur Rosyid Mubtadai, Nur Rosyid Oktavia Citra Resmi Rachmawati Piko Permata Ilham Prasetyo Primajaya, Grezio Arifiyan Puspasari Susanti Putra, Berlian Juliartha Martin Rachmawati, Oktavia Citra Resmi Ratri Cahyaning Winedhar Renovita Edelani Renovita Edelani Ridho, Bistiana Syafina Riyanto Sigit Riyanto Sigit, Riyanto Rizka Rahayu Sasmita Rudi Kurniawan S, Ferry Astika Sa'adah, Umi Saputra, Muhammad Krisnanda Vilovan Sesulihatien, Wahjoe Tjatur Setiawardhana Setiawardhana Setiawardhana, Setiawardhana Subhan, Muh Sumarsono, Irwan Suryani, Indah Yudi Susanti, Puspasari Susetyoko, Ronny Syd. Ali Zein Farmadi Syd. Ali Zein Farmadi, Syd. Ali Zein Tahta Alfina Taufan Radias Miko Tessy Badriyah Tessy Badriyah, Tessy Tita Karlita Tita Karlita Tresna Maulana Fahrudin Tresna Maulana Fahrudin Tri Hadiah Muliawati, Tri Hadiah Tri Harsono Tri Harsono ULURRASYADI, FAIZ Umam, Khotibul Wahjoe Tjatur Sesulihatien Wahjoe Tjatur Sesulihatien Wibowo, Galih Hendra Widodo, Edi Wahyu Wina Rachmawan, Irene Erlyn Yuliana Setiowati Yuliana Setiowati, Yuliana Zainal Arief