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All Journal Nusanatara of Engineering JURNAL PENGABDIAN KEPADA MASYARAKAT PROCEEDING IC-ITECHS 2014 JOIV : International Journal on Informatics Visualization MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Antivirus : Jurnal Ilmiah Teknik Informatika Jambura Journal of Electrical and Electronics Engineering Jurnal Tecnoscienza JATI (Jurnal Mahasiswa Teknik Informatika) Respati JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Journal of Computer Networks, Architecture and High Performance Computing Science in Information Technology Letters Journal of Soft Computing Exploration International Journal of Engineering, Science and Information Technology Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Archive: Jurnal Pengabdian Kepada Masyarakat Jurnal Borneo Informatika dan Teknik Komputer (JBIT) The Indonesian Journal of Computer Science Research Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Journal of Entrepreneurial and Business Diversity
Erna Daniati
Universitas Nusantara PGRI Kediri
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Few-Shot-BERT-RNN Narrative Structure Analysis for Andersen's Stories Daniati, Erna; Wibawa, Aji Prasetya; Irianto, Wahyu Sakti Gunawan; Hernandez, Leonel
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3932

Abstract

Event Extraction (EE) is a pivotal task for NLP, where important events in the narrative text need to be detected and recognized. We present an alternative method for extracting events from Hans Christian Andersen's fairy tales, utilizing Few-Shot Learning with BERT (Bidirectional Encoder Representations from Transformers) and RNN (Recurrent Neural Network) in this paper. We selected Andersen's fairy tales because they are characterized by rich narratives and symbolic language, which also often prevents automatic event extraction. To reduce reliance on labeled samples, we utilize the Few-Shot Learning method, which enables the model to learn from a small number of labeled event examples trivially. The BERT model is used to generate deep representations by modeling the context between words and sentences. RNN is essential to capture the sequence of events in the story, which determines the structure of the narrative. The findings demonstrate that the proposed framework significantly improves event extraction, with high values of evaluation metrics such as in accuracy, precision, recall, and F1-score. The proposed method is also effective in extracting non-explicit events while keeping the narrative context. Despite the challenges posed by metaphorical language and subjective events, this work demonstrates that Few-Shot Learning, BERT, and RNNs offer a promising solution to the task of event extraction from complex narratives.
Weak Supervision Dengan Pendekatan Labeling Function Untuk Analisis Sentimen Pada Twitter Utama, Hastari; Daniati, Erna; Masruro, Ahlihi
The Indonesian Journal of Computer Science Research Vol. 3 No. 1 (2024): January
Publisher : Hemispheres Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59095/ijcsr.v3i1.93

Abstract

Penggunaan sosial media saat ini telah meningkat dengan pesat. Salah satu jenis media sosial yang digunakan adalah Twitter. Media sosial ini memiliki miliaran pengguna dari seluruh dunia. Jadi, dalam waktu yang singkat data tweet yang mereka posting telah ada pada penyimpaannya. Setiap pengguna juga dibatasi jumlah karakter dalam melakukan pengiriman tweetnya. Namun, kumpulan tweet pada media sosial ini memiliki konteks tema yang bervariatif. Hal ini dapat memuat sentimen emosional seperti senang, sedih, gembira, duka, dan sebagainya. Berbagai jenis data tweet yang disediakan ini sangat berpotensial untuk dianalisis terutama bagi perusahaan berbasis profit. Hal ini dapat memuat kebiasaan pelanggan, tren produk, indeks saham, dan sebagainya. Salah satu jenis analisis yang dilakukan adalah sentiment analisis. Hal ini berguna untuk mengklasifikasikan opini tweet yang ada. Opini ini dapat berupa positif, negatif, atau netral. Hasil analisis ini sangat diperlukan perusahaan untuk mengetahui tren yang terjadi pada era ini. Salah satu solusi yang ditawarkan pada penelitian ini adalah dengan menggunakan Weak Supervision. Namun, ada tantangan yang terjadi pada metode ini. Hal ini adalah kuranganya tingkat akurasi jika dibandingkan dengan pelabelan secara manual.  Pada penelitian ini dilakukan pelabelan otomatis dengan weak supervision. Selain itu, dilakukan pendekatan labeling function dan Regex Pattern dalam melakukan pelabelan secara otomatis. Hal ini diharapakan dataset yang dilabeli akan menghasilkan model dengan tingkat akurasi mendekat pelabelan secara manual, lebih lagi jika dapat mengungguli metode manual. Selain itu, kontribusi yang diharapkan dalam penelitian ini adalah usaha untuk mempersingkat waktu pelabelan daripada dilakukan secara manual.Ringkasan penelitian tidak lebih dari 500 kata yang berisi latar belakang penelitian, tujuan dan metode penelitian yang diusulkan, luaran yang ditargetkan, serta uraian kontribusi penelitian. Gunakan style Abstract pada bagian ini dengan satu paragraf.
Comparison of C4.5 and Naive Bayes for Predicting Student Graduation Using Machine Learning Algorithms Tholib, Abu; Fadli Hidayat, M Noer; yono, Supri; Wulanningrum, Resty; Daniati, Erna
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 2 No. 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3364

Abstract

Student graduation is a very important element for universities because it relates to college accreditation assessment. One of them is at the Faculty of Engineering Nurul Jadid University, which has problems completing the study period within a predetermined time. So that it can be detrimental because accreditation is less than optimal, and the number of active students makes it less ideal in teaching and learning activities. This study aimed to compare the level of accuracy using the C4.5 algorithm and Naïve Bayes method in predicting graduation on time. The C4.5 and Naïve Bayes algorithms are one of the methods in the algorithm for classifying. Tests were carried out using the C4.5 and Naïve Bayes algorithms using Google Colab with Python programming language, then validated using 10-fold cross-validation. The results of this study indicate that the Naïve Bayes method has a higher accuracy value with an accuracy rate of 96.12%, while the C4.5 algorithm method is 93.82%.
Attention-Enhanced Convolutional Neural Network for Context Extraction in Andersen's Fairy Tales Daniati, Erna; Wibawa, Aji Prasetya; Irianto, Wahyu Sakti Gunawan; Nafalski, Andrew
JOIV : International Journal on Informatics Visualization Vol 9, No 6 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.6.4056

Abstract

Event extraction in classic literature and fairy tales remains highly challenging due to their non-linear plot structures, archaic linguistic expressions, and intricate character interactions, while advances in modern NLP still show limitations in capturing subtle narrative cues in historical texts. This study aims to address these gaps by developing an event extraction model tailored to the narrative characteristics of Hans Christian Andersen’s fairy tales. We propose a BERT-enhanced Context-aware Convolutional Neural Network (CNN) that integrates an attention mechanism to overcome the limited contextual range of traditional CNNs. The model leverages BERT’s contextual embeddings enriched with an attention layer to detect event triggers, character relations, and narrative transitions across nonlinear storylines. A hybrid dataset was constructed through system-generated annotations refined via manual verification and combined with AN/an cartoon-based representations for model training and final testing. Experimental results show that the proposed model surpasses both the CNN-only baseline and a rule-based approach, achieving precision of 0.92, recall of 0.89, F1-score of 0.90, and accuracy of 0.91, outperforming the CNN baseline (0.85/0.82/0.83/0.84) and rule-based system (0.78/0.75/0.76/0.77). These findings highlight the effectiveness of context-aware representations for processing literary narratives and demonstrate interdisciplinary relevance to digital humanities and AI-based storytelling, with future extensions envisioned for multilingual settings and genre-specific adaptations.
Inovasi Digital berbasis Video Dokumenter untuk Mempromosikan Kearifan Lokal Desa Budaya Seyegan Wahyuni, Sri Ngudi; Vijaya, Rosyidah Jayanti; Maemunah, Mei; Daniati, Erna
Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Vol. 5 No. 2 (2025): November - Abdiformatika: Jurnal Pengabdian Masyarakat Informatika
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/abdiformatika.v5i2.263

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan mengembangkan video dokumenter sebagai alat promosi bagi Desa Budaya Seyegan. Hal ini disebabkan minimnya kunjungan wisatawan ke Desa Budaya Seyegan ini yang memiliki potensi budaya dan alam yang besar. Topik ini dipilih untuk meningkatkan kesadaran masyarakat dan daya tarik wisatawan, serta memperbaiki kondisi ekonomi lokal. Metode pengabdian masyarakat yang digunakan meliputi kolaborasi antara akademisi dan masyarakat lokal dalam mendokumentasikan tradisi, seni, dan kearifan lokal. Hasil penelitian menunjukkan bahwa video yang dihasilkan berhasil menarik perhatian, hal ini tebukti dengan jumlah viewer 25 view sealam 8 hari di kanal Youtube Pengabdi. Video dokumenter ini difungsikan untuk meningkatkan visibilitas desa, dan mendorong pelestarian budaya dan memperluas jangkauan promosi. Kesimpulannya, inisiatif ini tidak hanya berfungsi sebagai promosi tetapi juga sebagai arsip budaya yang penting, dengan rekomendasi untuk pelatihan pembuatan konten bagi masyarakat lokal guna mendukung pengembangan pariwisata yang berkelanjutan.
Co-Authors Abadi, Ahmad Fajar Abu Tholib Achmad, Ridho Afrizal Ahmad Bayu P Agustama, Andri Tri Aidina Ristyawan Aidina Ristyawan, Aidina Aji Prasetya Wibawa Akmal Hisyam Pradhana Alamsyah, M Alfianto Aliyyah Fitri Nur'aini Alja, Farhan Maulana Amarya, Theo Krisna Amelia Nur Fadhila Andy G, Asye Candra Angga Wibisono Anita Sari Wardani ANUARIDLO, Mochamad Aldi Yusuf Anusua Ghosh, Anusua Ardiansyah , Bima Ardyansyah, Fikri Arie Nugroho, Arie Arie, Theo Yan Arti Romansa, Shasya Aulia, Ewanda Herdika Septa Azzahra, Salsabila Dini Bachti, Achmad Syauqi Bastian Dwiki Prasetyo Christy Atika Sari Cintiana Adisti, Talita Cristina Juwita Agata Dewi, Candrika Arlita Diah Kurniawati, Virginia Dimas Abimanyu Dimas Regga Meydianto Ditto Syahrul S Dwi Hariani Dwi Harini DWI HARINI Dwi Harini Dzatama, Krisna Fahrizal Eko Hari Rachmawanto Ery Mintorini Fadhila, Amelia Nur Fadli Hidayat, M Noer Fadli Hidayat, M. Noer Farhan Gagat Retnanto Faruq, Umar Al Faruqziddan, Muhammad Fatayasya, Ikhfal Fauzi, Mohammad Ainun Naja Felmidi, Ferdian Ahmat Firmansyah, Achmad Ali Fitriono, Deri Hastari Utama Herdika Septa Aulia, Ewanda Hyperastuty, Agoes Santika Ilahi, Ferlita Putri Anugerah Intan Aprilia Rahman Irfa’udin, Muhammad Islami, Bifadhlillah Marsheila Jauhar, Moh. Iqbal Iqza Kamilatutsaniya, Nila Khalid, Muhammad Iqbal Leonel Hernandez, Leonel Lestari, Afifah Kurnia Lukman, Muhammad Abi Maemunah, Mei Maha Shelin Sahira Masruro, Ahlihi Moh Kusen Muhammad Fahmi Muhammad Fikri Pratama Muhammad Hafiz Yustiar Muhammad Imron Amrulloh Muhammad Najibulloh Muzaki Mustofa, Mohammad Annan Makruf Muzaki, Muhammad Reza Nafalski, Andrew Naufal Rizqulloh Ningrum, Dea Yuliana Ayu Nngrum, Dea Yuliana Ayu Nugroho , Arie Nugroho, Arie Nur Alamsyah, Nur Nurfajriana, Intan Melinda Pradhana, Akmal Hisyam Prayogi, Anindita Puspa Ayu Priyanto, Evania Putra, Regi Candra Purnama Putri Wahyuni, Hesti Putri, Fitria Dessela Putriani, Dewi Ratih Kumalasari Niswatin Resty Wulanningrum Rina Firliana Rini Indriati Rini Indriati Rino Adi Kurniawan Ristiyawan, Aidina Ristyawan , Aidina Rizki Wahyu Nugroho Rosyidah Jayanti Vijaya, Rosyidah Jayanti Sahira, Maha Shelin Sakin, Kharisma Santoso, Heru Teguh Sari Wardani, Anita Sasongko, Muhammad Zuhdi Setiawan, Fachruddin Ari Shofyana, Altha Inas Sri Ngudi Wahyuni, Sri Ngudi Suci Dewanti Sucipto Sucipto sugandhi sugandhi saputra Supri yono Supri Yono, Supri Syafa’at, Achmadhin Tristan Teguh Andriyanto Theo Krisna Amarya Thoyib Fernanda Nanda Utama, Hastari Varuq, M Nizar Bahri Al Wahiid, Hermawan Nur Wahyu Sakti Gunawan Irianto Wardani, Anita Sari Wardani, Saylendra Arga Wardhani, Aurel Fransisca Kusuma Wiranata, Hadi Wiwik Juniati Yongki Dyno Oka Satria Yulva Irfan Anas Yuszril Herdianzah Yuszril