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Journal : Journal of Applied Data Sciences

Cognition-Based Document Matching Within the Chatbot Modeling Framework Jatmika, Sunu; Patmanthara, Syaad; Wibawa, Aji Prasetya; Kurniawan, Fachrul
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.209

Abstract

The aim of the study is to examine cognitive methods for document matching in a chatbot modeling framework by utilizing Euclidean Distance, Cosine Similarity, and BERT methodologies. Five primary indications are used to carry out evaluation in testing: document matching accuracy, document matching execution time, document search efficiency, consistency of document matching results, and the quality of the document representation in the matrix. Document matching accuracy is evaluated by precision; document matching execution time is measured from the beginning to the end of the document matching process; document search efficiency is measured through evaluation of execution time and matching accuracy; the consistency of document matching results is assessed by comparing method results when tested against the same or similar queries and the quality of document representation is assessed based on the method's ability to represent documents in a matrix or vector. The test findings offer a comprehensive understanding of how well the three approaches operate and exhibit their capacity to address the unique requirements of chatbot users. These results may contribute to the advancement of language technology applications, making it possible for chatbots to deliver pertinent information more rapidly and precisely. There are 1,755 labeled question samples in the dataset, which were split up into two sets: 60% for training (1,053 pieces), and 40% for testing (702 samples) to evaluate the model's performance. The test results show the accuracy of the three methods based on five measured evaluation indications, namely Euclidean Distance 0,45%, Cosine similarity 0,59%, and BERT 0,91%.  By comprehending the benefits and drawbacks of each approach, this research strengthens contributions to the growth of chatbot systems to better serve user demands and opens the door for the creation of more complex human-machine interaction solutions.
Clustering-Based Adaptive UX in E-Learning Systems: Aligning Microservices with the 4C Framework Belluano, Poetri Lestari Lokapitasari; Patmanthara, Syaad; Ashar, Muhammad; Kurniawan, Fachrul; Kurubacak, Gulsun
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.884

Abstract

This study introduces a clustering-driven adaptive User Experience (UX) architecture for e-learning systems, aligning machine learning segmentation with the 21st-century 4C educational framework (critical thinking, communication, collaboration, creativity). The objective is to dynamically personalize digital learning interactions through a microservices architecture responsive to users' UX profiles. A quantitative survey was conducted involving 50 active users of Shopee and Tokopedia, whose interaction feedback was mapped using the User Experience Questionnaire (UEQ). Three unsupervised clustering techniques—KMeans, Agglomerative, and DBSCAN—were compared. KMeans outperformed the others with a silhouette score of 0.157, compared to 0.146 for Agglomerative and −0.017 for DBSCAN, identifying three meaningful clusters representing high, medium, and low UX proficiency. A one-way ANOVA test confirmed statistically significant differences (p 0.01) among the clusters in dimensions such as error clarity, support responsiveness, and user confidence. These UX profiles were then mapped to individualized microservices: Cluster 0 received autonomous content with minimal support, Cluster 1 was offered guided prompts, and Cluster 2 was provided with simplified interfaces and proactive assistance. Each cluster was aligned with specific 4C competencies to ensure pedagogical relevance. The proposed architecture, built with gRPC-based microservices, enabled asynchronous, low-latency personalization based on user cluster membership. The novelty of this research lies in its dual alignment—technological (microservices + machine learning) and educational (4C competency mapping)—to construct a scalable and responsive e-learning environment. The system design, although validated through simulation, demonstrates a practical foundation for future deployment in platforms like Moodle or OpenEdX. By linking behavioral UX clustering to pedagogical intervention strategies, this study offers a model for adaptive, data-informed instructional systems that are both scalable and learner-centered.
Co-Authors Achmad Imam Agung Agung Bella Putra Utama Aji Prasetya Wibawa Al Mukafi, Muhammad Hamdan Amrullah, Ahmad Khakim Angga Achmad Cholid Anwar, Akhmad Syaiful Arie Wardhono Arizia Aulia Aziiza Arsyillah, Nazhiroh Tahta Asfani, Khoirudin Ashar, Muhammad Ashar, Muhammad Asih Setiani Aya Sofia Mufti Ayuningtyas Kurniawati Azhar Ahmad Smaragdina Benti Gandisa Bramastya, Rista Daniar Wahyu Akbar Oktaviando Dendy Dewa Widjaya Putra Dhega Febiharsa Didik Dwi Prasetya Didik Nurhadi Dila Umnia Soraya Djoko Kustono Djunaidi Ghany Dyah Lestari Eddy Sutadji Eddy Triswanto Setyoadi Eddy Triswanto Setyoadi Ega Putriatama Eko Setiawan Eko Setiawan Ekohariadi Ekohariadi Elfia Najib Kholifiatin Evania Kurniawati Fachrul Kurniawan Fadli Hidayat, M. Noer Fahmi Efendi Yusuf Fandi Akhmad Kurniawan Fatmawati, Hefi Ferdiansyah, Dodik Septian Fikha Rizky Aullia Firman Syahputra, Yohanes Dhimas Gülsün Kurubacak Hakkun Elmunsyah Hanna Zakiyya Hari Putranto Harits Ar Rosyid Harmanto Harmanto Hartarto Junaedi Hary Suswanto Hermansyah, Winda Adelia Heru Wahyu Herwanto Hidayat, Manik I Made Sudana I Made Wirawan Ikhwan Arif Ilmam, Thirafi Indraswari, Martha Devi Intan Sulistyaningrum Sakkinah Isnandar Jayadi, Puguh Joumil Aidil Saifuddin Kholiqin, Sabrina Nabila Kurniawan, Rivan Adi Kurubacak, Gulsun Lokapitasari Belluano, Poetri Lestari M. Zainal Arifin M. Zainal Arifin Mahali, Mahali Marji Marji MAULA, PUTRINDA INAYATUL Meidy, Ria Devita Meidy, Ria Devita Mentari, Febiana Putri Moh. Afifullah Mubarok, Sulton Muhammad Auva Romadhon Muhammad Hamdan Al Mukafi Muhammad Hudan Rahmat Mukhamad Angga Gumilang Muladi Naurah Septi Anggraini Nia Arlika Nidhom, Ahmad Mursyidun Ningrum, Gres Dyah Kusuma Nur Aini Susanti Nur Hidayat, Wahyu Nur Hikmah Nurul Hidayati Odhitya Desta Oki Dwi Yuliana Perdana Putra, Muhammad Ricky Prasetyo, Wiji Dwi Prayoga, Adie Purnomo, Purnomo R. Mahmud Sugandi Rahajeng Kartika Sari Rahmawati, Chusnia Ramadiani, Nanda Resta Resti Pranata Putri Ria Devita Meidy Rizal, Muhammad Fatkhur Rokhimatul Wakhidah Sari, Rahajeng Kartika Shofiyah Al Idrus Singgih Adie Kurniawan Siti Munawaroh Slamet Wibawanto Soenar Soekopitojo Suci Lestari Sunu Jatmika, Sunu Suparji Suparji Sutapa, Yohanes Gatot Titasari Rahmawati Tiya Nurul Khusna Tri Atmadji Sutikno Tri Wrahatnolo Triyana Widiyaningtyas Triyanna Widiyaningtyas Wahyu Sakti Gunawan Irianto Waras Waras Yuli Sutoto Nugroho Yuliana, Oki Dwi Yuniardi, Gigih Dwi Yussi Anggraini Zaeni, Ilham Ari Elbaith Zulfikar, Nizam Muchammad