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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Zenit Seminar Nasional Informatika (SEMNASIF) Conference SENATIK STT Adisutjipto Yogyakarta Compiler Informasi Interaktif CCIT (Creative Communication and Innovative Technology) Journal Makara Journal of Science JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Bernard Renaldy Suteja
Universitas Kristen Maranatha
Aerospace Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering

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Penerapan Model Semantik dalam Pengolahan Arsip Berita Iwan Santosa; Panji Yudasetya Wiwaha; Bernard Renaldy Suteja
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 8 No. 2 (2023): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v8i2.230

Abstract

Arsip berita yang dimiliki sebuah institusi merupakan sumber informasi yang menyimpan rekam jejak dan sejarah perkembangan institusi tersebut. Informasi ini dalam ruang lingkup yang lebih luas dapat menjadi sumber pengetahuan (knowledge) sebagai referensi pengambilan keputusan strategis. Pengolahan arsip konvensional dilakukan menggunakan dokumen berupa tabel sederhana. Pengambilan informasi dari arsip konvensional hanya dapat dilakukan secara terbatas, sehingga informasi pengetahuan yang terdapat dalam arsip berita tersebut tidak dapat dimanfaatkan secara optimal. Dalam penelitian ini dirancang pemodelan arsip berita menggunakan model semantik, dengan tujuan agar informasi yang terkandung dalam arsip berita dapat dengan mudah dicari dan diambil. Model yang dihasilkan selanjutnya dapat digunakan dan dihubungkan dengan sumber pengetahuan lainnya. Penelitian ini berhasil membuktikan bahwa Ontology Web Language (OWL) yang dibentuk menggunakan Protege dapat digunakan untuk memodelkan arsip berita. Pengujian ontologi dilakukan menggunakan kueri DL dan SPARQL. Rancangan ontologi kemudian diekspor dalam format RDF/XML agar dapat dihubungkan dengan ontologi lainnya, sehingga dapat didayagunakan untuk menghasilkan pengetahuan baru yang lebih luas.
Pemanfaatan SPARQL Dalam Pencarian Data Alih Kredit Merdeka Belajar Kampus Merdeka Agiharta, Kafka Febianto; Suteja, Bernard Renaldy
Jurnal Teknik Informatika dan Sistem Informasi Vol 9 No 3 (2023): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v9i3.6742

Abstract

The Merdeka Belajar Kampus Merdeka (MBKM) program provides facilities for students to transfer credits from work activities to specific courses. To support this process, this research utilizes Semantic Web technology by integrating an ontology built using the Protégé tool. Through the use of SPARQL query language, Semantic Web technology enables efficient and accurate searching between activity descriptions and courses based on the context and semantic meaning of the data. The research results show that this research can retrieve the required information efficiently and accurately from the ontology that has been developed.  
Pemonitoran Paparan Merek Terfokus Menggunakan Pemodelan Topik dan Formulasi Kueri Santosa, Iwan; Suteja, Bernard Renaldy; Budi, Setia
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 1 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i1.8395

Abstract

Brand exposure monitoring is a specialized form of media monitoring that aims to monitor brand exposure and brand mentions in publicity media. This research proposes a framework model for monitoring brand exposure through analysis of publicity media utilizing query formulation and topic modeling, aimed at extracting important topics contained in external media or mass media, and comparing them with the institution's internal media. Topic extraction is performed using Latent Dirichlet Allocation (LDA) method on text data in the form of SERP (Search Engine Results Page) snippets. Subsequent processing utilizes Jaccard index and cosine similarity calculations. The output of the framework includes visualizations of topics representing themes of articles exposing the institution's brand, and measurement metrics that are useful for decision-making analysis related to media management and institutional communication. Testing the proposed framework using data samples resulted in expected output, namely the topic groups formed can represent dominant topics in both media categories in a given monitoring period, with the highest coverage rate reaching 82.69% and similarity of 33.97%. The use of LDA method in this study does have its limitations, specifically the formation of topic groups that do not purely contain a singular topic, but rather consist of several subtopics. However, this does not diminish the usefulness of the framework.
Penerapan Sentence BERT Untuk Similaritas Kompetensi Pekerjaan dan Mata Kuliah Agiharta, Kafka Febianto; Suteja, Bernard Renaldy; Ayub, Mewati
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 3 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i3.9411

Abstract

This research focuses on the application of the Sentence BERT (S-BERT) model, a specialization of the BERT model and an adaptation of the Transformer architecture specifically designed for the Indonesian language, in exploring the concept of course credit transfer consolidation in accordance with the Merdeka Belajar – Kampus Merdeka program. The aim of this exploration is to develop an Indonesian-language S-BERT model and apply it to search and analyze the similarity between activity sequence descriptions and course syllabus (RPS) descriptions. The results of this similarity analysis are the identification of relevant courses based on the given query. The developed model has shown effective capabilities in searching and determining the similarity between activity sequence descriptions and course syllabus descriptions. Courses identified as relevant to the query demonstrate high similarity and compatibility, indicating that the S-BERT model can be relied upon in the process of course credit transfer consolidation within the context of Merdeka Belajar – Kampus Merdeka.
Perancangan Index Learning Style untuk Pengembangan Personalisasi Learning Management System berbasis Moodle Sianipar, Helen Anjelica; Chaeruman, Uwes Anis; Tarjiah, Indina; Suteja, Bernard Renaldy
Jurnal Teknik Informatika dan Sistem Informasi Vol 11 No 1 (2025): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v11i1.10418

Abstract

Differences in students' learning styles often pose challenges in online learning, particularly in personalizing learning materials to meet individual needs. This study developed an Index Learning Style (ILS) plugin based on the Felder-Silverman Learning Style Model (FSLSM) to support personalized learning on the Moodle Learning Management System (LMS). The plugin is designed to identify students' learning styles through 44 questions measuring four main dimensions: processing, perception, input, and understanding. The system development involved algorithms for learning style analysis, integration with Moodle's restricted access feature, and implementation in an Internet of Things (IoT) course. The implementation results show that the ILS plugin can effectively map students' learning styles to relevant Learning Object Materials (LOM). Moreover, personalized learning materials increase student engagement and facilitate material comprehension, particularly for those with dominant learning styles such as Active, Sensitive, Visual, and Sequential. The development of the ILS plugin provides a practical solution for enhancing the online learning experience to make it more adaptive. This plugin has the potential for widespread implementation in various technology-based education contexts to support more personal and effective learning.
Co-Authors Afiany, Nurul Agiharta, Kafka Febianto Agus Harjoko Agus Harjoko Agustaf, Rusdy Ahmad Ashari Ahmad Asharit Andreas Widjaja Anggara, Erik Dwi Antonius Antonius Antonius Antonius Antonius Antonius Arie Tunggal Billyanto Hendrik Billyanto Hendrik Budi Wibowo Suhanjoyo Chaeruman, Uwes Anis Cristover, Ronaldo Hapnes Toba Haryadi, Lucky Surya Hendrik, Billyanto Imbar, Radiant Indina Tarjiah Irawan, Yosef Ariyanto Iwan Santosa Iwan Santosa Iwan Santosa, Iwan Jaya, Try Atmaja Linggan Jingga, Kenny Johan, Meliana Johan, Meliana Christianti Kafka Febianto Agiharta Kenny Jingga Liman, Nathanael Lucky Surya Haryadi Maresha Caroline Wijanto Maresha Caroline Wijanto Mewati Ayub Nathanael Liman Nurul Afiany Panji Yudasetya Wiwaha Panji Yudasetya Wiwaha Rafliana, Trian Retantyo Wardoyo Robby Tan Robby Tan Ronaldo Cristover Rusdy Agustaf Setia Budi Setia Budi Sianipar, Helen Anjelica Sri Hartati Suryo Guritno Suryo Guritno Suryo Guritno Taufan Abdurrachman Teddy Marcus Zakaria Try Atmaja Linggan Jaya Tunggal, Arie Yosef Ariyanto Irawan