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All Journal Ekuitas: Jurnal Pendidikan Ekonomi Journal of Animation & Games Studies Computatio : Journal of Computer Science and Information Systems JIKO (Jurnal Informatika dan Komputer) INTECOMS: Journal of Information Technology and Computer Science Indonesian Journal of Computing and Modeling JATI (Jurnal Mahasiswa Teknik Informatika) Infotech: Journal of Technology Information Jurnal Algoritma, Logika dan Komputasi Go-Integratif : Jurnal Teknik Sistem dan Industri Jurnal Sisfotek Global Ekuitas Jurnal Pnedidikan Ekonomi
Jusia Amanda Ginting
Universitas Bunda Mulia
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences

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SOCIAL NETWORK ANALYSIS PERINGATAN DARURAT RUU PEMILIHAN KEPALA DAERAH Christianto, Stacia; Amanda Ginting, Jusia
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13676

Abstract

Tagar #KawalPutusanMK menjadi trending topic pada 21 Agustus 2024, menimbulkan beragam reaksi masyarakat terhadap putusan Mahkamah Konstitusi terkait perubahan rancangan peraturan tersebut. Penelitian ini bertujuan untuk memetakan sebaran informasi menggunakan Social Network Analysis (SNA) dan analisis sentimen publik menggunakan algoritma Support Vector Machine (SVM). Metodologi penelitian ini menggunakan pendekatan kuantitatif berbasis data. Data dikumpulkan di media sosial X dengan tagar #KawalPutusanMK. Analisis dilakukan dengan SNA untuk mengidentifikasi aktor kunci dalam jaringan sosial berdasarkan degree centrality, betweenness centrality dan closeness centrality. Untuk analisis sentimen, teknik TF-IDF digunakan untuk mengekstraksi fitur dan algoritma SVM diterapkan untuk mengklasifikasikan sentimen ke dalam tiga kategori. Hasil penelitian menunjukkan bahwa aktor utama yang berperan penting dalam penyebaran informasi adalah dessertmeys, dimm_sky, zyzee9, hasbil_lbs, lalalabloem, dsperdana, ddazling_ dan mamtalkatiri. Dalam analisis sentimen, kernel linier memberikan akurasi tertinggi sebesar 67%, diikuti oleh sigmoid sebesar 64%, RBF sebesar 63%, dan polinomial sebesar 59%. Opini masyarakat sebagian besar bersifat negatif (51,18%), sedangkan tanggapan netral dan positif masing-masing mencapai 26,38% dan 22,44%. Penelitian ini menyimpulkan bahwa media sosial X adalah platform penting untuk penyebaran informasi dan analisis opini publik. Saran dari penelitian ini adalah meningkatkan metode pelabelan data dan memilih algoritma yang lebih tepat untuk meningkatkan akurasi analisis di masa depan
PENGUJIAN KERENTANAN SISTEM DENGAN MENGGUNAKAN METODE PENETRATION TESTING DI UNIVERSITAS XYZ Ginting, Jusia Amanda; Ngurah Suryantara, I Gusti Gusti
Infotech: Journal of Technology Information Vol 7, No 1 (2021): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v7i1.105

Abstract

Awareness of information security will be a priority in the event of data loss or damage. This certainly harms the performance of a company or organization due to unpreparedness to resolve or minimize risks that can occur. The impact that occurs on the security system used is that the system cannot provide a sense of security because the system used and has security holes that can be used to exploit systems and networks at XYZ University. This study aims to examine the internal and external security controls of the system by identifying threats that can pose serious problems to assets at XYZ University by using the penetration testing method, the results can be used as a benchmark in measuring the weaknesses of the network and system from external attacks. The goal is to implement preventive controls against risks that can occur to improve system security at XYZ University.
REVOLUTIONIZING DIGITAL TRUST: NETWORK INTRUSION DETECTION SYSTEMS FOR IDENTITY AND SECURITY ASSURANCE IN THE METAVERSE Ginting, Jusia Amanda; Sembiring, Irwan; Putra, Yonathan Rahadi; Marvelino, Matthew
Infotech: Journal of Technology Information Vol 11, No 1 (2025): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i1.381

Abstract

Digital security has become a major challenge in the metaverse, an interactive virtual space that integrates augmented reality and virtual reality. This study develops a machine learning-based Network Intrusion Detection System (NIDS) to enhance security reliability within the metaverse. K-Means and Apriori algorithms are applied to optimize rules in the Snort IDS, enabling more accurate detection of Distributed Denial of Service (DDoS) and Malware Command and Control (CNC) attacks. The results show that rule optimization using machine learning increases detection accuracy for DDoS attacks from 60% to 75% and for CNC attacks from 35% to 40%. Furthermore, this approach successfully reduces the false positive rate. The implementation of the optimized NIDS provides a significant contribution to securing activities in the metaverse, ensuring a safer and more reliable virtual environment.
KLASIFIKASI PELANGGAN PADA CUSTOMER CHURN PREDICTION MODELS MENGGUNAKAN DECISION TREE Sinata, Frans; Thenata, Angelina Pramana; Wijaya, Agustinus Fritz; Suryantara, I Gusti Ngurah; Ginting, Jusia Amanda; Widyaningrum, Destriana; Lumba, Ester
Jurnal Algoritma, Logika dan Komputasi Vol 8, No 2 (2025)
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v8i2.8812

Abstract

Persaingan yang semakin ketat dalam dunia perdagangan modern menuntut perusahaan untuk menerapkan strategi retensi pelanggan yang proaktif, menjadikan prediksi customer churn (pelanggan yang berhenti menggunakan layanan) sebagai fokus utama. Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi model klasifikasi yang memanfaatkan data pelanggan historis guna mengidentifikasi secara dini pelanggan yang berpotensi churn atau tetap loyal. Metode yang digunakan adalah Data Mining, khususnya teknik Klasifikasi, dengan memilih algoritma Decision Tree C4.5 karena keunggulannya dalam menghasilkan aturan keputusan yang transparan dan mudah diinterpretasikan. Dataset yang dianalisis melibatkan 996 sampel pelanggan, mencakup berbagai atribut penting seperti jenis kelamin, usia, metode pembayaran, dan riwayat transaksi. Klasifikasi dilakukan untuk memprediksi status pelanggan ke dalam salah satu dari dua kategori target: loyal atau churn. Hasil pengujian menunjukkan bahwa model yang dibangun mampu mengklasifikasikan 636 pelanggan (sekitar 63.8%) sebagai kategori loyal dan 360 pelanggan (sekitar 36.2%) sebagai kategori churn, dengan mencapai tingkat akurasi model sebesar 98%. Temuan ini menunjukkan efektivitas Decision Tree C4.5 dalam memetakan pola loyalitas pelanggan. Secara praktis, model ini berkontribusi dalam menyediakan wawasan yang terukur bagi perusahaan untuk merumuskan inisiatif pemasaran dan retensi yang lebih tepat sasaran.
Student Centric Model for Learning Analytics in Smart Campus Ecosystem: A Systematic Literature Review I Gusti Ngurah Suryantara; Jusia Amanda Ginting; Raphael Benedict Manuel
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.16279

Abstract

The development of smart campuses has intensified the use of data-driven technologies to support institutional decision-making in higher education. However, many existing smart campus implementations remain system-oriented, with limited emphasis on learning processes and student needs. This study aims to formulate a student-centric model for learning analytics within digital twin–enabled smart campus ecosystems through a systematic literature review. The review follows the PRISMA 2020 guidelines and analyzes peer-reviewed articles indexed in the Scopus database, focusing on digital twins, smart campuses, learning analytics, and data governance. The findings indicate that digital twins have evolved from static digital representations into integrated platforms that combine real-time data, modeling, and analytics to support proactive decision-making. Nevertheless, the integration of learning analytics that explicitly centers on students is still fragmented. The concept of the student digital twin emerges as a promising approach for modeling learners as dynamic analytical entities, but it also raises critical concerns related to ethics, privacy, transparency, and governance. Based on the synthesis, this study proposes a conceptual student-centric model consisting of data sources, sensing mechanisms, student modeling, learning analytics, feedback and intervention pathways, and governance safeguards. The model provides a structured foundation for designing responsible and sustainable learning analytics in smart campus environments.
PENGEMBANGAN APLIKASI PEMBELAJARAN IMERSIF BERBASIS VIRTUAL REALITY MENGGUNAKAN METODE MDLC DAN EVALUASI EUQ Jusia Amanda Ginting; Irwan Sembiring; I Gusti Ngurah Suryantara; Teady Matius Surya Mulyana; Ferry Alamsyah
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.426

Abstract

The advancement of technology in the field of Virtual Reality (VR) offers new opportunities for developing more interactive and immersive learning media. One of the main challenges in online learning is the low level of student engagement in the learning process, as well as the tendency for instructional methods to remain passive. Recognizing this gap and the need for a new technological approach that can encourage active participation, this study aims to develop a VR-based learning application called “FirstMetaClass”. This application is designed to simulate a virtual classroom environment to enhance students’ learning experiences. The application development process follows the Multimedia Development Life Cycle (MDLC) method. The quality of the user experience was evaluated using the Extended User Experience Questionnaire (EUQ). The respondents consisted of 42 university students who participated in the application trial and completed the evaluation questionnaire. The results of the study show that all EUQ dimensions achieved an average score above 4.0 on a 1–5 scale. These findings confirm that the “FirstMetaClass” application successfully provides a positive, engaging, and user-friendly learning experience, while creating a classroom atmosphere that closely resembles the real world and fosters a sense of presence for users.
DIGITAL TWIN DRIVEN SMART CAMPUS DEVELOPMENT: CONCEPTS, CHALLENGES AND OPPORTUNITIES Jusia Amanda Ginting; I Gusti Ngurah Suryantara; Raphael Benedict Manuel
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.595

Abstract

This study aims to examine the development and implementation of digital twin technology in supporting smart campus ecosystems through a Systematic Literature Review approach. The study focuses on identifying technological trends, implementation opportunities, and various challenges that arise in the adoption of digital twin systems within higher education environments. The SLR method was conducted using the PRISMA framework to ensure a transparent and systematic article selection process. A total of 765 initial articles were identified from various academic databases with a publication range from 2015 to 2025. After undergoing the screening and selection process, 36 relevant articles were obtained for further analysis. The results show that digital twin technology has significant potential in supporting smart campus management through real-time monitoring of campus infrastructure, predictive maintenance of facilities, energy management optimization, and data-driven decision-making in university operations. In addition, this review also identifies several challenges in implementing digital twin systems, including data integration complexity, cybersecurity risks, high infrastructure investment requirements, and organizational readiness in facing digital transformation.
ANALISIS SENTIMEN DAN STRUKTUR SOSIAL DALAM PERDEBATAN DARING MENGENAI KEBIJAKAN MAKAN BERGIZI GRATIS (MBG) DI INDONESIA Jusia Amanda Ginting; I Gusti Ngurah Suryantara; Agustinus Fritz Wijaya; Teady Matius Surya Mulyana; Raphael Benedict Manuel
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.596

Abstract

Public policy discussions increasingly take place on social media, where public opinion is shaped not only by message content but also by patterns of user interaction. This study analyzes online conversations related to Indonesia’s Free Nutritious Meal (MBG) policy on platform X by integrating Social Network Analysis (SNA) and sentiment analysis. The dataset consists of 3,459 tweets collected between January 8 and February 11, 2025. Communication networks were constructed based on reply and mention relationships to identify interaction patterns and influential accounts. Sentiment analysis was conducted using a Natural Language Processing approach, with initial labeling based on BERT and further classification using a Support Vector Machine (SVM). Model performance was evaluated using accuracy, achieving a score of 91.78%. The findings reveal that MBG discussions form a relatively sparse yet highly centralized network dominated by a small number of accounts. Most tweets express neutral sentiment, while temporal analysis indicates a significant spike in activity on February 10, 2025. This study demonstrates that integrating network and sentiment analysis provides a more comprehensive understanding of how public opinion evolves in digital environments.
PENGARUH GAMIFIKASI TERHADAP PENINGKATAN KESADARAN KEAMANAN SIBER DAN KEBIASAAN DIGITAL DI UNIVERSITAS XYZ Raphael Benedict Manuel; Jusia Amanda Ginting
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI
Publisher : Institut Sosial dan Teknologi (ISTEK) Widuri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.578

Abstract

The increasing number of cybercrime cases indicates a low level of digital security awareness among the public. Therefore, an interactive and engaging educational approach is needed to better understand the importance of safe behavior in cyberspace. This study aims to develop and test the effectiveness of educational media-based learning media, namely gamification, in increasing cybersecurity awareness. The gamification is designed as an exploration game, watching educational videos inside, and ending with an evaluative quiz. The research method used is an experiment with a pretest and posttest design, where respondents were given a pretest before the intervention with the learning media and a posttest after the intervention. Analysis of the results showed a significant increase in posttest scores compared to the pretest, indicating that gamification is effective in increasing user knowledge and awareness of cyber threats. These findings indicate that implementing game elements in learning media can be an effective and engaging strategy in building a digital security culture.
MONITORING DAN SELF-DIAGNOSTIC KUALITAS UDARA DAN AIR CONDITIONER MOBIL MENGGUNAKAN ARDUINO UNO Arjuna David Bellino Gani; Jusia Amanda Ginting
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 1 (2026): JATI Vol. 10 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i1.16799

Abstract

Kualitas udara di dalam kabin kendaraan merupakan isu kesehatan krusial yang sering terabaikan akibat kurangnya sistem perawatan penyejuk udara (Air Conditioner) secara proaktif. Akumulasi polutan dan kegagalan komponen AC dapat menurunkan konsentrasi pengemudi serta memicu gangguan pernapasan. Penelitian ini bertujuan merancang prototipe self-diagnostic AC mobil berbasis Arduino Uno untuk memonitor parameter kabin secara real-time yang mencakup suhu, kelembapan, Kualitas Udara (CO2) dan Karbon Monoksida (CO). metodologi penelitian yang digunakan adalah Prototyping dengan mengintegrasikan sensor DHT22, MQ-135, dan MQ-7. Sistem mengimplementasikan mesin inferensi Rule-Based dengan Algoritma Worst-Case Scenario yang secara cerdas memprioritaskan indikator keselamatan paling kritis sebagai dasar diagnosis akhir, memastikan peringatan bahaya gas beracun didahulukan di atas parameter kenyamanan termal. Validasi prototipe dilakukan melalui 10 studi kasus lapangan pada berbagai unit kendaraan operasional. Hasil analisis menunjukkan bahwa sistem berhasil memvalidasi baseline kendaraan sehat tanpa adanya false positive serta mampu mendeteksi secara akurat anomali ganda, seperti fenomena evaporator beku hingga kebocoran polusi internal secara bersamaan. Kesimpulannya, prototipe ini efektif dalam mentransformasi data sensor yang kompleks menjadi rekomendasi perawatan yang preventif, tegas, dan komunikatif bagi pengguna kendaraan guna memitigasi risiko kesehatan selama perjalanan
Co-Authors Adikara, Fransiskus Agustinus Frits Wijaya Agustinus Fritz Wijaya Andry, Johannes Fernandes Ardy Mathias Jadera Arjuna David Bellino Gani Christianto, Stacia Destriana Widyaningrum Ferry Alamsyah Francka Sakti Lee Giovanni Alvaro Harry Setiawan Helen Leonora Henglie, Reycardo I Gede Wisnu Satria Chandra Putra I Gusti Ngurah Suryantara I Gusti Ngurah Suryantara Irwan Sembiring Johanes Fernandes Andry Julian Saputra Lumba, Ester Marvelino, Matthew Marvelino, Matthew Michael Michael Ngurah Suryantara, I Gusti Ngurah Suryantara, I Gusti Gusti Pangestu, Matias Indra Purnomo, Yunianto Putra, Yonathan Rahadi Raphael Benedict Manuel Raphael Benedict Manuel Raphael Jameson Rico Fernando sagaino Sagaino setiady, kevin wijaya Sinata, Frans Sulaiman, Dewi Candani Suryantara, I Gusti Ngurah Suryantara, I Gusti Ngurah Teady Matius Surya Mulyana Teady Matius Surya Mulyana Teady Matius Surya Mulyana, Teady Matius Thenata, Angelina Pramana Virginia, Maria Wijaya, Agustinus Fritz