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All Journal International Journal of Electrical and Computer Engineering JSM (Jurnal SIFO Mikroskil) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics SAMUDERA Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Jurnal Teknologi Informasi dan Komunikasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Indonesian Journal of Artificial Intelligence and Data Mining JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika Jurnal Inotera Data Science: Journal of Computing and Applied Informatics Jurnal Mantik Journal of Information Systems and Informatics The Indonesian Journal of Computer Science
Erna Budhiarti Nababan
Universitas Sumatera Utara
Aerospace Engineering Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences

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Analysis Of Mobile Banking User Activity Based On Transaction Time Clustering Using Self-Organizing Map (SOM) Method Syah Putra Lubis, Fachrurrozi; Amalia; Erna Budhiarti Nababan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.15503

Abstract

The rapid growth of mobile banking services in Indonesia demands a deeper understanding of user behavior, especially in terms of time and transaction patterns. However, the challenge is how to effectively cluster users based on their time habits in making transactions, so that service strategies can be tailored accordingly. To address this issue, this study applies the Self-Organizing Maps (SOM) method to cluster users based on transaction time features, such as the number of transactions in the morning, afternoon, evening, night, and the division between weekdays and weekends. The dataset used includes 87,361 mobile banking users throughout 2023. The results showed that the SOM method was able to form nine different user behavior clusters, with the largest cluster being Early User (Weekday) consisting of 32,324 users (37.0%). Overall, the Early User (Weekday) segment covers about 60.3% of the user population. Meanwhile, there are also minority segments such as Night Owl (Weekday) (5.9%) and Early User (Weekend) (2.7%) that show unique behavior patterns. The model performance evaluation resulted in a Quantization Error (QE) value of 0.339 and Topographic Error (TE) of 0.066, both on validation data and test data, indicating that the clustering results are quite accurate and the data mapping topology is well maintained. This research contributes to the understanding of mobile banking user behavior segmentation and can be used as a basis for a more adaptive and personalized time-based service strategy.
Reducing Semantic Distortion of Multiword Expressions for Topic Modeling with Latent Dirichlet Allocation Sitopu, Widya Astuti; Nababan, Erna Budhiarti; Budiman, Mohammad Andri
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1266

Abstract

The Makan Bergizi Gratis (MBG) is one of the Indonesian government’s priority initiatives that has received significant coverage in online media. To understand the main themes within these narratives, this study applies topic modeling using Latent Dirichlet Allocation (LDA). However, the results of topic modeling are highly influenced by the preprocessing stage, particularly in handling multiword expressions (MWEs) such as named entities, collocations, and compound words. This study compares two preprocessing approaches: basic and extended, with the latter involving the masking of MWEs. Experimental results show that the extended preprocessing model achieved the highest coherence score of 0.5149 at K=22K = 22K=22, with four other scores also exceeding 0.496, whereas the basic preprocessing model only reached a maximum of 0.3932 at K=10K = 10K=10. Furthermore, cosine similarity scores between topics in the extended model were lower (maximum 0.7406) than in the basic model (maximum 0.8244), indicating that the topics produced were more diverse and less overlapping. These findings highlight the importance of preprocessing strategies that preserve phrase-level meaning to reduce semantic distortion and improve topic coherence and representation-particularly in analyzing media discourse on public policy programs such as MBG.
Implementation Of Face-To-Face Online Learning System Based On Audio Video, Presentation And Chat Using The Moodle E-Learning Platform Nababan, Erna Budhiarti; Opim Salim Sitompul; Dedy Arisandi; Seniman
ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2021): ABDIMAS TALENTA : Jurnal Pengabdian Kepada Masyarakat
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (504.999 KB) | DOI: 10.32734/abdimastalenta.v6i1.5348

Abstract

Currently, the implementation of teaching and learning at SMP Negeri 1 Binjai Kwala Begumit was done in the classroom alternately. However, with the current condition of pandemic covid-19, the learning process no longer carried out fully in schools. The school has not been using information technology in the form of e-learning applications in the teaching and learning process. The school has difficulty in recording the existing teaching and learning process: assignments, exams, assessments, and other activities. Therefore the use of e-learning applications is now very much needed. With existing school facilities, such as internet facilities and the ICT teachers, training in developing and implementing e-learning for teaching staff become the best alternative so that learning process can be done properly.
Pengamanan File Teks Menggunakan Algoritma RSA – LUC dan Algoritma Zig-Zag dalam Hybrid Crypto Sistem Lubis, Rahmi Suliani; Tulus, Tulus; Nababan, Erna Budhiarti
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 6, No 2 (2022): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v6i2.4717

Abstract

Kriptografi adalah ilmu yang berdasarkan pada teknik matematika untuk berurusan dengan keamanan informasi seperti kerahasiaan, keutuhan data dan otentifikasi entitas. Hybrid crypto metode untuk mengunci plainteks dengan algoritma simetris dan menggunakan algoritma asimetris untuk mengunci algoritma simetris. Tujuan dari penelitian ini adalah kriptografi masih memiliki kelemahan oleh karena itu peneliti menggabungkan zig-zag dan RSA dengan kunci LUC dalam mengenkripsi pesan. Dalam penelitian digunakan pembangkit kunci pada algoritma LUC. hybrid kriptosistem merupaka metode untuk mengunci algortima plainteks dengan algoritma simetris dan asimetris digunakan untuk mengamankan algoritma simetris. Algoritma digunakan untuk mengenkripsi plainteks sedangkan algoritma RSA-LUC untuk mengenkripsi kunci zig-zag. Hasil dari penelitian ini adalah Semakin panjang jumlah karakter maka semakin lama proses yang dibutuhkan untuk proses enkripsi pada file teks. Dan semakin besar ukuran file, maka semakin besar ukuran ciphertext yang dihasilkan.
Pengamanan Citra Menggunakan Kombinasi Algoritma Kriptografi Hill Cipher dan Teknik Transposisi Segitiga Simamora, Windi Saputri; Efendi, Syahril; Nababan, Erna Budhiarti
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 6, No 2 (2022): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v6i2.4713

Abstract

Cara untuk mengamankan citra dapat dilakukan dengan kriptografi. Penelitian pada algoritma kriptografi sudah cukup banyak berkembang. Beberapa penelitian menyebutkan bahwa menggabungkan dua algoritma kriptografi dapat lebih meningkatkan keamanan dari citra dibandingkan dengan hanya satu algoritma. Penelitian ini melakukan enkripsi menggunakan kombinasi dua algoritma yaitu teknik transposisi segitiga dan Hill Cipher. Proses penggabungan dua algoritma dilakukan dengan terlebih dahulu mengenkripsi menggunakan teknik transposisi segitiga dan kemudian dilanjutkan dengan Hill Cipher. Begitu juga dengan proses dekripsi yang dilakukan secara kebalikannya. Pada penelitian ini menghasilkan performa yang lebih baik dibandingkan dengan menggunakan satu metode yang dapat dilihat pada nilai rata-rata MSE yang besar yaitu 10878,992 dan rata-rata PSNR yang kecil yaitu 0,781. Hal tersebut menandakan dengan menggabungkan dua algoritma dapat membuat pesan menjadi lebih aman. Metode dalam penelitian ini juga berhasil mengembalikan citra dangan baik tanpa adanya penambahan maupun pengurangan yang dapat dilihat dari hasil MSE dan PSNR yaitu 0 dan ∞.
Deep Support Vector Data Description for Anomaly Detection in Credit Insurance Claim Processes Ramadhana, Sari; Nababan, Erna Budhiarti; Sitompul, Opim Salim
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 3 (2025): November 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i3.38134

Abstract

This study evaluates Deep Support Vector Data Description (Deep-SVDD) for anomaly detection in credit insurance claim submissions processed through host-to-host systems. The model addresses irregularities such as duplicate claims, inconsistent values, and delayed reporting by learning normal claim behavior in a latent space and applying calibrated thresholds. Using a dataset of 5,000 claims with mixed-type variables, Deep-SVDD achieved strong performance on the validation set, with high precision, recall, and ROC-AUC. Confusion matrix and Recall@K analyses confirmed low false alarms and effective anomaly ranking, capturing a substantial portion of anomalies among top-ranked claims. These results demonstrate Deep-SVDD’s potential as a scalable and efficient early detection layer, improving transparency and reliability in credit insurance claim verification.
Finding Random Integer Ideal Flow Network Signature Algorithms Teknomo, Kardi; Nababan, Erna Budhiarti; Bisono, Indriati Njoto; Lim, Resmana
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 27 No. 1 (2025): June 2025
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.27.1.105-120

Abstract

We propose a Random Integer Ideal Flow Network (IFN) Signature Algorithm that generates integral flow assignments in strongly connected directed graphs under uncertainty. Existing models often fail to incorporate the inherent randomness and integer constraints present in systems like social networks. Unlike traditional approaches that enforce integrality through large scaling factors, our method distributes integer coefficients across multiple canonical cycles, ensuring precise balance where the sum of inflows exactly equals the sum of outflows at each node. We introduce two pseudocode algorithms that uphold flow conservation while maintaining network irreducibility, ensuring autonomy through strong connectivity. Theoretical contributions include the decomposition of IFNs into canonical cycles and the construction of network signatures, string-based representations that allow efficient performance evaluation through direct string manipulation. These signatures enable quick validation of key network properties such as total flow, balanced link flows, and structural irreducibility. To demonstrate practical applications, we apply our algorithm to modeling family power dynamics, illustrating how IFN can create minimal yet resilient networks that balance autonomy with accountability. This framework lays the foundation for future advancements in predictive modeling and network optimization. To ensure reproducibility, we provide an open-source Python implementation on GitHub.
Co-Authors ,, Amrullah Abda Abda Abdul Muis Afriandy Sharif Amalia Dedy Arisandi Efendi, Syahril Eka Irawan Elviawaty Muisa Zamzami Ermawati Ermawati Ferawaty - Goklas Tomu Simbolon Harahap, Lailan Hardisal, Hardisal Hartono Hartono Hayanti, Septi Herman Mawengkang Herman Saputra Indriati Njoto Bisono, Indriati Njoto Jonas Franky R Panggabean Jonatan Sianturi Julpan Julpan Junidar, Junidar, Kardi Teknomo Kelvin Onggrono Lailan Harahap Lismardiana Lismardiana Lubis, Rahmi Suliani M. Zarlis Mahyuddin K. M Nasution Mardiansyah, Heru Mohammad Andri Budiman Muhammad Ardiansyah Sembiring Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis, Muhammad Opim Salim Sitompul Opim Salim Sitompul Opim Salim Sitompul Pasaribu, Roni Fredy Halomoan Poltak Sihombing Pratiwi, Andini Rahmad Syah Ramadhana, Sari Rambe, Basyit Mubarroq Resmana Lim Riki Andri Yusda Rimbun Siringoringo, Rimbun Romi Fadillah Rahmat Rosmelda Ginting Rudy Chandra Saib Suwilo Sawaluddin Nasution Seniman Sianturi, Jonatan Simamora, Windi Saputri Sinuraya, Junus Sitopu, Widya Astuti Sutarman Sutarman Sutarman Syah Putra Lubis, Fachrurrozi Taufiqurrahman Taufiqurrahman Tulus Tulus Tulus Tulus Yuni Cancer