Article Per Year (5 Year)
p-Index From 2021 - 2026
3.734
P-Index
This Author published in this journals
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

Published : 37 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search
Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

 1 
Sistem Pendeteksian Manusia untuk Keamanan Ruangan menggunakan Viola – Jones Sianturi, Jonatan; Rahmat, Romi Fadillah; Nababan, Erna Budhiarti
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 1, No 2 (2018): Edisi Januari
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (656.955 KB) | DOI: 10.31289/jite.v1i2.1424

Abstract

Aspek keamanan sangat dibutuhkan dalam berbagai kehidupan saat ini seperti keamanan rumah, gedung, atau ruangan yang memiliki nilai penting bagi pemilik. Keamanan dapat dikerjakan oleh tenaga manusia tetapi cara ini kurang efisien karena menghabiskan banyak resources seperti uang, waktu, tenaga dan juga sangat rentan terhadap kelalaian manusia (human error). Oleh karena itu diperlukan suatu pendetekatan untuk dapat melakukan keamanan tersebut.Salah satu pendekatan yang dapat dilakukan adalah dengan melakukan pendeteksian objek manusia melalui kamera yang terhubung dengan komputer.Dalam penelitian ini digunakan Viola-Jones untuk mendeteksi objek manusia dalam citra berdasarkan fitur. Citra yang diinput dari webcam dengan fungsi capture dalam library OpenCV diubah menjadi citra abu-abu setelah mengalami proses scaling, dilanjutkan ekualisasi histogram, perhitungan fitur dengan citra integral, dan pendeteksian objek dengan cascade of classifier. Pada penelitian ini ditunjukkan bahwa metode yang diajukan mampu melakukan pendeteksian objek dengan hasil akurasi mencapai 86,88% . Kata Kunci : viola-jones, pendeteksian manusia, keamanan ruangan, cascade of classifier, opencv.
Sistem Pendeteksian Manusia untuk Keamanan Ruangan menggunakan Viola – Jones Jonatan Sianturi; Romi Fadillah Rahmat; Erna Budhiarti Nababan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 1, No 2 (2018): Edisi Januari
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v1i2.1424

Abstract

Aspek keamanan sangat dibutuhkan dalam berbagai kehidupan saat ini seperti keamanan rumah, gedung, atau ruangan yang memiliki nilai penting bagi pemilik. Keamanan dapat dikerjakan oleh tenaga manusia tetapi cara ini kurang efisien karena menghabiskan banyak resources seperti uang, waktu, tenaga dan juga sangat rentan terhadap kelalaian manusia (human error). Oleh karena itu diperlukan suatu pendetekatan untuk dapat melakukan keamanan tersebut.Salah satu pendekatan yang dapat dilakukan adalah dengan melakukan pendeteksian objek manusia melalui kamera yang terhubung dengan komputer.Dalam penelitian ini digunakan Viola-Jones untuk mendeteksi objek manusia dalam citra berdasarkan fitur. Citra yang diinput dari webcam dengan fungsi capture dalam library OpenCV diubah menjadi citra abu-abu setelah mengalami proses scaling, dilanjutkan ekualisasi histogram, perhitungan fitur dengan citra integral, dan pendeteksian objek dengan cascade of classifier. Pada penelitian ini ditunjukkan bahwa metode yang diajukan mampu melakukan pendeteksian objek dengan hasil akurasi mencapai 86,88% . Kata Kunci : viola-jones, pendeteksian manusia, keamanan ruangan, cascade of classifier, opencv.
Analysis Of Variation In The Number Of MFCC Features In Contrast To LSTM In The Classification Of English Accent Sounds Afriandy Sharif; Opim Salim Sitompul; Erna Budhiarti Nababan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 6 No. 2 (2023): Issues January 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i2.8566

Abstract

Various studies have been carried out to classify English accents using traditional classifiers and modern classifiers. In general, research on voice classification and voice recognition that has been done previously uses the MFCC method as voice feature extraction. The stages in this study began with importing datasets, data preprocessing of datasets, then performing MFCC feature extraction, conducting model training, testing model accuracy and displaying a confusion matrix on model accuracy. After that, an analysis of the classification has been carried out. The overall results of the 10 tests on the test set show the highest accuracy value for feature 17 value of 64.96% in the test results obtained some important information, including; The test results on the MFCC coefficient values of twelve to twenty show overfitting. This is shown in the model training process which repeatedly produces high accuracy but produces low accuracy in the classification testing process. The feature assignment on MFCC shows that the higher the feature value assignment on MFCC causes a very large sound feature dimension. With the large number of features obtained, the MFCC method has a weakness in determining the number of features.
Performance Analysis Of The Combination Of Blum Blum Shub And Rc5 Algorithm In Message Security Rambe, Basyit Mubarroq; Nababan, Erna Budhiarti; Nasution, Mahyuddin KM
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 2 (2024): Vol. 7 No. 2 (2024): Issues January 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i2.10937

Abstract

This research aims to enhance message security in the RC5 algorithm by integrating it with the Blum Blum Shub (BBS) algorithm. The rapid growth in data and information exchange, driven by advancements in information and communication technology, demands robust security against attacks such as eavesdropping, interruption, and data modification. Cryptography, particularly with symmetric and asymmetric keys, becomes a solution to maintain message confidentiality. The RC (Rivest Cipher) algorithm, specifically RC5, has become a popular choice in network applications due to its speed and variable key length complexity. This study attempts to improve the quality of encryption keys by integrating the Blum Blum Shub (BBS) method, a mathematical random number generator algorithm. RC5 and BBS are used together to secure messages, producing ciphertext that is difficult to predict and smaller in file size compared to the standard RC5 method. The test results show that the processing speed is independent of the number of characters in the plaintext, while the encrypted file size resulting from the RC5-BBS combination is more efficient than using the default RC5. In conclusion, integrating BBS into RC5 can enhance the security and efficiency of the encryption algorithm, with the potential for widespread application in cryptography-based data security
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.
Co-Authors ,, Amrullah Abdul Muis Afriandy Sharif Amalia Dedy Arisandi Edi Kurniawan 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