Article Per Year (5 Year)
p-Index From 2021 - 2026
6.424
P-Index
This Author published in this journals
All Journal International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vocatech : Vocational Education and Technology Journal JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Bangun Abdimas Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Jurnal Solusi Masyarakat Dikara Jurnal Pengabdian Masyarakat Teknologi Informasi (PERANTI)
Fadlisyah Fadlisyah
Universitas Malikussaleh
Religion Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

Published : 71 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : journal of informatics and telecommunication engineering

 1 
Performance Analysis of Naive Bayes Variation Method in Spice Image Classification Using Histogram of Gradient Oriented (HOG) Feature Extraction Taufik Ismail Simanjuntak; Muhathir Muhathir; Fadlisyah Fadlisyah; Ira Safira
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.7957

Abstract

Indonesia has a lot of natural wealth of spices. The diversity of spices is an inseparable aspect of Indonesian history. Spices and seasonings are biological resources that have long played an important role in human life. Indonesian spices have almost the same color and shape. The purpose of this study was to analyze the performance of the Naïve Bayes variation method in classifying spices using a Histogram Of Oriented Gradient (HOG) feature extraction. Based on 3 tests, the performance of the four Naïve Bayes variation methods carried out in this study, it can be seen that testing 5 types of spices using the Gaussian Naïve Bayes method obtained the best performance with an accuracy of 0.946, a precision of 0.95, a recall of 0.945, f1 score of 0.947, f beta score of 0.946, and Jaccard score of 0.90. Where as using the Complement Naïve Bayes method gets the lowest performance. From the results of this study it can be concluded that by utilizing HOG feature extraction and the Naïve Bayes variation method, maximum classification results are obtained in classifying spices. To obtain more accurate classification results, consider using other methods and other feature extraction
Analysis of Combined Contrast Limited Adaptive Histogram Equalization (CLAHE) and Median Filter Methods for Enhancement of CCTV Screenshot Image Quality Noor, Fredy; Muhathir, Muhathir; Fadlisyah, Fadlisyah; Syahputra, Dinur
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 2 (2025): Issues January 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i2.14016

Abstract

The quality of CCTV images often deteriorates due to poor lighting, low-quality cameras, and noise, hindering effective security analysis. This study aims to assess the combined effect of Contrast Limited Adaptive Histogram Equalization (CLAHE) and median filtering on improving the quality of CCTV screenshot images by enhancing contrast and reducing noise. Using a quantitative approach, four low-quality CCTV images were processed with CLAHE to improve contrast, followed by median filtering to reduce noise. Image quality was evaluated using two metrics: Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR). Results showed that CLAHE significantly improved image contrast, with MSE values ranging from 17.7513 to 159.092 and PSNR from 39.4809 to 47.1987. After applying the median filter, MSE values decreased to 12.1238–22.1747, and PSNR increased to 34.7288–37.3442, indicating noise reduction. The combination of CLAHE and median filter showed even better results, with MSE values ranging from 0.000993935 to 0.00508972, and PSNR ranging from 71.1032 to 78.1966. This combination significantly improved the quality of the CCTV screenshots, making them more suitable for security and forensic analysis. The findings suggest that CLAHE and median filtering can effectively enhance image clarity. Future studies should focus on optimizing these techniques for various lighting conditions and exploring other methods to address extreme noise levels in CCTV images
Pruning-Based ShuffleNetV1 Optimization for Plant Disease Image Classification and Web-Based System Prototype Implementation: Indonesia Taufik Ismail Simanjuntak; Muhathir Muhathir; Fadlisyah Fadlisyah
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 10 No. 1 (2026): Issues July 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v10i1.15374

Abstract

Diseases and pest infestations on tea plants can significantly reduce the quality and quantity of production, necessitating an early detection system based on artificial intelligence. Although deep learning architectures are capable of providing high accuracy, their large model size remains a major constraint for deployment on resource-limited devices. This study aims to compress the ShuffleNet V1 architecture using an L2-Norm based structured pruning method for the classification of six classes of tea leaf conditions utilizing a dataset from Mendeley Data. The model evaluation is carried out using the 5-Fold Cross Validation method with a fine-tuning process for 5 epochs to restore the network representation capacity after pruning. The experimental results demonstrate that the application of structured pruning successfully reduces the total parameters and computational operations significantly without sacrificing model performance. The compressed model is able to maintain an optimal accuracy reaching up to 99% across various pruning scale scenarios from 10% to 50%, while simultaneously providing a noticeable inference speedup. In the final stage, the best compressed model file is integrated into a web interface program, enabling users to perform tea leaf disease classification practically and responsively directly through a web browser. This research proves that the combination of ShuffleNet V1 and structured pruning can produce a highly lightweight yet accurate model for web implementation needs
Co-Authors Adani, Safira Agus Prayoga Alfi Fauzi Alfyansyah, Gusti Altharizka, Muhammad Aldonny Alzaky, Muammar Aris Munandar Aris Munandar Arnawan Hasibuan Aryandi Aryandi Aryandi, Aryandi Asmi, Nurul Annisa Asmirayani Asmirayani Asmirayani, Asmirayani Aulia Barus, M Farhan Azzahra, Dea Bustami Bustami Bustami Bustami Cindenia Puspasari Cindy Cika Pradita Cut Ita Erliana Cut Lika Mestika Sandy Dahlan Abdullah Dea Azzahra Defi Irwansyah Dessayani Putri Eva Darnila Fajriana Fajriana Fajriana, Fajriana Fasdarsyah Fasdarsyah Fauzi, Alfi Fuadi, Wahyu Gusti Alfyansyah Gusti Alfyansyah Hafizh Al Kautsar Aidilof Hamdhana, Defry Hamdhana, Defry Helmi Imran Intan Nuriani Ira Safira Irhami, Putri Irma Mauliza Jalaluddin Jalaluddin Jalaluddin Jalaluddin Jihan Adila Kamilaini Kamilaini Kamilaini, Kamilaini Lidya Rosnita Mahlil Fahrozi Maizuar Maizuar Mara Wahyu Alamsyah Pane Maryana Maryana Maryana Maryana Maryana Maryana, Maryana Mauliza, Irma Muammar Alzaky Muhammad Aldonny Altharizka Muhammad Fikry Muhammad Rivai Muhathir, Muhathir Muhathir, Muhathir Mukti Qamal Mukti Qamal Muqarrabin, Khalis Al Mutammimul Ula Nasriah Nasriah Nasriah Nasriah Noor, Fredy Nurdin Nurdin Nurdin Nurdin Nurdin Nurdin Nuriani, Intan Nuriani, Intan Putri, Dessayani Putri, Husna Moetia Rahmatin Nisak Reyhan Achmad Rizal Riansyah, Muhammad Risawandi, Risawandi Rizal Rizal Rizal Rizal Rizal S.Si., M.IT, Rizal Rizki Suwanda Rizky Darma Putra Rofiq Harun Rozzi Kesuma Dinata Safari, T Mirzal Safira Adani Safwandi Safwandi Safwandi Safwandi, Safwandi Said Fadlan Ansari Said Fadlan Anshari Salahuddin Salahuddin Sari, Putri Amelia Sayed Fachrurrazi Siregar, M. Ali Akbar Sujacka Retno Syahputra, Dinur SYAHRIAL SYAHRIAL Syahrial Syahrial Syahriani Putri Ayu Taufik Ismail Simanjuntak Taufik Ismail Simanjuntak Taufiq Taufiq Tri Ramdhany Uliana, Lisa Wahyu Fuadi Widari, Liz Ayu Yasir Amani Yesy Afrillia Zahrul Mubarak Zara Yunizar Zarkasyi Zarkasyi Zikratul Maulana Zuhra, Elviza