Article Per Year (5 Year)
p-Index From 2020 - 2025
2.092
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Ulul Albab: Jurnal Studi Islam MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Prosiding Seminas Competitive Advantage Prosiding SNATIKA Vol 01 (2011) Applied Information System and Management Letters in Information Technology Education (LITE) Journal of Applied Data Sciences Science in Information Technology Letters International Journal of Engineering, Science and Information Technology Bulletin of Social Informatics Theory and Application
Fachrul Kurniawan
Universitas Islam Negeri Malang
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 Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

Published : 26 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Science in Information Technology Letters

 1 
Design of an FTTH (Fiber To The Home) network for improving voice, broadband, and television services in hard-to-reach areas the Colombian case Hernandez, Leonel; Albas, Juan; Camargo, Jair; Hoz, César De La; Kurniawan, Fachrul; Pranolo, Andri
Science in Information Technology Letters Vol 3, No 2 (2022): November 2022
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v3i2.1001

Abstract

This project establishes the process of designing a fiber optic Ftth network that reaches the homes of each end customer, which allows providing voice services, broadband internet, and television, the above using GPON technology, based on the tree architecture through passive elements, where the node or central is connected to other nodes through a common link, which is shared by all the nodes (ONTs) of the network. This network will be designed in two levels, the first level that starts from the OLT to the level one splitter and the second level that begins from the level one splitter to the OTB element that the level two Splitters have. The entire design will be subject to standards that must be met to achieve the percentage of attenuation allowed. At the design level, it has two directions: one from left to right, where the nodes insert traffic, and another from right to left, where the nodes only have two functions: read or read and delete traffic. It is nothing more than the convergence of the primary communication services of today, such as fixed telephony, the internet, and television. The FTTH Network is designed for the Municipality of Usiacurí of the Department of Atlántico, using the Top-Down Design methodology, where the requirements are analyzed, the designs are developed, and the tests are carried out. The operation of this network is monitored.
Performance analysis of naive bayes in text classification of islamophobia issues Ridho, Faiz Mohammad; Wibawa, Aji Prasetya; Kurniawan, Fachrul; Badrudin, Badrudin; Ghosh, Anusua
Science in Information Technology Letters Vol 3, No 1 (2022): May 2022
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v3i1.1211

Abstract

In the aftermath of the 2013 Woolwich attack, a disturbing surge in hate crimes against the Muslim community emerged both offline and on social media platforms, prompting concerns about the widespread issue of Islamophobia. To systematically evaluate and quantify the presence of Islamophobic sentiment in online spaces, this study employed sentiment analysis, a robust method for deriving insights from textual data. Two classification models, Bernoulli Naive Bayes and Multinomial Naive Bayes, were selected to conduct a thorough analysis. Bernoulli Naive Bayes, specialized in handling binary data, was used for binary sentiment analysis, while Multinomial Naive Bayes, well-suited for data with multiple occurrences, was applied for more comprehensive analysis. The research encompassed nine meticulously designed test-train data scenarios, ranging from a 10:90 test-train data ratio to a 20:80 ratio. Surprisingly, both models exhibited a maximum accuracy rate of 68% in their respective optimal scenarios, raising intriguing questions about the potential and limitations of sentiment analysis and Naive Bayes models in the complex task of identifying and quantifying Islamophobic content on social media
Retaining humorous content from marked stand-up comedy text Supriyono, Supriyono; Wibawa, Aji Prasetya; Suyono, Suyono; Kurniawan, Fachrul; Voliansky, Roman; Cengiz, Korhan
Science in Information Technology Letters Vol 5, No 2 (2024): November 2024
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v5i2.1812

Abstract

Identifying humor in stand-up comedy texts has distinct issues due to humor's subjective and context-dependent characteristics.  This study introduces an innovative method for humor retention in stand-up comedy content by employing a pre-trained BERT model that has been fine-tuned for humor classification.  The process commences with the collection and annotation of a varied assortment of stand-up comedy writings, categorized as hilarious or non-humorous, with essential comic elements like punchlines and setups highlighted to augment the model's comprehension of humor.  The texts undergo preprocessing and tokenization to be ready for input into the BERT model. Upon refining the model using the annotated dataset, predictions regarding humor retention are generated for each text, yielding classifications and confidence scores that reflect the model's certainty in its predictions.  The criterion for prediction confidence is set to categorize texts as "retaining humor."  The results indicate that prediction confidence is a dependable metric for humor retention, with elevated confidence scores associated with enhanced accuracy in comedy classification.  Nonetheless, the analysis reveals that text length does not affect the model's confidence much, contradicting the presumption that lengthier texts are more prone to comedy.  The findings underscore the significance of environmental and linguistic elements in comedy detection, indicating opportunities for model enhancement.  Future efforts will concentrate on augmenting the dataset to encompass a broader range of comic styles and integrating more contextual variables to improve prediction accuracy, especially in intricate or ambiguous comedic situations
Co-Authors ., Rahmadwati Ady Wicaksono Aji Prasetya Wibawa Ajib Hanani Albas, Juan Alfachruddin, M. Nabil Fahd Andri Pranolo Anusua Ghosh, Anusua Artanti, Vera Ashar, Muhammad Camargo, Jair Cengiz, Korhan Fachry Khusaini Fresy Nugroho Gianto Widodo Hani Nurhayati Hoz, César De La Ikhlayel, Mohammed Kadir, Nurchaerani Karisma, Alfiana Intan Kurubacak, Gulsun Laili, Ufil Hidayatul Leonel Hernandez, Leonel Lokapitasari Belluano, Poetri Lestari M. Faisal Mubdik, M. Ahsanul Muhammad Faisal Nia, Nur Jazilah Purnomo Budi Santoso Qurrohman, Taufiq Ridho, Faiz Mohammad Siti Helmyati Sunu Jatmika, Sunu Supriyono Supriyono Suyono Suyono Syaad Patmanthara Triyo Supriyatno Voliansky, Roman W, Delliana Eka Wahyu Setiawan Yunifa Miftachul Arif