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 26 Documents
Search

 1   2   3 
E-LEARNING APPLICATION AS A ISLAMIC MENTORING ON LEARNING SYSTEM OF INFORMATICS ENGINEERING STUDENTS Setiawan, Wahyu; Qurrohman, Taufiq; Kurniawan, Fachrul
Letters in Information Technology Education (LITE) Vol 2, No 2 (2019)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (346.103 KB) | DOI: 10.17977/um010v2i22019p032

Abstract

Information technology is developing very fast and is increasingly strengthened by the existence of the internet that has spread throughout the world. With the internet, the flow of information is increasingly spinning to the public and information technology applications have begun to emerge. These applications make it easy for people who use them, including e-mail, video conferences, mailing lists, chat, e-learning, and others. This paper implements an e-learning system as an Islamic mentoring in the Department of Information Engineering. The e-learning system has the potential to make the mentoring process more effective, because the interaction are wider open. Mentees can communicate with their mentors anytime via the internet. Through e-learning, mentees can continue learning even if they are not physically present at weekly mentoring meetings. Mentoring activities become very flexible because it can be adjusted to the availability of mentee time. Learning activities occur through mentee interaction with learning resources available in e-learning applications and can be accessed from the internet. This e-learning application can be used as a supporting facility of Islamic religious mentoring using conventional methods where mentoring participants meet weekly with their respective mentors. With e-learning applications on Islamic mentoring, mentees can interact with their mentors wherever and whenever they are. With the prerequisites, they are connected to the internet.
Rancang Bangun Sistem Monitoring Environment Area Tempat Tinggal Mahasiswa Berbasis Internet Of Things Karisma, Alfiana Intan; Kurniawan, Fachrul; Hanani, Ajib
MATICS Vol 11, No 2 (2019): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.448 KB) | DOI: 10.18860/mat.v11i2.8416

Abstract

Pencemaran udara muncul menjadi masalah di kota-kota besar seperti pada kota Malang. Kota Malang dikenal sebagai kota Pendidikan, banyak mahasiswa dari luar kota yang menimba ilmu di kota ini. Bertambahnya penghuni maka peningkatan aktivitas manusia akan semain banyak dan menjadi salah satu penyebab pencemaran udara. Pencemaran udara mengandung gas-gas berbahaya seperti gas buang kendaraan bermotor dan asap pabrik, sehingga akan berdampak negatif bagi kesehatan manusia. Hal tersebut dapat diminimalisir dengan dibuat sebuah sistem monitoring lingkungan area tempat tinggal mahasiswa berbasis Internet Of Things (IoT) yang berada disekitar kampus UIN Malang.Perancangan sistem ini bertujuan untuk memberi informasi tingkat kualitas udara yang berasal dari gas buang kendaraan bermotor dan aktivitas gerakan yang terekam disekitar lingkungan tempat tinggal mahasiswa dengan menggunakan teknologi IoT. Alat yang digunakan yaitu sensor MQ-7, Mikrokontroller NodeMCU dan kamera web. Sistem database menggunakan database MSQL dan informasi data berupa grafik dalam aplikasi berbasis web. Setiap sensor gas memiliki tingkat akurasi yang berbeda-beda, untuk mengukur keakuratan sensor MQ-7 menggunakan perhitungan dari rumus Mean Absolute Percentage Error (MAPE). Sensor MQ-7 memiliki nilai akurasi sebesar 58,9% dengan nilai kesalahan 41,1%.
Implementasi Algoritma Fuzzy Tipe-2 Untuk Penentuan Kriteria Kota Berdasarkan Standar Smart City Alfachruddin, M. Nabil Fahd; Kurniawan, Fachrul; Arif, Yunifa Miftachul
MATICS Vol 11, No 2 (2019): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (461.841 KB) | DOI: 10.18860/mat.v11i2.8475

Abstract

City is a role model which represents the advancement of technology and the existence of prosperity. An improvement of technology should be used as a key to manage city’s prosperity. Many standards used to measure the value of city’s prosperity. One of that standards is smart city standard. It used factors which define city’s prosperity, hence it needs a key factor that allows the standard to produce a crisp result from the available factors. There are 6 key variables of city’s prosperity of smart city standard, they are smat governance, smart mobility, smart people, smart economy, smart environment dan smart mobility. Type-2 fuzzy algorithm is used to determine city prosperity’ grade using smart city standard. The algorithm is implemented in a game of Malang city’s miniature which named after Malang Urban. In this research several in-game experiments are made to get values that meet a specified rules. The values consist 73,33% of not ready category, 6, 67% of standard category, and 20% of good smart category of all in-game attempts.
Pergantian Senjata NPC pada Game FPS Menggunakan Fuzzy Sugeno Arif, Yunifa Miftachul; Wicaksono, Ady; Kurniawan, Fachrul
Prosiding Seminas Vol 1, No 2 (2012): Seminas Competitive Advantage II
Publisher : Unipdu Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak Pengembangan kecerdasan buatan dalam game bertujuan untuk membuat aksi dan reaksi yang secara otomatis pada NPC (Non-Player Character). Penelitian ini membahas tentang bagaimana sistem perubahan senjata secara otomatis pada NPC berdasarkan perubahan kondisi lingkungan yang dihadapi. Metode yang digunakan untuk menentukan jenis senjata yang digunakan pada penelitian ini adalah fuzzy sugeno. Untuk menghasilkan output fuzzy yang bervariasi, maka digunakan variabel jarak musuh dan jumlah teman. Desain pergantian senjata yang dibuat menggunakan software Matlab selanjutnya diujicobakan dalam game First Person Shooter menggunakan Torque Game Engine. Dalam hasil ujicoba game terjadi respon pergantian senjata pada masing-masing NPC terhadap kondisi yang dihadapi sesuai dengan rule fuzzy yang sudah didesain sebelumnya.   Kata kunci: NPC, pergantian senjata, otomatis, fuzzy sugeno.
Comparing neural network with linear Regression for stock market prediction Kurniawan, Fachrul; Arif, Yunifa Miftachul; Nugroho, Fresy; Ikhlayel, Mohammed
Bulletin of Social Informatics Theory and Application Vol. 7 No. 1 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i1.621

Abstract

There are both gains and losses possible in stock market investing. Brokerage firms' stock investments carry a higher risk of loss since their stock prices are not being tracked or analyzed, which might be problematic for businesses seeking investors or individuals. Thanks to progress in information and communication technologies, investors may now easily collect and analyze stock market data to determine whether to buy or sell. Implementing machine learning algorithms in data mining to obtain information close to the truth from the desired objective will make it easier for an individual or group of investors to make stock trades. In this study, we test hypotheses on the performance of a financial services firm's stock using various machine learning and regression techniques. The relative error for the neural network method is only 0.72 percentage points, while it is 0.78 percentage points for the Linear Regression. More training cycles must be applied to the Algortima neural network to achieve more accurate results.
Optimization of k-means clustering using particle swarm optimization algorithm for human development index Laili, Ufil Hidayatul; Faisal, Muhammad; Kurniawan, Fachrul
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.678

Abstract

K-Means algorithm can be used to cluster the Human Development Index in East Java in particular for the people, the hope is that with this development all the problems that exist in the community including poverty, unemployment, school dropouts, health and social inequality can be resolved. However, this algorithm has a weakness that is sensitive to the determination of the initial centroid. Initial centroids that are determined randomly will reduce the level of accuracy, often get stuck at the local optimum, and get random solutions. Optimization algorithms such as PSO can overcome this by determining the optimal initial centroid. The quality of clusters produced by K-Means algorithm with and without PSO algorithm is measured using the average Silhouette Coefficient (SC). In this study, better accuracy was obtained between pure kmeans and PSO based kmeans where the comparison value of pure kmeans was 0.27% while PSO based kmeans obtained a value of 0.34%. The Human Development Index data set was obtained from the official website of the Central Bureau of Statistics and used as secondary data in this study, especially the East Java region. In addition to program planning in the following year, the clustering carried out from 2019 to 2022 is also an evaluation of the East Java Provincial Government's program targets that have been implemented in that year, especially related to the human quality of life development program.
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
Cognition-Based Document Matching Within the Chatbot Modeling Framework Jatmika, Sunu; Patmanthara, Syaad; Wibawa, Aji Prasetya; Kurniawan, Fachrul
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.209

Abstract

The aim of the study is to examine cognitive methods for document matching in a chatbot modeling framework by utilizing Euclidean Distance, Cosine Similarity, and BERT methodologies. Five primary indications are used to carry out evaluation in testing: document matching accuracy, document matching execution time, document search efficiency, consistency of document matching results, and the quality of the document representation in the matrix. Document matching accuracy is evaluated by precision; document matching execution time is measured from the beginning to the end of the document matching process; document search efficiency is measured through evaluation of execution time and matching accuracy; the consistency of document matching results is assessed by comparing method results when tested against the same or similar queries and the quality of document representation is assessed based on the method's ability to represent documents in a matrix or vector. The test findings offer a comprehensive understanding of how well the three approaches operate and exhibit their capacity to address the unique requirements of chatbot users. These results may contribute to the advancement of language technology applications, making it possible for chatbots to deliver pertinent information more rapidly and precisely. There are 1,755 labeled question samples in the dataset, which were split up into two sets: 60% for training (1,053 pieces), and 40% for testing (702 samples) to evaluate the model's performance. The test results show the accuracy of the three methods based on five measured evaluation indications, namely Euclidean Distance 0,45%, Cosine similarity 0,59%, and BERT 0,91%.  By comprehending the benefits and drawbacks of each approach, this research strengthens contributions to the growth of chatbot systems to better serve user demands and opens the door for the creation of more complex human-machine interaction solutions.
Analyzing Audience Sentiments in Digital Comedy: A Study of YouTube Comments Using LSTM Models Supriyono, Supriyono; Wibawa, Aji Prasetya; Suyono, Suyono; Kurniawan, Fachrul
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.393

Abstract

The main objective of this paper is to analyze audience sentiment towards stand-up comedy content on the YouTube platform, specifically comments on stand-up comedy videos from Kompas TV, using the Long Short-Term Memory (LSTM) method. This research contributes significantly to a deeper understanding of how audiences engage with humorous content through a sentiment analysis approach that uses the LSTM model, which can capture complex nuances in humorous content, such as sarcasm, irony, and cultural references. The research methodology involves crawling data from YouTube, where user comments are extracted and processed through several stages of data cleaning, such as removing duplicate content, text normalization, and irrelevant comments. Once the data is prepared, the LSTM model is trained to analyze positive, negative, and neutral sentiments with varying accuracy rates of 85% for positive sentiment, 80% for negative sentiment, and 78% for neutral sentiment. The main results show that the LSTM model successfully classifies sentiments, although it needs help handling the more ambiguous neutral sentiments. The figures and tables included in this study illustrate the relationship between the number of views, likes, and the sentiment classification of the comments. One notable finding is a strong positive correlation between the number of views and video likes. The conclusions of this study underscore the need for model improvements to handle neutral sentiment better and capture the complexity of humor content. The implications of this research are useful for content creators and digital marketers in understanding and responding to audience preferences more effectively. They also pave the way for further research in sentiment analysis on more specific content genres on digital platforms.
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