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All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control ILKOM Jurnal Ilmiah INTEK: Informatika dan Teknologi Informasi Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Applied Technology and Computing Science Journal Infotekmesin Jurnal Sistem informasi dan informatika (SIMIKA) Journal of Innovation Information Technology and Application (JINITA) Madani : Indonesian Journal of Civil Society Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Media Aplikom Jurnal Pengabdian Teknologi Tepat Guna Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Muhammad Nur Faiz
Politeknik Negeri Cilacap
Religion Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Public Health Social Sciences Other

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Metode Weighted Product Pada Pendukung Keputusan Pemilihan Pengurus Himpunan Mahasiswa Hani Hidayati; Ratih Hafsarah Maharrani; Lutfi Syafirullah; Muhammad Nur Faiz
Journal of Innovation Information Technology and Application (JINITA) Vol 4 No 1 (2022): JINITA, June 2022
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (442.549 KB) | DOI: 10.35970/jinita.v4i1.1426

Abstract

The Department of Student Association (HMJ) is a student organization at the department level in a university which is an extracurricular activity. HMTI or Informatics Engineering Student Association is one of the HMJ at the Politeknik Negeri Cilacap (PNC). HMTI certainly has a vision and mission, therefore, in order to realize the vision and mission, candidates for management are needed according to the expected criteria. The criteria for determining the decision making of HMTI management include organizational experience, psychology, public speaking, self[1]confidence, having a warning letter (SP) and IPK. This problem was overcome by making a Decision Support System for the recruitment of HMTI management using the weighted product method. This system makes it easy for HMTI coaches and administrators to determine the candidate for the board. Decision Support System (DSS) is an application of information systems aimed at assisting leaders in the decision-making process. This study resulted in recommendations for prospective HMTI PNC administrators who through optimization of the weighted product method with various criteria used had the highest value, so that they became a reference for HMTI supervisors and administrators to choose candidates for the following year
Rekayasa Fitur Berbasis Machine Learning untuk Mendeteksi Serangan DDoS Muhammad Nur Faiz; Oman Somantri; Arif Wirawan Muhammad
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 3: Agustus 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v11i3.3423

Abstract

Distributed network attacks, also known as distributed denial of service (DDoS) are a major threat and problem for internet security. DDoS is an attack on a network aiming to disable server resources. These attacks increase every year with the current state of the COVID-19 pandemic. One of countermeasures to minimize the DDoS impact is the intrusion detection system (IDS) command. IDS techniques are currently still employing traditional methods so that they have many limitations compared to techniques and tools used by attackers because traditional IDS methods only use signature-based detection or anomaly-based detection models which cause many errors. Network data packet traffic has a complex nature, both in terms of sizes and sources. This research utilized the ability of artificial neural network (ANN) to detect normal attacks or DDoS. A classification technique with ANN method is a solution to these issues. Based on the shortcomings of the traditional IDS, this study aims to detect DDoS attacks using feeder machine learning-based feature engineering techniques to improve the IDS development. Using the UNSW-NB15 dataset with the ANN method, this study also aims to analyze and obtain training function combinations and the best hidden layer architectures of ANNs to solve the detection and classification problems of DDoS packets in computer networks. As a result, the training function combinations and hidden layer architectures of the ANN can provide a high level of DDoS recognition accuracy. Based on experiments conducted with three schemes and an ANN schema architecture technique with eight features as input, the highest accuracy was 98.22%. Feature selection plays an essential role in detection result accuracies and machine learning performances in classification problems.
Metode Pengembangan Perangkat Lunak MDLC Pada Rancang Bangun Media Pembelajaran Planet Berbasis Teknologi Augmented Reality Abdul Rohman Supriyono; Anggita Dwi Fatimah; Isa Bahroni; Linda Perdana Wanti; Muhammad Nur Faiz
Infotekmesin Vol 14 No 1 (2023): Infotekmesin: Januari, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i1.1689

Abstract

Along with the development of smartphones, Augmented Reality technology has begun to be used as a medium of interaction, although it has not been properly implemented and applied as a supporting medium. The use of still image objects in textbooks can make students tend to be more passive and less interactive because media images are unable to provide a reciprocal response. In science subjects, there is solar system material regarding planet recognition. Props are needed as learning media because the object of observation from the planet is too large. Several props are used as imitations of the planets, such as the use of drawing paper, audio, and video. The purpose of this research is to make a breakthrough in the use of Augmented Reality technology to support media for understanding planet recognition material by creating digital teaching aids that can be installed on smartphone devices. The MDLC method is an alternative method for developing multimedia applications that are easy to understand. The results of the test show that the application can function as expected, where each planetary marker that has been made can be recognized properly according to the intended planetary object.
Comparison Analysis of Cloning-Hashing Applications for Digital Evidence Security Muhammad Nur Faiz
Infotekmesin Vol 14 No 2 (2023): Infotekmesin: Juli, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i2.1844

Abstract

The development of the Internet has resulted in an increasing variety of cyber crimes. Cybercrime is closely related to digital evidence, so cybercriminals tend to delete, hide, and format all collected data to eliminate traces of digital evidence. This digital evidence is very vital in proving at trial, so it is necessary to develop applications to secure digital evidence. This study aims to compare the results of cloning and hashing in securing digital evidence and evaluate the performance of a digital forensic application developed under the name Clon-Hash Application v1 compared to applications commonly used by investigators including Autopsy, FTK Imager, md5.exe in terms of its function, the result, CPU usage. The results of the research conducted show that the cloning process is perfectly successful, as evidenced by the hash value results which are the same as paid applications and there are even several other applications that have not been able to display the hash value. Hash values in the Clon-Hash v1 application also vary from MD5, SHA1, and SHA256 which do not exist in other applications. Applications developed are better in terms of function, results, and CPU usage.
A Classification Data Packets Using the Threshold Method for Detection of DDoS Sukma Aji; Davito Rasendriya Rizqullah Putra; Imam Riadi; Abdul Fadlil; Muhammad Nur Faiz; Arif Wirawan Muhammad; Santi Purwaningrum; Laura Sari
Journal of Innovation Information Technology and Application (JINITA) Vol 6 No 1 (2024): JINITA, June 2024
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v6i1.2224

Abstract

Computer communication is done by first synchronizing one computer with another computer. This synchronization contains Data Packages which can be detrimental if done continuously, it will be categorized as an attack. This type of attack, when performed against a target by many computers, is called a distributed denial of service (DDoS) attack. Technology and the Internet are growing rapidly, so many DDoS attack applications result in these attacks still being a serious threat. This research aims to apply the Threshold method in detecting DDoS attacks. The Threshold method is used to process numeric attributes so obtained from the logfile in a computer network so that data packages can be classified into 2, namely normal access and attack access. Classification results using the Threshold method after going through the fitting process, namely detecting 8 IP Addresses as computer network users and 6 IP addresses as perpetrators of DDoS attacks with optimal accuracy.
Website Security Analysis Using Vulnerability Assessment Method : Case Study: Universitas Internasional Batam Haeruddin; Gautama Wijaya; Hendra Winata; Sukma Aji; Muhammad Nur Faiz
Journal of Innovation Information Technology and Application (JINITA) Vol 6 No 2 (2024): JINITA, December 2024
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v6i2.2476

Abstract

In today’s digital era, ensuring website security is crucial, especially in the education sector which is frequently targeted by cyber attacks. This research aims to test security of the Universitas Internasional Batam (UIB) website using OWASP ZAP and Nessus. The method will be used in this research was vulnerability assessment. It will involve gathering information with the tools such as, Nmap, whois and nslookup. OWASP ZAP detected 11 vulnerabilities, categorized into 6 medium level and 5 low level, including Content Security Policies (CSP) and anti-clickjacking headers. Otherwise, Nessus only detected one medium level vulnerability, the absence of HTTP Strict Transport Security (HSTS). The difference in detection results from the tools that OWASP ZAP is better at finding web application weakness that are consistent with the OWASP Top Ten 2021, while Nessus specifically targets server and network configuration. For educational institutions, these results emphasize the importance of conducting regular vulnerability assessment to protect sensitive data. Recommended action include implementing CSP to prevent Cross-site scripting (XSS) and other injection attacks, enforcing HSTS to secure communication, and its recommend to updating software to mitigate the unknown vulnerabilities. By adopting these measures, institutions can reduce their exposure to cyber attacks, its also can maintain user trust, and strengthen overall security. This research provides a pratical framework for stregthening the security of educational websites against evolving threats. These findings highlight that the importance of using multiple tools can provide a more comprehensive view of security gaps.
Pengembangan Desa Digital Dengan Penerapan Sistem Informasi Kearsipan Untuk Meningkatkan Pelayanan Publik Pada Pemerintah Desa Banjarwaru Kecamatan Nusawungu Kabupaten Cilacap Santi Purwaningrum; Ratih Hafsarah Maharrani; Agus Susanto; Prih Diantono Abda'u; Muhammad Nur Faiz; Oman Somantri; Ari Kristiningsih; Khoeruddin Wittriansyah
JURNAL PENGABDIAN TEKNOLOGI TEPAT GUNA Vol 6 No 1 (2025): Teknologi Tepat Guna (TTG)
Publisher : Universitas Sahid Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47942/jpttg.v6i1.1925

Abstract

Pelayanan Publik yang efektif dan efisien menjadi salah satu tolak ukur masyarakat dalam menilai kinerja penemrintah daerah secara kasat mata. Pelayanan publik seperti pembuatan surat dan pencarian data arsip sangat berpengaruh terhadap kualitas layanan pada Kantor Desa Banjarwaru. Proses pengarsipan surat dan administrasi lainnya di Desa Banjarwaru saat ini belum terdigitalisasi dan terdokumensi dengan baik. Hal tersebut sering membuat terjadinya kesalahan dalam penyimpanan data surat masuk dan membutuhkan ruang yang cukup luas untuk menyimpannya, selain itu juga seringnya terjadi kesalahan dalam penulisan nomor surat keluar karena pencarian nomor surat terakhir masih dicari manual pada buku besar. Guna untuk mewujudkan visi dan misi Desa Banjarwaru, maka sangat diperlukan Penerapan Sistem Informasi Kearsipan untuk pengembangan Desa Digital. Sistem informasi arsip persuratan mempunyai tujuan mengubah metode penyimpanan surat atau administrasi lainnya dengan proses pengarsapan secara digital sehingga mengurangi penggunaan kertas dan lebih efektif dan akurat.
Sentiment Analysis Using Stacking Ensemble After the 2024 Indonesian Election Results Pakpahan, Andy Victor; Fahmi Reza Ferdiansyah; Robby Gustian; Muhammad Nur Faiz; Sukma Aji
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 1 (2025): JINITA, June 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v7i1.2724

Abstract

Sentiment analysis is a text processing technique aimed at identifying opinions and emotions within a sentence. Machine learning is commonly applied in this area, with algorithms such as Naïve Bayes, Support Vector Machine (SVM), and Random Forest being frequently used. However, achieving optimal accuracy remains a challenge, particularly when dealing with unstructured text data, such as content from social media platforms. This research seeks to improve sentiment analysis performance by implementing a stacking ensemble learning approach, which combines the predictive strengths of several base models. The base models selected for this study are Naïve Bayes, SVM, and Random Forest, while Random Forest also serves as the meta-model to generate final predictions. The study focuses on sentiment analysis in a specific context—public opinion following the announcement of the Indonesian presidential election results in 2024. The dataset comprises 6,737 tweets collected from the X platform using web scraping techniques in 2024. Results show that individual models achieved varying levels of accuracy: Naïve Bayes at 66.84%, SVM at 77.74%, and Random Forest at 74.78%. In contrast, the stacking ensemble model achieved a significantly higher accuracy of 81.53%. This improvement highlights the effectiveness of ensemble learning in integrating different algorithmic perspectives to enhance predictive performance. By leveraging the complementary strengths of each base model, stacking not only boosts accuracy but also increases model robustness, making it highly suitable for real-world sentiment analysis applications that involve noisy and informal textual data from social media.
Co-Authors Abdul Fadlil Abdul Rohman Supriyono Achmad Zaki Yamani Agus Susanto Agus Susanto Andy Victor Pakpahan Anggita Dwi Fatimah Annas Setiawan Prabowo Anton Yudhana Ari Kristiningsih Arif Wirawan Muhammad Davito Rasendriya Rizqullah Putra Dwi Cita Septia Candra Erna Alimudin Fahmi Reza Ferdiansyah Ganjar Ndaru Ikhtiagung Gautama Wijaya Haeruddin Hani Hidayati Hani Hidayati Hendra Winata Hety Dwi Astuti Ifda Nurul Azroha Imam Riadi Isa Bahroni, Isa Khoeruddin Wittriansyah Laura Sari Linda Perdana Wanti Linda Perdana Wanti Lutfi Syafirullah Lutfi Syarifullah Nur Chasanah Nur Wachid Adi Prasetya Nur Wahyu Rahadi Oman Somantri Prih Diantono Abda`u Ratih Hafsarah Maharrani Robby Gustian Rusydi Umar Santi Purwaningrum Santi Purwaningrum Seppy Ayu Rachmawati Sidiq, Muhammad Fajar Sukma Aji Ummi Athiyah Wahyu Adi Prabowo