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INDONESIA
Teknomatika: Jurnal Informatika dan Komputer
Published by Universitas Jenderal Achmad Yani Yogyakarta
ISSN : 19797656     EISSN : 30310865     DOI : 10.30989
Core Subject : Science,
Computer Science & IT
Teknomatika: Jurnal Informatika dan Komputer ISSN: 3031-0865 (Online), 1979-7656 (Print) is a free and open-access journal published by Fakultas Teknik dan Teknologi Informasi Universitas Jenderal Achmad Yani Yogyakarta, Indonesia. Teknomatika publishes scientific articles from scholars and experts worldwide related to the computer science, informatics, computer systems and information systems. This journal accommodates articles covering: Mathematics and Statistics Algorithms and Programming Intelligent System Artificial Intelligence Software Engineering Computer Architecture Distributed System Cyber Security Electronics and Embedded Systems Data and Information Management Information Systems Enterprise System All published articles will have a Digital Object Identifier (DOI). The Journal publication frequency is twice a year (sixth monthly: Maret and September).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6 Documents
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Search results for , issue "Vol 15 No 1 (2022): TEKNOMATIKA" : 6 Documents clear
Analisis Keamanan Data Pribadi pada Shopee Paylater Menggunakan Metode Hybrid Nanang Widayanto; Alfirna Rizqi Lahitani; Netania Indi Kusumaningtyas
Jurnal Teknomatika Vol 15 No 1 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i1.1097

Abstract

The low level of awareness and understanding of Shopee online shopping application users regarding the security of user data causes the level of digital crime to increase, as evidenced by the many crime cases that occur, namely the misuse of users' personal data by utilizing OTP codes as a verification process. This can be a loophole for digital crimes that are certainly very detrimental to users. Perform personal data security analysis on Shopee PayLater using the Hybrid method. The method used is the hybrid method, which is a method of combining basic digital forensic techniques with re-engineering techniques. This method can be used to analyze applications that involve user personal data, tools used such as MobSF, Virustotal to view application activity, and apk-deguard for apk reengineering. Personal data security research on Shopee PayLater was carried out using the help of Virustotal and MobSF tools found vulnerabilities caused by users. The results of the personal data security analysis carried out on the Android-based Shopee application show that there are several vulnerabilities in the user's personal data vulnerability, namely in the application licensing section.
IMPLEMENTASI PI-HOLE UNTUK MEMBANGUN SISTEM PERTAHANAN JARINGAN DARI SERANGAN MALVERTISING Nindya Dwi Anggana; Dedi Hariyadi; Rama Sahtyawan; Alfun Roehatul Jannah
Jurnal Teknomatika Vol 15 No 1 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i1.1104

Abstract

The Internet has revolutionized human activities in the digital era, providing new avenues for innovation and connectivity. Online advertising, a significant aspect of this digital landscape, enables advertisers to reach diverse audiences. However, this convenience has also attracted cybercriminals who exploit online advertisements to deploy malicious ads, commonly known as malvertising. This study focuses on implementing Pi-Hole, a network defense system, to combat web-based malvertising attacks and reduce associated risks. Utilizing a Raspberry Pi 3 model B+ device, the Pi-Hole system is deployed within the DMZ network at FTTI Universitas Jenderal Achmad Yani Yogyakarta. By capturing query logs, Pi-Hole effectively blocks malicious ads by employing an adlist. The research was conducted over a 14-day period, from July 26 to August 8, 2022. The results demonstrate the efficacy of the Pi-Hole defense system, with a remarkable 22.7% of the total captured queries, amounting to 895,077 queries, being successfully blocked. Additionally, testing from the client's perspective confirmed the system's ability to prevent ads from appearing on websites and mobile applications. The implementation of Pi-Hole on the FTTI network at Jenderal Achmad Yani Yogyakarta University provides a robust defense against malvertising attacks. By blocking malicious ads, Pi-Hole safeguards users' browsing experiences and reduces the risk of potential harm from online advertisements. This research contributes to the growing body of knowledge on network security and offers practical insights for organizations and individuals seeking effective measures to counter web-based malvertising attacks.
Analisis Forensik Digital Pada Komentar Youtube Live Menggunakan Sentiment Analysis Uning Kristiana; Alfirna Rizqi Lahitani; Chanief Budi Setiawan; Nafisa Alfi Sa'diya
Jurnal Teknomatika Vol 15 No 1 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i1.1115

Abstract

The development of increasingly sophisticated technology can have a positive influence on various aspects of our daily lives. From the survey results of the Indonesian Internet Services Association (APJII) in the second quarter of 2019-2020, it shows that Internet users of the operator spend more time watching online videos. Youtube video content watching is open to the public and all ages can freely watch it. However, the content and comments are not necessarily suitable for audiences of all ages to read. Of course, Youtube video content can also affect behavior, especially minors.The purpose of this research is to conduct digital forensic analysis on Youtube Live Comments using sentiment analysis.The research method used applies the NIST SP 800-86 method, namely Collection, Examination, Analysis, and Reporting. Sentiment analysis resulted in 0.01 in the comments on the two videos tested, namely the PUBG and Free Fire video games. Sentiment analysis resulted in 0.01 in the comments on the two videos tested, namely the PUBG and Free Fire video games.
Analisis Kesadaran Cyber Security di Kalangan Pengguna Layanan Keuangan Digital Indonesia Maulida Farahanita; Chanief Budi Setiawan; Rama Sahtyawan; Nurul Fatimah
Jurnal Teknomatika Vol 15 No 1 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i1.1119

Abstract

The rapid development of information technology has led most people to choose to use digital banking and financial services to carry out various financial transactions. The most common crimes that occur are in the banking industry, including hacking (hacking of digital services), skimming (copying data information from digital service users), defacing (replacing or modifying digital service pages), phishing (deception of digital service users), BEC (business email compromise), and social engineering (social engineering to digital service users). To measure the level of cyber security awareness among users of digital financial services in Indonesia using the AHP method. This research is a quantitative study by distributing online questionnaires, then analyzed using the AHP method to find out which criteria have the highest or lowest scores. The largest weight of these criteria is knowledge of 0.5009, then sequentially is attitude of 0.3307, and behavior of 0.173. Digital financial service users already have insight or knowledge regarding how to maintain the security of their personal data, but it is still lacking in its application, so it is necessary to conduct in-depth re-education regarding the big risks given by carelessly maintaining privacy data. On the Attitude criteria; users still save PIN/passwords in smartphone notes, install applications outside the Play Store or App Store, rarely update the operating system on their smartphones, and leave their smartphones to other people or public places. On the Behavior criteria; users still use the same PIN/password on different accounts.
Analisis Quality of Service (QOS) pada Akses Game Online Menggunakan Standar Tiphon Bambang Nakulo; Chanief Budi Setiawan; Rama Sahtyawan; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 15 No 1 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i1.1130

Abstract

The quality of internet service plays a crucial role in online gaming experiences. This study focuses on assessing the quality of internet services provided by 6 cellular cards in Indonesia using the TIPHON standard. The objective is to determine the suitability of these services for online gaming on a website. Data packets generated during online gaming sessions were captured using the Wireshark application in three different locations. The captured data was processed using the TIPHON standard formula to evaluate the quality of internet service provided by the 6 cellular cards. The analysis of the captured data revealed that three cellular cards, namely Telkomsel, XL, and Tri, demonstrated good performance in terms of providing a quality online gaming experience. The results were consistent across the three tested locations. Based on the TIPHON standard, the evaluation of 6 cellular cards in three different locations indicated that three of them (Telkomsel, XL, and Tri) offer suitable internet service for playing online games on the website.
ANALISIS SENTIMEN ULASAN BANTUAN SOSIAL (BANSOS) DI TWITTER MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) GILANG BRILIAN RACHMAT; Puji Winar Cahyo; Fajar Syahruddin
Jurnal Teknomatika Vol 15 No 1 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i1.1137

Abstract

Background: Social assistance (bansos) is assistance provided to the community/social institutions in a non-continuous and selective manner in the form of money/goods to the community, aiming to improve the welfare of the community. The purpose of this study is to create an analytical model using the Support Vector Machine method which is used to perform Sentiment analysis regarding social assistance (bansos) on Twitter. Research Method: using the Support Vector Machine (svm) method. Based on the classification results, a lot of negative tweet data and many netizens regret that social assistance is still not evenly distributed and there is still a lot of social assistance corruption by the government itself which is marked by a lot of negative sentiments rather than positive sentiments. Conclusion: This study succeeded in testing the accuracy using the Support Vector Machine (SVM) method with a value of 84% on training data and 97% on testing data.

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