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All Journal Technomedia Journal Jiko (Jurnal Informatika dan komputer) Jurnal Teknik Informatika (JUTIF) Malcom: Indonesian Journal of Machine Learning and Computer Science
Raka Yusuf, Raka
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Computer Science & IT Languange, Linguistic, Communication & Media

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Perbandingan Algoritma DBSCAN dan K-MEANS dalam Segmentasi Pelanggan Pengguna Transportasi Publik Transjakarta Menggunakan Metode RFM: Comparison of the DBSCAN and K-MEANS Algorithms in Segmenting Customers Using Public Transportation of Transjakarta Using the RFM Method Saputra, Aditiya; Yusuf, Raka
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 4 (2024): MALCOM October 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i4.1516

Abstract

Transportasi umum sangat penting dalam kehidupan individu di suatu daerah. Transjakarta, diperkenalkan pada tahun 2004, adalah sistem Bus Rapid Transit (BRT) terpanjang di dunia dengan 251,2 kilometer jalur, 14 jalur, dan 287 halte di seluruh Jakarta. Sistem ini melayani masyarakat dengan 1.347 unit transportasi. Seiring peningkatan jumlah pengguna, masalah seperti kerumunan di halte dan antrian panjang muncul, sehingga diperlukan segmentasi pelanggan yang cermat.Penelitian ini menggunakan metode Recency, Frequency, Monetary (RFM) untuk analisis segmentasi pelanggan Transjakarta dengan algoritma DBSCAN dan K-Means. Hasil menunjukkan DBSCAN membutuhkan waktu pemrosesan lebih lama untuk klaster tertentu, sedangkan K-Means lebih cepat di klaster tertentu. K-Means unggul dengan Silhouette Score 0.714917 dan Davies-Bouldin Index 0.365776, dibandingkan DBSCAN dengan Silhouette Score 0.699971 dan Davies-Bouldin Index 0.390784. K-Means lebih efektif dalam membedakan pelanggan berdasarkan frekuensi dan nilai moneter, sementara DBSCAN dapat mengidentifikasi outlier dengan interaksi dan nilai moneter tinggi. Secara keseluruhan, K-Means menunjukkan performa yang lebih baik dalam segmentasi pelanggan Transjakarta. Berdasarkan hasil ini, K-Means lebih cocok digunakan untuk segmentasi pelanggan Transjakarta, yang dapat membantu pihak berwenang merancang strategi layanan yang lebih efisien dan meningkatkan kepuasan pelanggan.
Implementasi Metode QINQ Pada Jaringan Metro Ethernet Untuk Memaksimalkan Penggunaan VLAN Menggunakan Teknologi GPON Studi Kasus : PT. Telkom Indonesia Prayoga Pangestu; Yusuf, Raka
Technomedia Journal Vol 6 No 1 Agustus (2021): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.431 KB) | DOI: 10.33050/tmj.v6i1.1551

Abstract

VLAN is part of network system that serves as the divider, The use of vlan very helpful in mapping the router or switch on the device. The use of vlan become a sure thing in building architecture of effective and flexible. Not except one of a company service providers like PT. Telkom Indonesia. The use of vlan according to the standard of limited to specification 802.1q with the limited to 1 – 4096 VLAN ID can be used. This will make a problem when found vlan id who have been used for a network will not get used again to another network. The problem also can be found on PT Telkom Indonesia who uses GPON (Gigabit Passive Optical Network) to meet the needs of their customers. Based on the problems encountered , researchers want to use of vlan qinq on technology GPON (Gigabit Passive Optical Network) To solve the problem limited vlan id that might be encountered when meet the needs of from customers PT. Telkom Indonesia .
ENHANCED NETWORK SECURITY USING ZERO TRUST IN SMART HOME NETWORKS AGAINST MAN-IN-THE-MIDDLE ATTACKS SINGH, BEWIT RAJ; Yusuf, Raka
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 2 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i2.10329

Abstract

The rapid adoption of Internet of Things (IoT) devices in Smart Home environments has increased network vulnerability to internal threats, such as Man-in-the-Middle (MitM) attacks, which traditional security models often fail to address. This study aims to design, simulate, and comparatively analyze the effectiveness of a Zero Trust architecture against a traditional security model in protecting a smart home network from MitM attacks. A comparative experiment was conducted in a GNS3 simulation environment featuring two topologies: a conventional flat network using HTTP and a Zero Trust network implementing microsegmentation via VLANs, Access Control Lists (ACLs), and encrypted HTTPS communication. MitM attacks, specifically ARP Spoofing and packet sniffing, were launched against both scenarios. The results unequivocally show that the traditional network was highly vulnerable, allowing attackers to successfully intercept user credentials in plaintext. In contrast, the Zero Trust architecture completely thwarted the attack; its layered defenses blocked unauthorized traffic and encrypted sensitive data, preventing any credential theft. This research concludes that the Zero Trust model is a significantly more effective and robust security strategy for IoT-based smart homes, providing superior protection against internal threats with minimal performance trade-offs compared to conventional approaches
Comparison of Port Scanning, Vulnerability Scanning, and Penetration Testing Combinations for Network Vulnerability Detection in GNS3 Testbed Rusdianto, Rusdianto; Yusuf, Raka
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4917

Abstract

Network security faces significant challenges due to the increasing number and complexity of system vulnerabilities. This study aims to develop and evaluate a full combination method (ABC) integrating port scanning (Nmap), vulnerability scanning (OpenVAS), and penetration testing (Metasploit), and compare it with partial combinations (AB, BC, AC) for more effective vulnerability detection. Using a quantitative experimental approach within a controlled GNS3 TestBed, three key indicators were analyzed: number of vulnerabilities detected, detection time, and exploit validity. Experimental results show that the ABC method detected 62 potential vulnerabilities, including 11 high and medium severity CVEs, matching the AB method but significantly outperforming AC, which detected none. In terms of detection time, the ABC method achieved a balanced performance at 91 minutes, which is 31.5% faster than AB (133 minutes), while maintaining full exploit validation. Notably, the ABC method successfully validated 100% of critical vulnerabilities using Metasploit, confirming the practical applicability and reliability of the integrated approach compared to dual combinations. Overall, the findings demonstrate that the full combination method (ABC) offers superior accuracy and comprehensiveness in detecting and validating network vulnerabilities. This research contributes to cybersecurity practices by proposing an integrated detection workflow that effectively balances speed and depth of analysis, setting a practical benchmark for vulnerability detection systems applicable to both simulated and real-world network environments.
Co-Authors Prayoga Pangestu Rusdianto Rusdianto, Rusdianto Saputra, Aditiya SINGH, BEWIT RAJ