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Implementasi VPS Hosting Cloudbank.id pada PT Pundi Mas Berjaya (gomarketsmy.id dan juraganit.my.id) Haeruddin Haeruddin; Husnul Khatimah
National Conference for Community Service Project (NaCosPro) Vol 5 No 1 (2023): The 5th National Conference for Community Service Project 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/nacospro.v5i1.8085

Abstract

PT Pundi Mas Berjaya merupakan perusahaan yang bergerak dibidang solusi teknologi informasi salah satu layanan yang dimiliki yaitu cloudbank.id yang menyediakan penyewaan hosting, domain, VPS, dan colocation. Setiap pelanggan yang menyewa layanan tersebut harus mengelolah layanan secara mandiri, sehingga akan mempersulit pelanggan yang tidak memiliki sumber daya manusia di bidang Teknologi Informasi. Pada kegiatan ini membuat solusi layanan yang siap pakai khususnya layanan VPS. Paket yang diberikan pada layanan VPS ini adalah paket private web hosting, dan mail server, terdapat dua layanan yang akan diimplementasiakan kepada pelanggan cloudbank.id yaitu gomarkets.my.id dan juraganit.my.id. Adapun metode yang digunakan pada kegiatan ini adalah metode Network Developmen Life Cycle (NDLC) yang terdiri dari tahapan analisa, desain, implementasi dan pemantauan.
Sistem Keamanan Work From Anywhere Menggunakan VPN Generasi Lanjut Haeruddin Haeruddin; Gautama Wijaya; Husnul Khatimah
JITU : Journal Informatic Technology And Communication Vol. 7 No. 2 (2023)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v7i2.1086

Abstract

Working remotely or what we know as Work From Anywhere is still a trend after the COVID-19 pandemic. Working from anywhere and anytime can increase productivity and reduce transportation costs, and is accompanied by fast internet support, good communication and collaboration platforms so this is very popular and in demand. When implementing WFA, it has its own challenges, namely data security. Not all organizations are supported by a reliable IT infrastructure that can protect employee data during WFA. One of the security system technologies that can be used during WFA is VPN. Currently there are many VPN protocols that can be used for WFA. However, in implementing a VPN network, there are several things that must be considered to ensure that the VPN network is successful and functional, such as security, choosing the right architecture, selecting technology and protocols, scalability, quality of service, management and monitoring, as well as security and privacy policies. ZeroTier is a next-generation VPN that is easy to configure, can support multiple devices, and uses an end-to-end connection, eliminating the need for a centralized VPN server. In implementing VPN ZeroTier the method used is the Network Development Life Cycle (NDLC). This methodology is used to plan, implement, and manage a VPN network with ZeroTier to function according to WFA needs.
SISTEM KEAMANAN RUMAH BERBASIS IOT DENGAN SMARTLOCK Haeruddin; Gautama Wijaya; Leo
JURNAL ILMIAH BETRIK Vol. 14 No. 01 APRIL (2023): JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : P3M Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/betrik.v14i01 APRIL.19

Abstract

Security systems are important because they help protect people and things from being hurt or stolen. The development of technology is getting faster and faster and helping people to meet their needs more easily. The house is one of the things that needs to be protected, because the house is a place to take shelter and store valuables and daily necessities. One of the main access to the house is the door. With the development of IoT technology, it can implement a smartlock security system. The security system uses face recognition based on Arduino Uno using face recognition as input. So that the rate of loss, exchange of goods, documents becomes less because only a few users can open them. The output generated by this system is in the form of an electric motion from the door lock and LED as information when face recognition is read. With the existence of a smartlock with face recognition technology that utilizes Arduino Uno, and can provide telegram notifications to homeowners. So that homeowners can monitor the situation of the house in real time.
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.
Phishing Website Detection Using the Decision Tree Algorithm Method Prasetyo, Stefanus Eko; Haeruddin , Haeruddin; ., Arron
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2167

Abstract

Along with the increasing number of internet users and the rapid development of technology, cyber security threats are becoming more complex, including phishing threats that often cause major losses such as loss of individual or corporate privacy. This study aims to identify phishing websites effectively through the application of machine learning algorithms. The dataset used in this study comes from the UCI learning repository developed by the University of Huddersfield. The research methodology includes the stages of problem identification, Cart algorithm collection, validation, and model evaluation. With this method, the study found that the CART algorithm was able to achieve an accuracy level of 90.5% in detecting phishing sites. These results show cyber security, especially in protecting users from phishing threats, this study is expected to contribute to improving data protection and privacy of internet users, as well as encouraging the application of machine learning technology in a more adaptive cyber security system.
Pengaruh Manajemen Bandwidth Terhadap QoS dengan Standar TIPHON Pada Alur Monitoring SNMP Alzi Alzi; Haeruddin Haeruddin
Jurnal Ilmiah Teknologi Informasi Asia Vol 17 No 1 (2023): Volume 17 Nomor 1 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v17i1.883

Abstract

Universitas Internasional Batam menyediakan fasilitas internet yang didominasi oleh pengguna jaringan wireless. Para pengguna yang terdiri dari staff, karyawan, tenaga pendidik dan mahasiswa memanfaatkan fasilitas internet di UIB, sehingga diperlukan manajemen bandwidth agar penggunaan trafik di UIB stabil, terbagi secara merata dan terjaga konektivitasnya. Metode yang digunakan adalah Network Development Life Cycle (NDLC). Penelitian ini bertujuan untuk melakukan stabilisasi trafik penggunaan bandwidth pada protokol Simple Network Management Protocol (SNMP), membagi kecepatan upload dan download secara merata dan proporsional ke masing-masing pengguna, serta meningkatkan Quality of Service melalui parameter throughput, delay, jitter, dan packet loss. Penelitian ini menghasilkan output kuantitatif dari masing-masing tujuan dan parameter QoS yang dapat digunakan sebagai referensi untuk menentukan pembagian bandwidth yang sesuai dengan kapasitas bandwidth yang dimiliki tanpa mengganggu QoS pada jaringan wireless.
Comparative Analysis of User Experience: A Study of MyPortal Universitas International Batam on Desktop and Mobile Platforms Aklani, Syaeful Anas; Haeruddin, Haeruddin; Elia, Elia
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 1: April 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i1.2580

Abstract

This research evaluates the UX of MyPortal. Myportal is an academic information system established by Universitas International Batam (UIB) on desktop and mobile platforms. This research uses the UTAUT2 model. This study examines factors that can influence user satisfaction and behavioral intentions such as Performance Expectancy, Effort Expectancy, Social Influence, and Habit. A mixed-methods approach was taken by combining quantitative surveys and qualitative interviews conducted by 349 students who actively use Myportal. The results show that the Performance Expectancy and Effort Expectancy variables can significantly increase productivity and also ease of use, but the Hedonic Motivation variable is not the main factor. This study emphasizes that technical support, habits, and environmental recommendations also have an important role in shaping user behavior. The results of this study can provide practical insights in improving MyPortal and similar systems in academic environments by focusing on ease of use, satisfaction, and accessibility.Keywords: User Experience; UTAUT2; MyPortal AbstrakPenelitian ini mengevaluasi UX dari MyPortal. MyPortal adalah sebuah sistem informasi akademik yang dibentuk oleh Universitas Internasional Batam (UIB) pada platform desktop dan mobile. Penelitian ini menggunakan model UTAUT2. Dalam penelitian ini mengkaji faktor-faktor yang dapat memengaruhi kepuasan pengguna dan niat perilaku contonya seperti Performance Expectancy, Effort Expectancy, Social Influence, dan Habit. Pendekatan dengan mixed-methods dilakukan dengan menggabungkan survei kuantitatif dan wawancara kualitatif yang dilakukan oleh 349 mahasiswa yang aktif menggunakan Myportal ini. Hasilnya menunjukkan bahwa variabel Performance Expectancy dan Effort Expectancy secara signifikan dapat meningkatkan produktivitas dan juga kemudahan penggunaan, namun variabel Hedonic Motivation bukanlah faktor utama. Penelitian ini memberikan penekanan bahwa dukungan teknis, kebiasaan, dan rekomendasi lingkungan juga memiliki peran penting dalam membentuk perilaku pengguna. Hasil dari penelitian ini dapat memberikan wawasan praktis dalam meningkatkan MyPortal dan juga sistem yang serupa di lingkungan akademik dengan memberi fokus pada kemudahan penggunaan, kepuasan, dan aksesibilitas. 
Perbandingan Support Vector Machine, Random Forest Classifier, dan K-Nearest Neighbour dalam Pendeteksian Anomali pada Jaringan DDos Haeruddin Haeruddin; Erick Erick; Heru Wijayanto Aripradono
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2025): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i1.628

Abstract

A Distributed Denial of Service (DDoS) attack poses a serious threat to network security and can disrupt online services by overwhelming the target server with excessive traffic. Effective detection of DDoS attacks requires a system capable of identifying anomalies in network traffic. In this context, Machine Learning (ML) offers an effective approach for classification and anomaly detection. However, different ML algorithms have varying strengths and weaknesses when processing large and complex network data. Therefore, this study aims to evaluate the performance of three ML algorithms: Support Vector Machine (SVM), Random Forest Classifier (RFC), and K-Nearest Neighbors (KNN) in detecting DDoS anomalies. The dataset used consists of 225,745 data points with 85 attributes that describe various characteristics of network traffic, such as destination port, flow duration, packet count, and packet size. This dataset is classified into two classes, BENIGN and DDoS, representing normal traffic and DDoS attacks, respectively. Evaluation is performed using several performance metrics, including accuracy, precision, recall, MCC (Matthews Correlation Coefficient), F-Measure, ROC Area, PRC Area, True Positive Rate (TPR), and False Positive Rate (FPR). The results show that the Random Forest Classifier (RFC) delivers the best performance with an accuracy of 99.99%, precision of 99.98%, recall of 100%, and a very low FPR of 0.02%. This is followed by the Support Vector Machine (SVM) with an accuracy of 99.91%, and the K-Nearest Neighbor (KNN) with an accuracy of 99.98%. All three algorithms demonstrate strong performance in detecting DDoS anomalies, with RFC slightly outperforming others in terms of consistency and higher classification capability. The findings of this study provide valuable insights for selecting the best algorithm to detect DDoS attacks in networks.
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.
Evaluasi Efektivitas Teknik Regularisasi Dalam Mengurangi Overfitting Pada Model CNN Prasetyo, Stefanus Eko; Haeruddin, Haeruddin; Elvis, Elvis
EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Vol 15, No 2 (2025): December
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/expert.v15i2.4676

Abstract

Penelitian ini bertujuan mengevaluasi dan membandingkan efektivitas berbagai teknik regularisasi seperti regularisasi L1 dan L2, dropout, dan augmentasi data, baik secara terpisah maupun kombinasi, dalam mengatasi overfitting pada model Convolutional Neural Network (CNN) dalam skenario dataset terbatas. Keterbatasan dataset merupakan tantangan utama yang menyebabkan model CNN cenderung mengalami overfitting, di mana performa pada data pelatihan 97.95% akurasi jauh melebihi akurasi validasi 67%. Penelitian ini menggunakan arsitektur CNN dasar yang konsisten dan dataset CIFAR-10. Hasil pengujian teknik regularisasi tunggal menunjukkan bahwa augmentasi data adalah teknik yang paling optimal pada pengujian terpisah. Model dengan augmentasi data mencapai akurasi validasi tertinggi 78.18% dan kesenjangan generalisasi terendah 2.31% di antara semua teknik yang diuji. Sementara itu, ditemukan bahwa penggunaan tingkat regularisasi yang terlalu ekstrem pada teknik regularisasi L1/L2 dapat menyebabkan underfitting karena bobot dipaksa mendekati nol  sehingga model kehilangan kapasitas belajar. Pencapaian kinerja model yang paling superior diperoleh melalui pendekatan kombinasi. Kombinasi antara augmentasi data dan regularisasi L2 menghasilkan akurasi validasi tertinggi sebesar 79.89% dengan kesenjangan generalisasi paling kecil, yaitu 0.38%. Dengan demikian, disimpulkan bahwa pendekatan kombinasi teknik regularisasi adalah strategi paling efektif untuk meningkatkan generalisasi model CNN pada lingkungan dengan dataset terbatas.