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All Journal Jurnal Sarjana Teknik Informatika Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Sains dan Teknologi Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Sistem Informasi Galuh Jurnal Komputer dan Teknologi (JUKOMTEK) Jurnal Riset Ilmiah
Yustian Servanda, Yustian
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VLAN SEBAGAI MEDIA KEAMANAN SEDERHANA UNTUK MENGISOLASI JARINGAN DI SMKN6 BALIKPAPAN MENGGUNAKAN MIKROTIK ROUTER Djumhadi, Djumhadi; Servanda, Yustian; A, Wahyu Nur; Muliansyah, Nur
SINERGI : Jurnal Riset Ilmiah Vol. 1 No. 2 (2024): SINERGI : Jurnal Riset Ilmiah, February 2024
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/gp17xr33

Abstract

Tujuan dari penelitian ini adalah untuk mengetahui bagaimana SMKN6 Balikpapan menggunakan VLAN (Virtual Local Area Network) sebagai alat untuk melindungi data rahasia dan menghentikan akses ilegal. Dengan menawarkan segmentasi infrastruktur fisik yang terisolasi dan berbeda, VLAN adalah alat yang berguna untuk mengatur dan memisahkan lalu lintas jaringan. Penelitian ini meneliti pengaturan dan penggunaan VLAN pada perangkat MikroTik RouterOS dan meneliti tingkat keamanan yang muncul dari penggunaan VLAN sebagai isolator jaringan. Diyakini bahwa penelitian ini akan mengarah pada penemuan perbaikan langsung untuk keamanan LAN dan Internet di lingkungan pendidikan. Data dikumpulkan untuk penelitian ini dengan menggunakan wawancara, uji coba instalasi VLAN, dan observasi. Analisis kuantitatif dan kualitatif dilakukan pada data yang terkumpul untuk menilai seberapa baik VLAN bekerja sebagai solusi keamanan informasi dasar. Diharapkan bahwa temuan penelitian ini akan meningkatkan pengetahuan tentang instalasi jaringan VLAN dalam kaitannya dengan keamanan jaringan sekolah. Selain itu, penelitian ini dapat memberikan saran yang berguna untuk mengkonfigurasi VLAN secara efisien dan menggunakan MikroTik RouterOS untuk membagi koneksi jaringan di SMKN6 Balikpapan. Agar lembaga pendidikan lain dapat menggunakan penelitian ini sebagai dasar untuk meningkatkan keamanan jaringan melalui penggunaan MikroTik RouterOS dan jaringan VLAN.
PERBANDINGAN ALGORITMA AI UNTUK SISTEM PENDUKUNG KEPUTUSAN PENJADWALAN BONGAKR MUAT BARANG DI PELABUHAN SEMAYANG BALIKPAPAN Janatu, Asfi; Karangan, Reygina; Servanda, Yustian; Sudinugraha, Tri
Jurnal Sistem Informasi Galuh Vol 4 No 1 (2026): Journal of Galuh Information Systems
Publisher : Fakultas Teknik Jurusan Sistem Informasi Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jsig.v4i1.5104

Abstract

Optimizing loading and unloading scheduling at Semayang Port, Balikpapan, is a complex challenge that requires an artificial intelligence approach. This study compares the effectiveness of the Genetic Algorithm (GA) and Neural Network (NN) as decision support systems in minimizing dwell time and improving operational efficiency. The research data covers the period 2020–2023, including ship arrival times, cargo types and volumes, equipment availability, and external factors such as weather and tides. GA is implemented using a chromosomal representation based on ship priority and fitness functions to optimize dwell time and dock utilization. NN employs a Long Short-Term Memory (LSTM) architecture to process port time-series data. The evaluation of three scenarios—peak, normal, and low seasons—shows that GA reduces dwell time by 22.3% compared to conventional methods, while NN predicts potential delays with an accuracy of 87.2%. GA performs best in static scheduling, while NN is effective in handling dynamic uncertainties. The hybrid GA-NN solution provides a balance between performance and complexity, with the potential to reduce operational costs by up to IDR 1.2 billion per year. This study presents a framework for the comparative evaluation of AI algorithms in port logistics and offers practical recommendations for optimizing operations at Semayang Port.
Analysis of user experience with TikTok Shop features among Generation Z in Balikpapan Safitri, Sanrina Aprilia; Ar Rifana, Nabila Auliya; Servanda, Yustian; Fatma, Febrina
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.2015

Abstract

This study was conducted to determine the usability level of TikTok Shop features among Generation Z in Balikpapan. The main focus of this study was how easy these features were to use for the user experience when shopping on the TikTok Shop application. The method used was a quantitative approach using the System Usability Scale (SUS) instrument. Data was collected by distributing questionnaires to 27 respondents who were Generation Z aged 13 to 28 years old residing in Balikpapan. The SUS questionnaire consisted of 10 questions using a Likert scale of 1 to 5, which were then processed to obtain a usability score. The results of data processing showed that the total SUS score obtained was 2,230 with an average value of 82.59. This value indicates that the TikTok Shop feature has a high level of usability. In general, respondents felt that the interface was easy to understand, supported shopping activities, and was in line with Generation Z's social media usage habits. Based on these results, the researcher concluded that the TikTok Shop feature was well-designed and provided a positive experience for Generation Z in Balikpapan.
Co-Authors A, Wahyu Nur Adinata, Ivan Agus Wijayanto Ahmad Ramadhan Allo, Jemita Lisu Anastasya Safitri, Adinda Ar Rifana, Nabila Auliya Bin Idris , Nasruddin Christian Tjiang, Bryan Djumhadi Djumhadi Djumhadi, Djumhadi Fatma, Febrina Hardiansyah, Syavina Tiaranandra Indah Rizki, Elvina Janatu, Asfi Julianto, Mustofa Karangan, Reygina Muliansyah, Nur Pratama, Nazril ardi Syah Putra Purnama, Wahyu Aji Rizky, Alif Safitri, Sanrina Aprilia Sudinugraha, Tri Syahrial, Muhammad Athoriq Nadzar Zainal Arifin