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Journal : Journal Of Artificial Intelligence And Software Engineering

Implementation SEO and SEM to Enhance Brand Awareness and Consumer Loyalty Rozaliana, Rozaliana; Azzahari, Muhammad; Khaldun, Ibnu
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6646

Abstract

The development of digital technology has changed the way micro, small, and medium enterprises (MSMEs) market their products and build relationships with consumers. Digital marketing is one of the main strategies in increasing brand awareness and consumer loyalty. This study aims to analyze the effectiveness of digital marketing strategies in increasing brand awareness and consumer loyalty. The research methods used are literature studies and surveys of consumers who actively use digital platforms to interact with brands. The results of the study show that effective digital marketing strategies, such as the use of social media, content-based marketing, and service personalization, can increase brand awareness and build strong loyalty in consumers. By utilizing Search Engine Optimization (SEO),    Search Engine Marketing (SEM), and influencer marketing techniques, MSMEs can reach target markets more widely and effectively. These findings underline the importance of the role of digital marketing in the era of digital transformation that continues to grow. Therefore, an integrated and sustainable digital marketing strategy is needed to increase the company's competitiveness and maintain customer loyalty.
Server Worker Power Optimization with Virtual Machine Live Migration Technique Using Fuzzy Mamdani Azzahari, Muhammad; Khaldun, Ibnu; Mahmud, Mahmud; Rozaliana, Rozaliana
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.7310

Abstract

This study focuses on power optimization of worker servers by applying live migration techniques for virtual machines (VMs) using the Mamdani fuzzy logic method. The main goal is to automatically move VMs to servers with lower CPU usage, thereby reducing overall power consumption. The system was built using the Proxmox VE platform and simulated for 30 minutes under two conditions: without and with Mamdani fuzzy logic. The results show that the use of fuzzy Mamdani reduces power consumption by 0.26 watts compared to the non-migration system. Although the savings may seem minor, the method is effective when applied at a larger data center scale. This technique enables efficient workload distribution by migrating VMs, allowing idle servers to reduce energy usage. In conclusion, Mamdani fuzzy logic offers a practical solution for energy-saving in cloud computing environments without compromising system performance.
Analisis Konsumsi Daya Server Worker Dengan VM Live Migration Berbasis Proxmox Azzahari, Muhammad; Khaldun, Ibnu
Journal of Artificial Intelligence and Software Engineering Vol 4, No 1 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i1.5403

Abstract

Live migration merupakan suatu teknik migrasi yang memindahkan server virtual machine (VM) ke server worker yang rendah CPU usage nya. Teknik migrasi ini dilakukan dengan memanfaatkan metode fuzzy mamdani sebagai pengambil keputusan berdasarkan hasil monitoring CPU usage pada masing-masing server worker. Pada setiap server worker akan ditentukan nilai batas (Threshold) yang berfungsi sebagai acuan kapan server vm akan bermigrasi ke server worker yang mengalami rendah CPU usage. Hasil pengujian yang dilakukan selama 30 menit menunjukkan bahwa teknik live migration VM dapat mengurangi konsumsi daya sebesar 0,26 Watt dibandingkan dengan tanpa teknik tersebut. Dengan demikian optimasi daya bisa terjadi jika proses migrasi server VM terlaksana dari server worker host asal ke server worker host tujuan sehingga server worker asal nantinya akan mengalami penurunan konsumsi daya atau mengalami dengan serendah-rendahnya konsumsi daya (idle).AbstractLive migration is a migration technique that moves a virtual machine (VM) server to a server worker with low CPU usage. This migration technique is carried out by utilizing the fuzzy mamdani method as a decision maker based on the results of monitoring CPU usage on each worker server. On each worker server, a threshold value will be determined which serves as a reference for when the VM server will migrate to a worker server that experiences low CPU usage. The results of tests carried out for 30 minutes show that the VM live migration technique can reduce power consumption by 0.26 Watts compared to without this technique. Thus, power optimization can occur if the VM server migration process is carried out from the original worker host server to the destination worker host server so that the original worker server will experience a decrease in power consumption or experience the lowest possible power consumption (idle).
Implementation Of Dama-Dmbok-Based Data Governance To Optimize Organizational Decision Making Khaldun, Ibnu; Khaidar, Al
Journal of Artificial Intelligence and Software Engineering Vol 5, No 4 (2025): Desember (On Progress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i4.8502

Abstract

Di era digital, pengelolaan data menjadi aspek penting bagi perusahaan penyedia layanan internet (PIJI) dalam menjaga kualitas dan keamanan informasi. Penelitian ini bertujuan untuk merancang model tata kelola data berbasis kerangka kerja DAMA-DMBOK (Data Management Body of Knowledge) yang disesuaikan dengan kebutuhan operasional PT XYZ Cabang Medan, serta melakukan pengukuran tingkat kematangannya untuk menilai efektivitas penerapan model tersebut. Pendekatan penelitian menggunakan metode deskriptif kuantitatif, dengan penyebaran kuesioner kepada pihak yang terlibat dalam pengelolaan data keuangan dan operasional perusahaan. Hasil analisis menunjukkan bahwa secara keseluruhan tata kelola data berada pada tingkat kematangan Managed (Level 4), yang mengindikasikan bahwa proses pengelolaan data telah terstandarisasi dan terdokumentasi dengan baik. Area Data Governance dan Data Security memiliki tingkat kematangan tinggi dengan nilai masing-masing 4,8 dan 4,6, sedangkan Data Quality masih rendah dengan nilai 2,5. Model tata kelola data yang dirancang melalui penelitian ini dapat menjadi acuan bagi PT XYZ dalam meningkatkan integritas, kualitas, dan keamanan data, serta sebagai referensi penerapan DAMA-DMBOK pada industri penyedia layanan internet.
Public Sentiment Analysis on the November 2025 Flood Disaster in Aceh Using Natural Language Processing and Lexicon-Based Approach Erwanda, Ade Putra; Khaidar, Al; Asrianda, Asrianda; Fikry, Muhammad; Khaldun, Ibnu
Journal of Artificial Intelligence and Software Engineering Vol 5, No 4 (2025): Desember (On Progress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i4.8481

Abstract

Bencana banjir yang melanda Provinsi Aceh pada November 2025 merupakan salah satu bencana hidrometeorologi besar yang berdampak luas terhadap kehidupan masyarakat. Banjir terjadi di 16 kabupaten/kota dan mengakibatkan hampir 120 ribu jiwa terdampak, puluhan ribu warga mengungsi, serta kerusakan signifikan pada permukiman dan infrastruktur. Peristiwa ini memicu respons publik yang masif di media sosial, khususnya Instagram. Penelitian ini bertujuan untuk menganalisis sentimen respons masyarakat terhadap bencana tersebut menggunakan pendekatan Natural Language Processing (NLP) berbasis lexicon. Data diperoleh melalui proses data crawling terhadap 2.790 komentar Instagram, yang selanjutnya diproses melalui tahapan text cleaning, case folding, tokenization, stopword removal, dan stemming. Hasil analisis menunjukkan dominasi sentimen positif sebesar 62,51%, diikuti sentimen netral 24,98% dan negatif 12,51%. Temuan ini menunjukkan adanya apresiasi, harapan, serta kritik masyarakat terhadap penanganan bencana, dan dapat menjadi bahan evaluasi bagi pemangku kebijakan dalam meningkatkan strategi penanganan dan komunikasi bencana berbasis data.