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All Journal JEMSI (Jurnal Ekonomi, Manajemen, dan Akuntansi) Journal of Intelligent Systems and Information Technology
Pradana, Ferry
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Engineering

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Memaksimalkan Dampak Media Sosial dalam Pemasaran Digital: Strategi Instagram yang Efektif untuk Merek Rahman, Fadali; Tzauri, Achmad; Khoiruddin; Pradana, Ferry
JEMSI (Jurnal Ekonomi, Manajemen, dan Akuntansi) Vol. 11 No. 3 (2025): Juni 2025
Publisher : Sekretariat Pusat Lembaga Komunitas Informasi Teknologi Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jemsi.v11i3.4233

Abstract

Instagram has emerged as a crucial tool for social media marketing, as it enables businesses to connect with their target audience in the contemporary digital landscape. This study examines the most effective strategies businesses have employed to enhance audience engagement and growth on Instagram. A qualitative technique was employed to assess the strategies implemented by 22 leading digital marketing companies in the Madura market, drawing on insights from specialists inside these agencies. The data indicate that the majority of marketing experts consider Instagram to be the essential medium for communication and marketing tactics. This underscores Instagram's efficacy in social media marketing efforts and its pivotal role in corporate marketing strategies. Nonetheless, despite the favorable rating, several experts expressed their dissatisfaction with certain characteristics, including navigation, limited visibility, high costs relative to outcomes, ad fatigue, and a narrow emphasis on the business-to-business sector. Conversely, Instagram is esteemed for its ability to engage stakeholders and achieve operational objectives. This overview underscores the importance of a planned and comprehensive approach on Instagram, focusing on innovation, audience engagement, and the quality of shared content.
Detection and Mitigation of DoS Attacks Based on Decision Tree Algorithm on Log Server Pradana, Ferry; Chusyairi, Ahmad
Journal of Intelligent Systems and Information Technology Vol. 2 No. 2 (2025): July
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/jisit.v2i2.149

Abstract

Denial of service (DoS) is an attack on a computer or server on an internet network that consumes computer resources until it can no longer perform its duties properly. The research objective is to develop a DoS attack detection and mitigation system based on the decision tree algorithm on server log analysis. The security method uses the decision tree algorithm because it has classification capabilities and produces simple classification tree decision rules. The system will monitor the spike of an IP in the server log to detect attacks and provide handling with IP Blocking techniques that are able to block the attacker's IP request for a certain duration. Python is used to study the data by generating a rule-based classifier then applied to the system using the PHP programming language and a separate PowerShell implementation so that it can run the system automatically. The database used is MySQL which consists of 2 tables, namely the request log table to store logs of requests that enter the server and ips throttle to store IPs that indicate attacks. The simulation results are the TPR accuracy value of 99.49% while the FPR error value is 0.14%, besides that the system successfully blocked 657 attacks but there were 135 incoming attacks and 17 normal requests were blocked. As a result, the system can predict attacks accurately and block the majority of incoming attacks although it still needs to be further optimised.
Co-Authors Chusyairi, Ahmad Khoiruddin Rahman, Fadali Tzauri, Achmad