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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Penelitian Sistem Informasi
Akhmal Angga Syahputra
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Analisis Kualitas Layanan Menggunakan Framework ITIL V3 Domain Service Operation Website Akademik Muhammad Asfari Alkaromi; Akhmal Angga Syahputra; Muhammad Asnafi Alkaromi; Ahnaf Vanning Al Haq; Ito Setiawan
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 2 No. 4 (2024): November : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v2i4.2668

Abstract

The advancement of information technology has transformed the management of academic systems in universities, necessitating effective and efficient IT management to support operational and administrative processes. Universitas Amikom Purwokerto uses a web-based academic system to integrate academic and administrative services. However, issues such as server connection failures often disrupt operations. Based on an ITIL V3 analysis, the system is at Maturity Level 3 (*Defined*) in problem management, with recommendations to improve real-time monitoring and process flexibility. Implementing these recommendations is expected to enhance service quality and user experience. This study aims to analyze the service quality of Universitas Amikom Purwokerto’s academic system within the service operation domain, particularly in the problem management subdomain. According to the ITIL V3 framework, the system's maturity is at the *Defined* level (Level 3), indicating that problem-handling processes are well-documented but limited in flexibility. These findings highlight the need for improvements in real-time monitoring, predictive analysis, and user feedback to better meet dynamic needs. Such recommendations are expected to improve operational effectiveness and overall user experience.
Implementasi Data Mining untuk Clustering Lowongan Pekerjaan Menggunakan Metode Algoritma K-Means Rifqi Mubarok; Akhmal Angga Syahputra; Abdillah Teguh Permana; Lifa Sholiah; Tarwoto
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3438

Abstract

The development of digital technology has transformed the way businesses recruit employees online. This study aims to create an interactive dashboard that facilitates job seekers and companies, using clustering methods with the K-Means algorithm to analyze job posting data in the United States. The data from the Kaggle LinkedIn Job Postings 2023 dataset, consisting of 33,000 records, is processed using the CRISP-DM phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The clustering analysis results in four job categories: low-mid-level general jobs, high-level executive jobs, time-based jobs, and mid-high-level professional jobs. Model evaluation shows good clustering quality with a Silhouette Coefficient of 0.78 and a Davies-Bouldin Index of 0.55. The developed dashboard helps companies plan recruitment and job seekers find positions matching their skills and salary expectations. The practical contribution of this study is modernizing the recruitment process, assisting companies and recruitment agencies in screening candidates more efficiently, and improving job matching through deeper data analysis.
Co-Authors Abdillah Teguh Permana Ahnaf Vanning Al Haq Ito Setiawan Lifa Sholiah Muhammad Asfari Alkaromi Muhammad Asnafi Alkaromi Rifqi Mubarok Tarwoto