Sahuri, Afandi Chalid (2026) Pemanfaatan Dashboard Business Intelligence Untuk Continual Improvement Layanan TI Dan Prediksi Kebutuhan Tenaga Kerja Yang Efisien Berbasis Data Tiket Service Desk. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Teknologi Informasi memiliki peran penting dalam mendukung operasi perusahaan multinasional, terutama dalam organisasi yang menerapkan ITIL 4 untuk mendorong continual improvement berbasis data. Namun, proses pelaporan layanan yang masih manual, keterbatasan akses data historis, dan tidak adanya alat prediksi volume tiket menjadi tantangan dalam evaluasi performa dan perencanaan kapasitas tenaga kerja TI. Penelitian ini dilakukan dengan menganalisis tiket incident dan change request periode 2021–2025 pada lingkungan service desk berbasis ITIL.
Penelitian merancang dashboard Business Intelligence yang mengotomatisasi pelaporan, menyimpan data historis multi tahun, dan menampilkan tren SLA serta beban kerja melalui pendekatan storytelling yang lebih mudah dipahami manajemen. Selain itu, model peramalan ARIMA dikembangkan untuk memproyeksikan volume tiket sebagai dasar perencanaan tenaga kerja TI Support. Hasil evaluasi melalui survei menunjukkan bahwa dashboard secara signifikan lebih unggul daripada Topdesk pada lima indikator utama: kejelasan informasi, kemudahan penggunaan, kualitas insight, dukungan pengambilan keputusan, dan relevansi strategis.
Temuan penelitian menunjukkan bahwa dashboard berhasil mengubah data operasional menjadi informasi manajerial yang ringkas dan dapat ditindaklanjuti, sementara model ARIMA memberikan proyeksi beban kerja yang konsisten. Integrasi antara descriptive analytics pada dashboard dan predictive analytics melalui ARIMA menghasilkan kerangka pendukung keputusan yang menghubungkan performa masa lalu, kondisi saat ini, dan kebutuhan operasional masa depan. Solusi ini memperkuat penerapan continual improvement secara lebih objektif, prediktif, dan strategis.
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Information Technology plays a central role in supporting the operations of multinational companies, especially those adopting ITIL 4 to enable data driven continual improvement. However, manual reporting processes, limited access to historical performance data, and the absence of analytical tools for forecasting ticket trends pose challenges for service evaluation and IT workforce planning. This study addresses these issues by analyzing incident and change request tickets from 2021 to 2025 within an ITIL based service desk environment.
A Business Intelligence dashboard was designed to automate service reporting, store multi year historical data, and visualize SLA trends and workload distribution through a storytelling driven layout that improves managerial comprehension. In parallel, an ARIMA forecasting model was developed to project ticket volume as a quantitative baseline for planning IT Support workforce capacity. The evaluation, conducted through a structured survey, shows that the dashboard significantly outperforms the existing Topdesk system in information clarity, ease of use, insight quality, decision making support, and strategic relevance.
The findings demonstrate that the dashboard successfully transforms operational data into concise and actionable managerial insights, while the ARIMA model produces reliable projections for future workload planning. Combined, these descriptive and predictive analytics establish an integrated decision support framework that connects past performance, current conditions, and future operational needs. This solution strengthens the organization’s ability to execute continual improvement in a more objective, predictive, and strategic manner.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Dashboard BI, ITIL 4, continual improvement, service desk, peramalan kebutuhan tenaga kerja TI, performa layanan TI, ARIMA, BI dashboard, ITIL 4, continual improvement, service desk, IT Workforce Forecasting, IT Service Performance, ARIMA. |
| Subjects: | T Technology > T Technology (General) > T58.6 Management information systems |
| Divisions: | Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT) |
| Depositing User: | Afandi Chalid Sahuri |
| Date Deposited: | 31 Jan 2026 08:18 |
| Last Modified: | 31 Jan 2026 08:18 |
| URI: | http://repository.its.ac.id/id/eprint/131425 |
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