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All Journal Agrikultura Jurnal Konseling dan Pendidikan Jurnal Simetris Teika JRSI (Jurnal Rekayasa Sistem dan Industri) INFORMASI (Jurnal Informatika dan Sistem Informasi) Decode: Jurnal Pendidikan Teknologi Informasi INOTEK
Chairuddin
STMIK IM
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Pengaruh Implementasi Incident Management Berbasis ITIL v4 terhadap Pencapaian Service Level Agreement (SLA) Decka Azqia Abad; Chairuddin Chairuddin
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 17 No. 1 (2026): JURNAL SIMETRIS VOLUME 17 NO 1 TAHUN 2026
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v17i1.17005

Abstract

Penelitian ini bertujuan menganalisis pengaruh implementasi incident management terhadap pencapaian Service Level Agreement (SLA) pada layanan teknologi informasi. Studi ini dilatarbelakangi oleh masih terbatasnya kajian kuantitatif berbasis data ticketing operasional pada konteks organisasi pendidikan di Indonesia. Metode penelitian menggunakan pendekatan kuantitatif dengan desain korelasional. Data diperoleh dari 120 tiket insiden selama periode enam bulan serta kuesioner kepada 30 staf pengelola layanan. Analisis data meliputi uji validitas, reliabilitas, uji asumsi klasik, dan regresi linier sederhana. Hasil penelitian menunjukkan bahwa incident management memiliki hubungan positif dengan nilai signifikansi 0,000 (<0,05). Koefisien determinasi sebesar 0,504 menunjukkan bahwa 50,4% variasi pencapaian SLA dipengaruhi oleh kualitas incident management. Temuan ini menegaskan bahwa penguatan proses klasifikasi, prioritas, eskalasi, dan resolusi insiden merupakan faktor kunci dalam menjaga kepatuhan SLA. Penelitian ini memberikan kontribusi empiris berbasis data operasional riil bagi penguatan praktik IT Service Management pada layanan pendidikan digital.
Evaluasi Kelayakan dan Validitas Perbandingan Model Deep Learning Lintas Domain: Studi Kasus YOLO dan RNN Chairuddin; Yudhi Widya Arthana Rustam; Muhammad Haniif Muzaki
INFORMASI (Jurnal Informatika dan Sistem Informasi) Vol 18 No 1 (2026): INFORMASI (Jurnal Informatika dan Sistem Informasi)
Publisher : LPPM STMIK Indonesia Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37424/informasi.v18i1.573

Abstract

The rapid development of deep learning has encouraged the use of various neural network architectures for diverse computational tasks. However, there is a growing tendency to compare the performance of models with different characteristics and objectives without a clear methodological framework, which can lead to scientific misconceptions. This study aims to analyze the validity of a direct comparison between Recurrent Neural Networks (RNN) and You Only Look Once (YOLO). A mixed-method approach was employed, combining a conceptual analysis of fundamental differences including model objectives, data types, output spaces, and evaluation metrics with limited empirical proof within each architecture's respective task domain. The results indicate that RNN and YOLO operate in entirely different representation spaces; RNN is designed to model temporal dependencies in sequential data, whereas YOLO focuses on spatial data processing for object detection. Therefore, it is concluded that a direct comparison between these two architectures is methodologically invalid, as image data lacks meaningful temporal dimensions for RNN processing, and sequential data lacks the spatial annotations required as ground truth for YOLO. Deep learning model evaluation must always be aligned with its original task domain to avoid biased and misleading conclusions.
Co-Authors Ardi Azhar Nampira arie sairoen Decka Azqia Abad Gede Bagia Wijaya Adyana Haryoso Wicaksono HENDRA GUNAWAN B11211055 Jarot Budiasto Moch. Ali Ramdhani Muhammad Haniif Muzaki Muhammad Maksum Nana Suryana Putra, Yogi Kurnia Rifky Nurfauzi Rahman Rio Ariswendi Sevi Nurafni Yudhi Widya Arthana Rustam