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All Journal Journal of Electrical Engineering and Computer (JEECOM) Prosiding University Research Colloquium Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Kusrini, K
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Environmental Science Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology

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Evaluasi Tata Kelola dan Manajemen Risiko Unit Teknologi Informasi dan Pangkalan Data pada Perguruan Tinggi Keagamaan Islam Negeri XYZ dengan Menggunakan Framework COBIT 2019 Sulistiyono, Agus; Kusrini, K
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.512

Abstract

The Information Technology and Data Base Unit (UTIPD) is one of the units at the XYZ State Islamic Religious College (PTKIN) which is tasked with managing and developing information system management, network and application maintenance, managing databases, and developing other information technology (IT). This research aims to evaluate governance and risk management at UTIPD at PTKIN XYZ. As a higher education institution that continues to develop, PTKIN XYZ relies heavily on information technology to support its operations, administration and academic activities. However, with the increasing complexity of information systems and associated risks, an in-depth evaluation of how IT governance and risk management is implemented is needed. The COBIT 2019 framework, which is an international standard framework for IT governance and management, is used in this research to assess IT governance and risk management capabilities at UTIPD. The primary focus of this evaluation is to determine the extent to which current IT governance practices meet expected standards, as well as to identify areas requiring improvement. This research includes an analysis of COBIT 2019 domains that are relevant to IT governance and risk management. The results of this research show that the APO07 domain and APO12 domain processes only obtained capability level 2 and obtained a gap value (GAP) of 1 each. In addition, this research also presents recommendations for improving IT governance and risk management at PTKIN XYZ, with the aim of Finally, to ensure that this university can utilize information technology optimally, reduce risks, and support the achievement of its strategic goals. It is hoped that the findings from this research can become a reference for PTKIN XYZ and other higher education institutions in strengthening IT governance and risk management.
Classification Of Mustard Leaf Diseases Using Convolutional Neural Network Architecture Hafidurrohman, M.; Kusrini, K
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10779

Abstract

Diseases in mustard leaves can reduce productivity if not detected early. This study aims to develop and evaluate a disease classification system for mustard leaves using Convolutional Neural Network (CNN) architectures, specifically Xception and VGG19, while comparing their performance in terms of accuracy and computational efficiency. The mustard leaf image dataset undergoes preprocessing before being used for model training and testing. Experimental results show that Xception achieves the highest validation accuracy of 99% with better loss stability compared to VGG19, which attains 94.50% accuracy but exhibits greater fluctuation. In terms of time efficiency, VGG19 reaches optimal accuracy faster and completes the training process in 42 seconds, whereas Xception requires more epochs and a training time of 50 seconds. Therefore, Xception is recommended for classification tasks that demand high accuracy and stability, while VGG19 is more suitable for rapid detection with a slight trade-off in accuracy stability.
Implementasi TOPSIS Pada Sistem Informasi Pembagian Jam Mengajar Guru SMK PGRI 1 Ngawi Sumafta, Ikhwan Baidlowi; Kusrini, K; Sunyoto, Andi
Prosiding University Research Colloquium Proceeding of The 7th University Research Colloquium 2018: Bidang Teknik dan Rekayasa
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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Abstract

Penjadwalan merupakan salah satu hal penting dalam proses kegiatanbelajar mengajar, karena semua kegiatan guru dan murid bergantungpada jadwal yang ada. Salah satu langkah penting dalam pembuatanjadwal pelajaran adalah pembagian jam mengajar. SMK PGRI 1Ngawi adalah salah satu sekolah swasta terbaik di kabupaten ngawimemiliki 2303 siswa pada tahun pelajaran 2017/2018 dan dibagimenjadi 64 rombongan belajar serta memiliki jumlah guru sebanyak103 guru terbagi dalam dua kelompok guru yaitu 40 guru matapelajaran produktif, 63 guru mata pelajaran normatif dan adaptif.SMK PGRI 1 Ngawi juga memiliki dua gedung pembelajaran danmasing-masing memiliki dua lantai. TOPSIS merupakan salah satumetode pengambilan keputusan multikriteria yang memiliki beberapakelebihan, diantaranya konsepnya yang sederhana dan mudahdipahami, efisiensi komputasi, dan memiliki kemampuan untukmengukur kinerja relatif dari alternatif-alternatif keputusan dalambentuk matematis yang sederhana. Fokus penelitian yang dilakukanadalah bagaimana menentukan pembagian jam mengajar gurunormatif dan adaptif berdasarkan usia guru, status guru, dan lamaguru mengajar di SMK PGRI 1 Ngawi dengan menggunakan metodeTOPSIS. Penelitian menghasilkan jumlah jam mengajar danrombongan belajar untuk masing-masing guru sesuai dengan kriteria.
Co-Authors Adhani, Muhammad Azmi Agastya, I Made Artha AGUS SULISTIYONO Andi Sunyoto Anggraini, Resti Kusuma Hafidurrohman, M. Hanif Al Fatta Mohammad Haris Muzakki, Mohammad Haris Sukaria, Petra Nugra Sumafta, Ikhwan Baidlowi