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All Journal CESS (Journal of Computer Engineering, System and Science) JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Information Technology and Cyber Security
Syauqi, A’la
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Library & Information Science

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Pengembangan Website E-Kinerja Menggunakan Metode Agile Development: Studi Kasus Dinas Perhubungan Kota Malang Rahmania, Fadilla; Syauqi, A’la
CESS (Journal of Computer Engineering, System and Science) Vol 9, No 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.51173

Abstract

Penelitian ini bertujuan mengembangkan website E-Kinerja Dinas Perhubungan Kota Malang dengan metode Agile, terutama kerangka kerja Scrum. Dengan membagi proyek menjadi empat sprint berdurasi 21 hari, pendekatan ini menghasilkan produk yang responsif terhadap kebutuhan pengguna dengan cepat. Dengan sprint mencakup increment produk yang dapat diuji secara berkala, memungkinkan pemangku kepentingan memberikan umpan balik sepanjang proses pengembangan. Keberhasilan ini menunjukkan bahwa pengembangan E-Kinerja Dinas Perhubungan Kota Malang perlu didukung oleh peran kolaborasi serta komunikasi yang efektif antara tim pengembangan dan pemangku kepentingan. Metode Scrum yang meliputi Sprint Planning dan Daily Standup berperan penting dalam menjaga transparansi dan pemahaman. Implikasi penelitian ini menunjukkan bahwa penerapan metode Agile, khususnya Scrum, secara signifikan meningkatkan efisiensi pengembangan perangkat lunak dalam upaya meningkatkan manajemen kinerja pegawai di sektor publik.
Clustering of Post-Disaster Building Damage Levels Using Discrete Wavelet Transform and Principal Component Analysis Purnamasari, Putri; Imamudin, Mochamad; Zaman, Syahiduz; Syauqi, A’la; Almais, Agung Teguh Wibowo
Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.12270

Abstract

Damage assessment of buildings after natural disasters is generally performed manually by a team of experts at the disaster site, making it prone to human error and resulting in low accuracy in classifying the level of damage. This research aims to develop a more efficient and accurate method in post-disaster building damage assessment by integrating Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) techniques. The main contribution of this research is the use of DWT as well as the application of this method on more than one image to improve the accuracy of damage level classification. A total of nine unlabelled images of post-disaster buildings were used in this study, which were obtained from the Regional Disaster Management Agency or Badan Penanggulangan Bencana Daerah (BPBD) of Malang City, Indonesia. The methods applied include data pre-processing, DWT decomposition for image analysis to identify features, and clustering using PCA to cluster the level of building damage into light, medium, and heavy categories, which are then evaluated based on accuracy. The results showed that the method yielded 100% accuracy with validation results from surveyors, as evidenced through 2D and 3D visualisations based on principal components (PC1-PC3). These findings confirm that the integration of DWT and PCA can be an effective alternative in improving the accuracy of post-disaster building damage assessment, as well as supporting decision-making in rehabilitation and reconstruction after natural disasters.
Spatial Decision Support System to Determine the Feasibility of Evacuation Posts in Natural Disasters Alviola, Nuril Afni; Almais, Agung Teguh Wibowo; Syauqi, A’la; Chamidy, Totok; A Basid, Puspa Miladin Nuraida Safitri; Anisa, Anisa; Wardana, M. Dafa
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 3 (2025): September 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.3.307-318

Abstract

This study aimed to improve the accuracy of determining the feasibility of evacuation posts after natural disasters using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) within a Spatial Decision Support System (SDSS). A dataset of 50 evacuation posts from the 2021 Mount Semeru eruption was analyzed. The Rank Order Centroid (ROC) method was applied for criteria weighting, and TOPSIS was used to process the data. Results showed 72% accuracy, confirming that TOPSIS is a passable method for assessing post-feasibility based on accessibility, sanitation, and refugee facilities. Although the focus is on evaluating post-disaster evacuation posts, the system can be adapted for use in various other types of disasters. However, it is still dependent on historical data and lacks real-time adaptability. Future research can integrate Artificial Intelligence (AI) and Machine Learning (ML) with real-time data to improve decision-making in disaster management.
Co-Authors A Basid, Puspa Miladin Nuraida Safitri Agung Teguh Wibowo Almais Alviola, Nuril Afni Anisa Anisa Mochamad Imamudin Putri Purnamasari Rahmania, Fadilla Syahiduz Zaman Totok Chamidy Wardana, M. Dafa