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All Journal TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Jurnal Ilmu Komputer dan Sistem Informasi
Khairul Fajri Ilahi
Universitas Riau
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Library & Information Science

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Perancangan Sistem Informasi Penyewaan Karangan Bunga pada Delima Florist Menggunakan Metode Prototype Khairul Fajri Ilahi; Boy Sandy Dwi Nugraha H.; Herlina H.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 6 No 1 (2026): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol6No1.pp46-56

Abstract

Delima Florist is a company engaged in flower board rental services, currently focusing on providing flower board rentals in Padang. At present, Delima Florist is able to serve flower board orders from customers both within Padang and from outside the city. Currently, the flower board ordering process at Delima Florist is still carried out conventionally by using a communication application, after which the orders are manually recorded in an order ledger. This has led to several serious issues, such as customer orders frequently not being properly recorded, resulting in the flower boards not being produced by the Florists. Another issue is the frequent loss of flower boards after the rental period, caused by customers failing to return them to Delima Florist. The purpose of developing this flower board rental information system is to automate the processes of ordering, production recording, and flower board returns. This system is expected to make it easier for staff to monitor orders, deliveries, and returns of flower boards. The flower board rental information system will be developed using the Prototype method, while the process flow and system design will utilize Unified Modeling Language (UML).
Integrasi Algoritma DBSCAN Dengan Sistem Informasi Geografis Untuk Mengidentifikasi Cluster Wilayah Rawan Kebakaran Provinsi Riau Chairun Nas; Khairul Fajri Ilahi; Boy Sandy Dwi Nugraha
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.386

Abstract

Riau Province is one of the regions in Indonesia that is prone to forest and land fires (karhutla), especially during the dry season. Accurately identifying the distribution patterns of fire-prone areas is crucial in supporting disaster mitigation and management efforts. This study aims to identify the spatial patterns (Cluster) of forest and land fire-prone areas (karhutla) in Riau Province using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm integrated with a Geographic Information System (GIS). This study uses NASA-MODIS data taken from 2020 to 2024 with 840 data records. The analysis results show that DBSCAN is able to effectively group hotspots, with Cluster 2 being the largest cluster covering 297 karhutla points in Bengkalis, Rokan Hilir, and Dumai. The large number of points in this cluster is due to the high frequency of forest and land fires between 2020 and 2024. However, Cluster 7 shows the best density quality with a Silhouette Coefficient value of 0.872, surpassing Cluster 2 which has a value of 0.638. The overall average Silhouette Coefficient value is 0.683, indicating that the cluster modeling is quite optimal. A total of 57 hotspots are categorized as noise, but still provide a picture of the distribution of forest and land fires. GIS-based map visualization reveals that most fire hotspots are located in peatlands and dry vegetation areas that are consistent from year to year. The results of the study confirm that the use of appropriate DBSCAN parameters (epsilon and minPts) produces accurate spatial visualization and supports more effective and targeted mitigation strategies and fire monitoring based on priority areas.    
Co-Authors Boy Sandy Dwi Nugraha Boy Sandy Dwi Nugraha H. Chairun Nas Herlina H.