Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Specta Journal of Technology Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Jurnal Keselamatan Transportasi Jalan
Nurul Istiqomah
Universitas Islam Negeri Sunan Ampel
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Environmental Science Mechanical Engineering Transportation

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Penerapan K-Means Clustering untuk Analisis Kondisi Lalu Lintas di Jalan Ir. H. Soekarno Surabaya Nurul Istiqomah; Wika Dianita Utami; Dian Yuliati
Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Vol. 12 No. 2 (2025): JURNAL KESELAMATAN TRANSPORTASI JALAN (INDONESIAN JOURNAL OF ROAD SAFETY)
Publisher : Pusat Penelitian dan Pengabdian Masyarakat (P3M)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46447/ktj.v12i2.725

Abstract

Growth in the number of vehicles, especially in urban areas, has a significant impact on traffic density, especially during peak hours, so an approach is needed to group traffic conditions based on the volume of all types of vehicles and the degree of saturation using the K-Means Clustering algorithm. The data used are the volume of all types of vehicles and the degree of saturation obtained from the Surabaya City Transportation Agency. The clustering results show that there are 4 clusters of different traffic characteristics, such as the volume of 2-wheeled vehicles during heavy traffic conditions of more than 4700 vehicles with a degree of saturation of more than 0.45. Evaluation using the silhouette coefficient produces a value of 0.63, which means the quality of the cluster is in a medium structure. This study shows that the clustering method is effective in understanding traffic conditions, although additional features can be done to optimize the quality of the cluster.
Penerapan K-Means Clustering untuk Analisis Kondisi Lalu Lintas di Jalan Ir. H. Soekarno Surabaya Nurul Istiqomah; Wika Dianita Utami; Dian Yuliati
Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Vol. 12 No. 2 (2025): JURNAL KESELAMATAN TRANSPORTASI JALAN (INDONESIAN JOURNAL OF ROAD SAFETY)
Publisher : Pusat Penelitian dan Pengabdian Masyarakat (P3M)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46447/ktj.v12i2.725

Abstract

Growth in the number of vehicles, especially in urban areas, has a significant impact on traffic density, especially during peak hours, so an approach is needed to group traffic conditions based on the volume of all types of vehicles and the degree of saturation using the K-Means Clustering algorithm. The data used are the volume of all types of vehicles and the degree of saturation obtained from the Surabaya City Transportation Agency. The clustering results show that there are 4 clusters of different traffic characteristics, such as the volume of 2-wheeled vehicles during heavy traffic conditions of more than 4700 vehicles with a degree of saturation of more than 0.45. Evaluation using the silhouette coefficient produces a value of 0.63, which means the quality of the cluster is in a medium structure. This study shows that the clustering method is effective in understanding traffic conditions, although additional features can be done to optimize the quality of the cluster.
Pemodelan Gaussian Plume pada Sebaran Abu Vulkanik sebagai Sistem Peringatan Dini: 177 - 185 Nurul Istiqomah; Fanny Maulidya; Izza Dhinillah; Dian Candra Rini Novitasari
SPECTA Journal of Technology Vol. 10 No. 2 (2026): Specta Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Indonesia is part of the Pacific Ring of Fire and hosts 129 active volcanoes, including Mount Ibu in Halmahera Regency, North Maluku. Mount Ibu, standing 1,340 meters above sea level, has shown increased volcanic activity since 2008, with 2,136 eruptions recorded up to 2025. This study aims to apply the Gaussian Cloud Model to simulate the distribution of volcanic ash, especially PM10, and map the potential impacts of the eruption of Mount Ibu as part of an early warning system. Data were obtained from PVMBG. The modelling results show that volcanic ash dispersed toward the northwest, reaching a maximum concentration of 2.35 × 10⁻¹⁸⁸ μg/m³. A MATLAB-based Graphical User Interface (GUI) was developed to visualize the ash distribution. The highest concentration occurred around the Talen region, near the eruption source, and gradually decreased in other areas such as Tolofu and Gam Ici due to particle dispersion and dilution. These findings indicate that the proposed model can support early warning systems and contribute to disaster mitigation efforts related to volcanic activity
Co-Authors Dian Candra Rini Novitasari Dian Yuliati Fanny Maulidya Izza Dhinillah Wika Dianita Utami