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Ririd, Ariadi Retno Tri Hayati
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Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media

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Analisis Klasterisasi Patok Jalan Berbasis Geospasial Menggunakan K-Means dan Evaluasi Davies-Bouldin Dien, Habibie Ed; Ratsanjani, M. Hasyim; Saputra, Agung Adi; Noprianto; Ririd, Ariadi Retno Tri Hayati; Nugraha, Bagas Satya Dian
Jurnal Pekommas Vol 9 No 2 (2024): Desember 2024
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jpkm.v9i2.5471

Abstract

Geographic Information System (GIS) has become a very important tool for spatial analysis and decision making in various fields. In this paper, the analysis process of grouping Kilometer Hectometer (KM/HM) road milestones use the K-Means method in the context of GIS. The KM/HM road milestones are road equipment made of concrete or signboards equipped with texts containing information about the distance and the name of the city to be traveled by road users. The length of the road that has such a long distance will make it difficult to maintain and to manage the road milestones that are scattered throughout the road. Currently, the process of mapping the location of the road milestones is still being carried out using the conventional method, in which the survey officer records the data on paper and measures it with the vehicle's odometer. However, this method often causes data loss, errors in determining the location, and lacks photographic evidence as a reference for assessing the condition of the road milestones. The role of GIS for survey officers is to map the road milestones and to visualize the road milestone data. The main objective is to gain meaningful insights from the spatial distribution of these road milestones, which will assist in better navigation and infrastructure planning. The K-Means method separates clusters from KM/HM road milestones which are identified based on geographical proximity. To assess the quality of these clusters, the evaluation is conducted using the Davies-Bouldin index (DBI) which provides a quantitative measure of inter-group similarity and within-group dissimilarity. For officers, it can be useful to find location points for the road milestones that have high damage conditions to prioritize to be repaired first. Based on the test results using DBI, it produces a value close to zero, which is equal to 0.1656, indicating that the clusters formed have very good quality.
Co-Authors Adi Pranoto, Adi Anak Agung Bagus Wirawan Andarini, Dyah Kartika Dwi Annisa, Diina Itsna Ardiansyah, Rizky Dhebys Suryani Hormansyah, Dhebys Suryani Dien, Habibie Ed Fadli, Alfian Huda Utama, Erwin Tidar Indra Dharma Wijaya, Indra Dharma Kurniawati, Ayundha Wulan Mubarok, M. Farid Husni Noprianto Nugraha, Bagas Satya Dian Pradibta, Hendra Prakoso, Aditya Bagus Pribadi, Dedy Teguh Primadhana, Yoga Andri Purwoko Aji, Deddy Kusbianto Ratsanjani, M. Hasyim Rosa Andrie Asmara Rudy Ariyanto Santoso, Nurudin Saputra, Agung Adi Setiyawan, Angga Yunhasnawa, Yoppy Yuri Ariyanto