Article Per Year (5 Year)
p-Index From 2021 - 2026
3.544
P-Index
This Author published in this journals
All Journal TEKNIK Jurnal Geodesi Undip Journal of Engineering and Technological Sciences JURNAL ILMIAH GEOMATIKA Elipsoida : Jurnal Geodesi dan Geomatika Jambura Geoscience Review TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Pasopati : Pengabdian Masyarakat dan Inovasi Pengembangan Teknologi Jurnal Ilmiah Geomatika Geoid - Journal of Geodesy and Geomatics
Moehammad Awaluddin
Departemen Teknik Geodesi - Fakultas Teknik Universitas Diponegoro
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Social Sciences

Published : 153 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 153 Documents
Search

 12   13   14   15   16 
Identification of Traffic Accidents Vulnerability Level Using Kernel Density And K-Medoids Methods (Case Study: Depok and Kalasan Districts, Sleman Regency) Siregar, Afifah Zafirah; Awaluddin, Moehammad; Wahyuddin, Yasser
Jurnal Ilmiah Geomatika Vol. 3 No. 1 (2023): April Jurnal Ilmiah Geomatika
Publisher : Program Studi Teknik Geomatika Fakultas Teknologi Mineral Universitas Pembangunan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/imagi.v3i1.9241

Abstract

One of the analytical tools that can be used to help, parse, identify and map traffic accident problems in an area is a Geographic Information System (GIS). GIS is used to create clusters of traffic accident events. The level of accident vulnerability in this paper is obtained by calculating the density of the number of incident points where the accident occurred, namely Depok and Kalasan Districts, Sleman Regency on a road segment length of 1,000 m per year. The clustering methods used are kernel density and k-medoids methods. Comparison of the identification of traffic accident-prone levels in Depok and Kalasan sub-districts using the Kernel Density and K-Medoids methods with a road length of 1,000 meters using the Kernel Density and K-Medoids methods in 2018 there is the same difference, namely 6.17% with the medium level classification and low level classification. For 2019 it is 0.01% with a high level classification, 1.85% for the medium level and 1.86% for the low level. For 2020 there is the same difference, namely 1.23% with medium and low level classifications. For 2021 there is no difference for high level classification but there is the same difference for medium and low level classification which is 3.7%.
Analysis of Building Density Using Deep Learning Model Semantic Segmentation Nuranda, Kris Junida Herindra; Awaluddin, Moehammad; Hadi, Firman
Elipsoida : Jurnal Geodesi dan Geomatika Vol 8, No 2 (2025): Volume 08 Issue 02 Year 2025
Publisher : Department of Geodesy Engineering, Faculty of Engineering, Diponegoro University,Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/elipsoida.2025.27502

Abstract

Densely populated settlements are one of the urban problems with building density that requires special attention. This research aims to detect and analyze the spatial distribution of building density, especially in detecting building density in residential areas using the Semantic Segmentation deep learning model method with a research dataset sourced from the entire DKI Jakarta Province area. The analysis was conducted using typology criteria in the form of building density levels based on PERMEN PUPR No. 14 of 2018 concerning the Prevention and Improvement of the Quality of Slums and Slum Settlements, which was processed through the Kaggle Notebook and Google Colaboratory platforms using the Python programming language and based on the U-Net architecture. The segmentation results show that using the U-Net architecture is capable of classifying image pixels with an accuracy of 70% in distinguishing between dense and Sparse buildings, which indicates fairly good accuracy performance. The output produced in this final project research is a web interface for detecting dense and Sparse buildings that can be used as a tool to aid in decision-making for regional planning. This research shows that the Semantic Segmentation deep learning model approach can be an efficient and objective solution in satellite image-based spatial analysis. Keywords:  Deep Learning, Building Density, Semantic Segmentation       
PENAJAMAN DAN SEGMENTASI CITRA PADA PENGOLAHAN CITRA DIGITAL Moehammad Awaluddin; Bambang Darmo Y
TEKNIK Vol 31, No 1 (2010)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2140.426 KB) | DOI: 10.14710/teknik.v31i1.1756

Abstract

Image processing takes an image to produce a modified image for better viewing or some other purposes Imageanalysis takes an image into something other than an image such as number of object types, size of an object,etc.The main purpose of Enhancing Image is to produce image in order to have a suitable image forApplication requirement. Image segmentation is divided into a several segment considering area of the object.We need the Enhancement technique and segmentation to have a good image. In this case , it was trying toprocess image with a several stage , stretching, lowpass filter, laplace filter, edgesenh filter and clustering inSPOT image in aceh coverage area.
Co-Authors Abdi Sukmono Abdi Sukmono, Abdi Adnan Khairi Afriyanto Afriyanto Aisyah Arifin Aisyah Arifin Ajeng Kartika Nugraheni Syafitri Alfian Budi Prasetya Alfien Rahmenda Ali Amirrudin Ahmad Amal Fathullah, Amal Amri Perdana Ginting Ana Rosida Andika Malik Andika Rizal Bahlefi Andre Hermawan Andri Suprayogi Anggi Tiarasani Anisa Rachmawati, Anisa ARGNES DIONANDA RESZA PRADIPTA Arief Laila Nugraha Arief Laila Nugraha Arief Laila Nugraha Arintia Eka Ningsih Ario Damar Wicaksono Armenda Bagas Ramadhony Aruma Hartri Aufan Niam Aulia Fikki Wicaksono Aysha Puspa Pertiwi Ayu Nur Safi'i Bambang Darmo Y Bambang Darmo Yuwono Bambang Darmo Yuwono Bambang Darmo Yuwono Bambang Sudarsono Bambang Sudarsono Bandi Sasmito Bhekti Hapsari Bilqis, Ramadhani Sarah Alicya Bobby Daneswara Indra Kusuma Brinton Patuan Sitorus Budi Prayitno Cindy Puspita Sari Damar Ismoyo Danang Budi Susetyo Desita Khrisna Putri, Dewa, Kusuma Hangga Dewi Shinta Septifany Dian Rizqi Ari Wibowo Dimas Bagus Dina Wahyuningsih Dwi Arini Dzaki Adzhan Ega Gumilar Hafiz Enersia Ihda K. U Extiana, Kiky Fadhilla Shara Denafiar Fajar Dwi Hernawan Fanni Kurniawan Fanny Rachmawati Fathan Aulia Fauzi Iskandar Fauzi Janu Amarrohman, Fauzi Janu Fauzi Janu Ammarohman Febrian Pramana Putra Fetra Kristina Harianja Gina Andriyani Habib Azka Ramadhani Hadi, Firman Hana Sugiastu Firdaus Hana Sugiastu Firdaus Hana Sugiastu Firdaus Handayani Nur Arifiyanti Haniah Haniah Haris Yusron Heri Gusfarienza Heri Setiawan Ika Nurdianasari Ikhlasul Amal Ahyani Indra Laksana Irfan Tri Anggoro irwan meilano Johan Wisma Anggoro Joko Wibowo Juwita Widya Qur’ani Khairuddin Khairuddin Khofifatul Azizah Khofifatul Azizah Kiky Extiana Kindy Ibrahim Hari Kurniawan Adi Widiyanto L. M. Sabri Labib, Muhammad Faishal Laode M Sabri LAURENTIUS IMMANUEL YUDIT PRABOWO LM. Sabri Lolita, Diaz Amel Lorenzia Anggi Ramayanti Lufti Rangga Saputra LUKMAN MAULANA ABDILLAH Lutfi Eka Rahmawan Lutgar Sudiyanto Sitohang LUTHFI RAHMANDHANI Mahmudi, Fakhry Nur Maulana Eras Rahadi Meita Arddinatarta Moh Kun Fariqul Haqqi Mohammad Afif MOHAMMAD YUSUP LUTFI Much. Jibriel Sajagat, Much. Jibriel Muhamad Arif Debalano Muhamad Nurman Cholid Muhammad Bagus Salim Muhammad Danny Rahman Muhammad Hudayawan Nur L Muhammad Iqbal Akhsin Muhammad Maulana mahardika Amfa Muhammad Rifqi Andikasani Nanda Dewi Arumsari Nasytha Nur Farah Nella Wakhidatus Nina Ratnaningrum NOVAYA NURUL BASYIROH Nugrahanto, Prasetyo Odi Nur Lail, Muhammad Hudayawan Nuranda, Kris Junida Herindra Nurhadi Bashit Nurhadi Bashit Nurmalasari, Cici Nurnaning Aisyah Pardjono, P. Prya Adhi Surya Nugraha Putri, Alifa Salsabilla Rachmawati, Ekha Ramdhan Thoriq Setyabudi Renaud Saputra Purba Resi Diansismita Reza Nur Hidayat Rico Waskito Putro Rifki Purnama Aji Rifqi, Muhammad Alifian Risa Ayu Miftahul Rizky Riyadi, Elnatan Vieno Rizky Saputra Rofi'i, Nur Izha Jannah Roy Kasfari Sabri, Laode M. Safii, Ayu Nur Safira Devi Kirana Sandy Yudistira Mahardika, Sandy Yudistira Sarmedis Anrico Situmorang Satrio Wicaksono Sawitri Subiyanto Septian Dewi Cahyani Septiawan Setio Hutomo Setiaji Nanang Handriyanto Sigit Irfantoro Siregar, Afifah Zafirah Siti Fathimah Soraya Rizky Puspitasari Sri Widiyantoro Sry Suando Sinaga Susilo Susilo Sutomo Kahar Syachril Warasambi Mispaki Tiara Toyyibatul Arofah Tristika Putri Wahyu Entriana Kumala Dewi Wahyu Nur Rohim Wahyuddin, Yasser Wakhidatus, Nella Wibowo, Sidik Tri Wildan Ryan Irfana Yolanda Adya Puspita Yudo Prasetyo