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All Journal Jurnal Kesehatan Masyarakat Innovative: Journal Of Social Science Research
Ilham Armi
Institut Teknologi Padang
Humanities Computer Science & IT Law, Crime, Criminology & Criminal Justice Public Health Other

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Pemetaan Rute Trans Padang Berbasis Webgis Dwi Arini; Martince Novianti Bani; Ilham Armi; Quinoza Guvil; Ade Fernando
Innovative: Journal Of Social Science Research Vol. 3 No. 3 (2023): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v3i3.2483

Abstract

Trans Padang merupakan layanan angkutan massal (Bus Rapid Transit - BRT) di kota padang. Seiring dengan peningkatan pelayanan maka Rute Trans Padang juga telah dikembangkan ke beberapa ruas jalan, seperti pada Jalan Bypass. Dalam upaya untuk memberikan informasi yang komprehensif bagi masyarakat sehingga dapat mengetahui dan mengakses jalur Trans Padang secara efektif, efisien, dan secara daring, maka dilakukan pemetaan pada rute tersebut. Selain itu, penelitian ini juga bertujuan untuk mengaplikasikan penggunaan WebGIS dalam pemetaan Jalur Trans Padang. Data jalur koridor, jumlah armada yang beroperasi dan sebaran halte yang berada pada setiap koridor menjadi data utama dalam proses pemetaan ini. Dari hasil overlay dan penyusunan basis data maka diperoleh informasi, antara lain Jalur Trans Padang koridor 1 dari Jalan Imam Bonjol ke Lubuk Buaya (batas kota) dan koridor 4 dari Bungus Teluk Kabung Ke Mato Aia. Lebih dari itu, juga dapat diketahui bahwa terdapat 25 armada yang beroperasi pada koridor 1 dan 10 armada pada koridor 4. Waktu pengoperasian armada juga menjadi salah satu informasi yang bisa didapatkan yaitu pukul 06.00 WIB – 21.00 WIB. Selain itu, pembuatan WebGIS pada Jalur Trans Padang dengan menggunakan web hosting yang dikenal dengan 000Webhost dapat diakses secara gratis oleh masyarakat awam serta pemula dalam pembuatan WebGIS.
The Spatial Pattern of the Spread of the COVID-19 Pandemic (Case Study: DKI Jakarta Province) Dwi Arini; Agung Syetiawan; Eliza Nanda Pitria; Ilham Armi
Jurnal Kesehatan Masyarakat Vol 19, No 1 (2023)
Publisher : Department of Public Health, Faculty of Sport Science, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/kemas.v19i1.34015

Abstract

The COVID-19 pandemic has been running in Indonesia for more than two years. The first case was found in March 2020. DKI Jakarta as the capital city of the country with a high population density and an economic center that was threatened because the area has a high vulnerability to the spread of COVID-19. The number of confirmed cases that continue to soar and the spread that is difficult to be controlled have resulted in the DKI Jakarta government taking policies such as implementing large-scale social restrictions (PSBB), which aims to stop the spread of COVID-19 and to look for patterns of spread of COVID-19. This study uses a geographic information system in looking for patterns of the spread of COVID-19. The analytical method used is spatial autocorrelation, which is carried out using the Moran Index. In addition, the autocorrelation test was also carried out using a Local Indicator of Spatial Autocorrelation (LISA) with the results in the form of a cluster map and a map of significance. The Ordinary Least Squares analysis method is a regression technique that provides a global model for understanding and predicting variables in research. The correlation variables used in this research are Markets, Supermarkets, Buses, and Stations. The result of this study is the spatial autocorrelation of the pattern of spread of COVID-19 between villages and spatially the distribution pattern is clustered. In the OLS regression distribution pattern, the supermarket variable with an R-Squared value of 0.128555 or 12% affects the spread of COVID-19. Based on the calculation of R-Square, Koenker (BP) in addition to the OLS model, the assumption of homoscedasticity is not met, so the model is Ordinary Least Squares not good compared to other models in analyzing the pattern of the spread of COVID-19 in DKI Jakarta. 
Co-Authors Ade Fernando Agung Syetiawan Dwi Arini Eliza Nanda Pitria Martince Novianti Bani