Main Article Content
Abstract
A livable house is abbreviated as the feasibility of a residential house which can be measured from 2 aspects, namely the physical quality of the house and the quality of house facilities. The physical quality of the residential house is measured by 3 variables, namely the type of roof, the type of wall, and the type of floor, while the quality of the housing facilities is measured by 2 variables, namely the source of lighting and the availability of toilet facilities. In this study, the authors use the prototype method using data analysis and system design. This web-based geographic information system for livable houses in Kandolo Village aims to assist in the data collection process for livable houses in Kandolo Village. The results of this study 257 house data have been entered, of which 247 houses are suitable for livable on, 6 houses that are less suitable for livable on, and 4 houses that are not suitable for livable on. For visitors, this system functions to select houses that are livable by looking at several registered pins, then the system will take the resident data detail page. Then in the detail section of citizen data, there will be some resident data, photos of houses, and routes to their destination. From the application trial results, the author conducted a black box test with 11 test class items and respondent tests for direct users at the Kandolo Village Office where the features are used to well and are accepted among the community.
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References
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References
Beze, H. et al. (2021) ‘Implementasi SIG Untuk Monitoring Kesehatan Lingkungan Studi Kasus Kelurahan Harapan Baru’, Buletin Poltanesa, 22(1), pp. 33–37. doi: 10.51967/tanesa.v22i1.464.
Chandra , W.J. and Hardiyana, B. (2019) ‘Rancang Bangun Sistem Informasi Geografis Rumah Tidak Layak Huni Sebagai Pendukung Keputusan Kebijakan Di Tingkat Desa’, Jurnal Teknik Informatika dan Sistem Informasi, 5(1), pp. 40–50. doi: 10.28932/jutisi.v5i1.1580.
Darussalam and Arief, G. (2017)’Analisis Data Sistem Informasi Geografis Rumah Tidak Layak Huni
(RTLH) Menggunakan Metode Fuzzy Logic’Jurnal Resti’, Resti, 1(1), pp.1179 – 1189.
Gustina, R. and Leidiyana, H. (2020) ‘Sistem Informasi Penggajian Karyawan Berbasis Web Menggunakan Framework Laravel’, JSiI (Jurnal Sistem Informasi), 7(1), p. 34. doi: 10.30656/jsii.v7i1.1726.
Lasena, M. and Tambayong, D. (2016) ‘Sistem Informasi Geografis Bantuan Rumah Layak Huni Berbasis Web Pada Dinas Sosial Kabupaten Bolaang Mongondow Utara’, Teknosains, 10(1), pp. 89–103. Available at: http://journal.uin-alauddin.ac.id/index.php/teknosains/article/view/1880.
Saputra, D. (2018) ‘Analisis Perbandingan Performa Web Service Rest Menggunakan Framework Laravel, Django Dan Ruby On Rails Untuk Akses Data Dengan’, Jurnal Bangkit Indonesia, 7(2), p. 17. doi: 10.52771/bangkitindonesia.v7i2.90.
Sarwindah, S. and Yanuarti, E. (2020) ‘Pengembangan Prototype Sistem E-Commerce pada Ajun Elektronik dengan Metode FAST’, Jurnal Sisfokom (Sistem Informasi dan Komputer), 9(2), pp. 281–288. doi: 10.32736/sisfokom.v9i2.871.
Setiawan, N. V. (2018) ‘Sistem Informasi Geografis Rumah Sehat Berbasis Website’, 1. Available at: https://repository.unikom.ac.id/57849/.
Sihotang, H. T. (2019) ‘Sistem Informasi Pengagendaan Surat Berbasis Web Pada Pengadilan Tinggi Medan’, 3(1), pp. 6–9. doi: 10.31227/osf.io/bhj5q.
Soepomo, P. (2013) ‘Perancangan Sistem Pendukung Keputusan Penentuan Rumah Sehat’, JSTIE (Jurnal Sarjana Teknik Informatika) (E-Journal), 1(2), pp. 584–596.