Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo

23 December 2021

By: Khadijah Nurul Lathifah

Open Data

Best Location (Clip)

Open Data

Best Location

Open Data

Jalan_MultipleRingBuffer

Open Data

Permukiman_MultipleRingBuffer

Open Data

Sungai_MultipleRingBuffer

Open Data

Kota_MultipleRingBuffer

Open Project

The Best Site Location for Dumping Site in Kulon Progo

Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo

One of the GIS applications on natural resources and the environment is to determine optimal locations for dumping sites by weighting an area by considering several factors such as the location distance from the river, elevation, soil type, distance from settlements, and others.

What is The Issue?

A dumping site is an excavated piece of land used as temporary storage for waste materials. Waste is a major problem in most places in Indonesia. The problem which often raises is the difficulty to find the land for the dumping site.

Why Dumping Site?

  • Based on Google Trends, Topic for Garbage is one of the most searched topic in Google which relevant with Dumping Site, and searched by many people in different provinces in Indonesia.
Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo
  • Also, I do social media trend analysis. I find out that some topic of Garbage is actually have a lot of views on Tiktok. For #garbage the views are 577.5M. It means that there are so many people that has aware with this issue.
Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo

Based on Google Trends and some Social Media Trend Analysis, we can conclude that Garbage is actually a popular topics and it h. This is why I choose Dumping Site for the topic in this project.

Why should be in Kulon Progo?

Based on my research, the potential for dumping site in Kulon Progo with a population of 434,483 people is estimated to be up to 173 tons per day or 63,260 tons per year. Meanwhile, the waste handled at the Banyuroto TPA in Kulon Progo is currently based on weighing data as much as 24-35 tons per day.

Reporting from harianmerapi.com (October 2021), "The condition of the Banyuroto TPA as of September 2021 has occurred. The location is indeed far from settlements and not densely populated. But if in the future the population is increasingly dense and around the TPA has become urban, this will become serious problem."

This is why I choose Kulonprogo to be the area of site selection.

"Kulon Progo's waste management must be taken seriously. Special measures are needed to prevent waste from accumulating in Kulon Progo."
harianmerapi.com (Oktober 2021)

Methodology

Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo

Buffer & Tessellation

The data used in this project are roads, city, land use, settlements, and rivers. The weighting for each input variable is based on the table 1 (Buffer zone layer with sub-criteria ratings). I use generate tessellation tool for producing the tessellation in hexagon shapes from the weighting result which have been done before in each variable. Analysis using vector approach with generate tessellation tools is available in ArcGIS Pro. The map result can be seen in the All Layer Maps section in GEO MAPID. The steps of generate tessellation are based on literature (Alkaradaghi et al. 2019).

Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo

Results

Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo

Lokasi Tempat Pembuangan Akhir Terbaik di Kulon Progo

As shown in the image above (Figure 5 & 6), each hexagon has its values based on the weighting results and Total_Value calculations done previously. The higher the Total_Value, the redder the color will appear. The redder the color, the more it shows that the area in the hexagon area is less suitable for use as a dumping site area. On the other hand, the lower the value, which is indicated by a more

Conclusion

From this project, we can conclude some points, such as :

1. Waste is a major problem in most places in Indonesia. The problem which often raises is the difficulty to find the land for the dumping site.

2. The project uses five polygon layers to find the best location for the dumping site in Kulon Progo with Generate Tessellation tools. The best site locations from Analysis result are in near Jalan tambon, Jalan gadingan Kulon Progo.

3. The project also provides a Dashboard to see the Opportunity of Site Location and Map Viewer by Geomapid to see all variable layers in one map.

References

Alkaradaghi K, Ali SS, Al-Ansari N, Laue J, Chabuk A. 2019. Landfill Site Selection Using MCDM Methods and GIS in the Sulaimaniyah Governorate, Iraq. Sustainability Journal. Accessible on: https://www.mdpi.com/2071-1050/11/17/4530.

Big Thanks to : MAPID Academy 3.0 x MRT Jakarta

Data Publications

Analisis Kesesuaian Lokasi dan Peluang Pasar untuk Ekspansi Gerai HokBen Berbasis Location Intelligence di Kota Surabaya

Food & Beverages

06 Sep 2026

Ridhwan Saputra

Analisis Kesesuaian Lokasi dan Peluang Pasar untuk Ekspansi Gerai HokBen Berbasis Location Intelligence di Kota Surabaya

Analisis site selection ekspansi gerai HokBen di Kota Surabaya menggunakan GIS untuk mengintegrasikan land suitability, market opportunity, demografi, POI, aksesibilitas, dan harga lahan. Hasil analisis QGIS dibandingkan dengan GEO MAPID Site Selection untuk mengidentifikasi area potensial berdasarkan kesesuaian lokasi dan peluang pasar.

24 min read

246 view

Evaluasi Keterjangkauan dan Usulan Rerouting Angkutan Kota Berbasis Location Analytics di Kota Malang, Jawa Timur

Transportation

04 Sep 2026

Meutia Amirotun Nuha

Evaluasi Keterjangkauan dan Usulan Rerouting Angkutan Kota Berbasis Location Analytics di Kota Malang, Jawa Timur

Penelitian ini mengevaluasi keterjangkauan pelayanan angkutan kota di Kota Malang dan menyusun alternatif rerouting berbasis location analytics. Keterjangkauan dianalisis menggunakan buffer 400 meter terhadap jaringan trayek eksisting, kemudian distribusi penduduk pada kawasan permukiman digunakan untuk mengidentifikasi population service gap. Kawasan yang belum terlayani dikelompokkan menjadi 27 cluster dan lima cluster dengan service gap terbesar dipilih sebagai Priority Service Area. Analisis selanjutnya mempertimbangkan jaringan jalan, pusat aktivitas, keterhubungan terhadap trayek eksisting, dan akses transportasi regional untuk menyusun koridor kandidat. Hasil menunjukkan bahwa pelayanan angkot eksisting menjangkau sekitar 616.575 jiwa atau 69,33% penduduk Kota Malang, sementara 272.784 jiwa belum terlayani. Skenario rerouting pada lima kawasan prioritas mampu menambah jangkauan terhadap sekitar 145.101 penduduk sehingga coverage meningkat menjadi 85,64%. Selain itu, 53 dari 56 POI prioritas berada dalam jangkauan pelayanan setelah skenario diterapkan. Temuan menunjukkan bahwa penanganan service gap secara terarah dapat meningkatkan keterjangkauan tanpa harus memperluas jaringan ke seluruh kawasan residual. Hasil penelitian merupakan screening spasial awal yang masih memerlukan validasi teknis dan operasional sebelum implementasi.

26 min read

228 view

12 Data

1 Projects

Analisis Sweet Spot Location Attractiveness Bagi Pengembangan Properti Co-Living di Area Perkotaan Yogyakarta

Real Estate

06 Sep 2026

Wildan Rafi Fadlilah

Analisis Sweet Spot Location Attractiveness Bagi Pengembangan Properti Co-Living di Area Perkotaan Yogyakarta

Panduan ekspansi co-living yang terukur di Yogyakarta untuk pengembang properti dalam menghadapi kebutuhan pasar dan tekanan kompetisi

41 min read

206 view

1 Projects

Rekomendasi Lokasi Optimal Pengembangan Kawasan Permukiman dengan Metode Multi-Criteria Scoring di Kawasan BSD Barat, Kabupaten Tangerang

Real Estate

04 Sep 2026

Asti Ardiningrum

Rekomendasi Lokasi Optimal Pengembangan Kawasan Permukiman dengan Metode Multi-Criteria Scoring di Kawasan BSD Barat, Kabupaten Tangerang

Penelitian dengan analisis spasial multi-kriteria pada kawasan BSD Baru mengidentifikasi bahwa wilayah selatan (sebagian Jatake, Situ Gadung, dan Sampora) merupakan lokasi paling optimal (Sangat Sesuai) untuk kawasan permukiman karena didukung akses langsung Tol Serpong–Balaraja dan stasiun KRL. Temuan yang selaras dengan RTRW 2021–2031 dan Masterplan BSD City ini menempatkan wilayah selatan sebagai prioritas utama pembangunan bagi pengembang sekaligus opsi hunian dan investasi terbaik bagi masyarakat.

14 min read

226 view

1 Projects

Terms and Conditions
Introductions
  • MAPID is a platform that provides Geographic Information System (GIS) services for managing, visualizing, and analyzing geospatial data.
  • This platform is owned and operated by PT Multi Areal Planing Indonesia, located at