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Prediksi Penduduk Kota Tomohon Menggunakan Random Forest Regression Berbasis WebGIS

SemanTIK: Teknik Informasi · Vol. 12 No. 1 (2026) · pp. 100–109

DOI
10.55679/semantik.v12i1.279
ISSN
2502-8928, 2460-1446
Published
2026-06-25
Publisher
Informatics Engineering Department of Halu Oleo University
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Pertumbuhan penduduk merupakan indikator vital dalam perencanaan pembangunan daerah. Saat ini, penyajian data kependudukan oleh Badan Pusat Statistik (BPS) Kota Tomohon masih berbentuk tabel statis, sehingga menyulitkan pemangku kepentingan untuk melakukan analisis spasial dan proyeksi tren masa depan. Penelitian ini membangun sistem WebGIS yang memprediksi dan memvisualisasikan pertumbuhan penduduk Kota Tomohon menggunakan Random Forest Regression dengan fitur lag untuk menangkap pola historis 2015–2023. Hasil prediksi 2024–2030 diintegrasikan ke dalam peta interaktif yang menampilkan sebaran kepadatan penduduk melalui simbol proporsional. Sistem ini berhasil menyajikan informasi demografis secara visual dan interaktif, dengan variasi pertumbuhan antar kecamatan sesuai pola data historis, sehingga efektif sebagai alat bantu keputusan dalam perencanaan tata ruang berbasis data. Population growth is a vital indicator in regional development planning. Currently, population data provided by the Central Statistics Agency (BPS) of Tomohon City is primarily presented in static tables, which limits stakeholders’ ability to conduct spatial analyses and project future trends efficiently. This study develops a WebGIS system capable of predicting and visualizing population growth in Tomohon City using Random Forest Regression with lag features to capture historical patterns from 2015–2023. The prediction results for the 2024–2030 period are integrated into an interactive web-based map that displays population density through proportional symbols. The system effectively presents demographic information visually and interactively, revealing variations in growth trends across different districts in accordance with historical data. Consequently, this tool provides practical support for data-driven decision-making in urban spatial planning.

Keywords

Collaboration network of the authors

7 authors · 9 co-authorship links

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  • Manado State University
  • Different organisations
  • Same organisation
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  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
G D P MaramisManado State University1
Mesiasi Anjelika SupitManado State University1
Nibertin ZaiManado State University1
Alfiansyah A HasibuanManado State University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://semantik.uho.ac.id/index.php/journal/oai, first harvested 26 Okt 2026, last seen 1 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Prediksi Penduduk Kota Tomohon Menggunakan Random Forest Regression Berbasis WebGIS</dc:title>
	<dc:creator>Rondonuwu, Tesalonika Natalia</dc:creator>
	<dc:creator>Audy Aldrin Kenap</dc:creator>
	<dc:creator>Tangkawarow, Irene Realyta Halldy Trosi</dc:creator>
	<dc:subject xml:lang="en-US">WebGIS</dc:subject>
	<dc:subject xml:lang="en-US">Random Forest</dc:subject>
	<dc:subject xml:lang="en-US">Machine Learning</dc:subject>
	<dc:subject xml:lang="en-US">Data Mining</dc:subject>
	<dc:description xml:lang="en-US">Pertumbuhan penduduk merupakan indikator vital dalam perencanaan pembangunan daerah. Saat ini, penyajian data kependudukan oleh Badan Pusat Statistik (BPS) Kota Tomohon masih berbentuk tabel statis, sehingga menyulitkan pemangku kepentingan untuk melakukan analisis spasial dan proyeksi tren masa depan. Penelitian ini membangun sistem WebGIS yang memprediksi dan memvisualisasikan pertumbuhan penduduk Kota Tomohon menggunakan Random Forest Regression dengan fitur lag untuk menangkap pola historis 2015–2023. Hasil prediksi 2024–2030 diintegrasikan ke dalam peta interaktif yang menampilkan sebaran kepadatan penduduk melalui simbol proporsional. Sistem ini berhasil menyajikan informasi demografis secara visual dan interaktif, dengan variasi pertumbuhan antar kecamatan sesuai pola data historis, sehingga efektif sebagai alat bantu keputusan dalam perencanaan tata ruang berbasis data.  
Population growth is a vital indicator in regional development planning. Currently, population data provided by the Central Statistics Agency (BPS) of Tomohon City is primarily presented in static tables, which limits stakeholders’ ability to conduct spatial analyses and project future trends efficiently. This study develops a WebGIS system capable of predicting and visualizing population growth in Tomohon City using Random Forest Regression with lag features to capture historical patterns from 2015–2023. The prediction results for the 2024–2030 period are integrated into an interactive web-based map that displays population density through proportional symbols. The system effectively presents demographic information visually and interactively, revealing variations in growth trends across different districts in accordance with historical data. Consequently, this tool provides practical support for data-driven decision-making in urban spatial planning.</dc:description>
	<dc:publisher xml:lang="en-US">Informatics Engineering Department of Halu Oleo University</dc:publisher>
	<dc:date>2026-06-25</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://semantik.uho.ac.id/index.php/journal/article/view/279</dc:identifier>
	<dc:identifier>10.55679/semantik.v12i1.279</dc:identifier>
	<dc:source xml:lang="en-US">SemanTIK : Teknik Informasi; Vol. 12 No. 1 (2026): Vol. 12 No. 1 (2026): SemanTIK Teknik Informasi; 100-109</dc:source>
	<dc:source>2502-8928</dc:source>
	<dc:source>2460-1446</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://semantik.uho.ac.id/index.php/journal/article/view/279/67</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Tesalonika Natalia Rondonuwu, Audy Aldrin Kenap, Irene Realyta Halldy Trosi Tangkawarow</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>