Prediksi Volume Sampah Perkotaan Berbasis Data Spasial Menggunakan Random Forest di DKI Jakarta

Authors

  • aftor maulana Universitas Nusantara PGRI Kediri Indonesia
  • Aidina Ristyawan Universitas Nusantara PGRI Kediri Indonesia https://orcid.org/0000-0001-9080-5723
  • Andika Firmansyah Universitas Nusantara PGRI Kediri Indonesia
  • Anastasia R R Ndun Universitas Nusantara PGRI Kediri Indonesia

DOI:

https://doi.org/10.29407/5yeap977

Abstract

Pengelolaan sampah di DKI Jakarta menghadapi tantangan seiring pertumbuhan penduduk dan perubahan pola konsumsi. Penelitian ini memanfaatkan algoritma Random Forest Regressor untuk memprediksi volume sampah berdasarkan data spasial, seperti lokasi wilayah administratif, luas permukiman, dan kepadatan penduduk. Data dikumpulkan dari BPS, Dinas Lingkungan Hidup DKI Jakarta, serta platform pemetaan digital, mencakup lebih dari 600 titik wilayah. Model menghasilkan nilai R² sebesar 0,87, Mean Absolute Error 15,3 ton, dan Root Mean Squared Error 21,7 ton. Fitur paling berpengaruh adalah luas kawasan permukiman, jumlah penduduk, dan kepadatan wilayah. Model ini berpotensi membantu pemerintah dalam merencanakan distribusi armada dan fasilitas pengelolaan sampah secara lebih efektif. Penelitian juga merekomendasikan penambahan variabel seperti aktivitas ekonomi dan mobilitas penduduk guna meningkatkan akurasi prediksi di masa mendatang.

Keywords:

prediksi volume sampah, Random Forest Regresor, data spasial, perencanaan sampah

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References

[1] A. Kahfi, “Overview of Waste Management,” Jurisprud. Dep. Law, Fac. Sharia Law, vol. 4, no. 1, p. 12, 2017.

[2] M. Iqbal, R. M. Mulyadin, K. Ariawan, and S. Subarudi, “Analisis Implementasi Kebijakan Pengelolaan Sampah Di Provinsi Dki Jakarta,” J. Anal. Kebijak. Kehutan., vol. 19, no. 2, pp. 129–140, 2022, doi: 10.20886/jakk.2022.19.2.129-140.

[3] R. Mohamad Mulyadin, K. Ariawan, and M. Iqbal, “Conflict of Waste Management in Dki Jakarta and Its Recomended Solutions,” J. Anal. Kebijak. Kehutan., vol. 15, no. 2, pp. 179–191, 2018, doi: 10.20886/jakk.2018.15.2.179-191.

[4] M. R. Diani, D. Haniifah, and F. R. Dianty, “Analisis proyeksi pertumbuhan penduduk dan volume sampah DKI Jakarta terhadap dampak yang ditimbulkan,” J. Waste Sustain. Consum., vol. 1, no. 1, pp. 27–45, 2024, doi: 10.61511/jwsc.v1i1.2024.691.

[5] B. A. R. Apriyeni, Sejarah dan Perkembangan Awal Informasi Geospasial. 2023.

[6] C. Puspawati and B. Besral, “Pengelolaan Sampah Berbasis Masyarakat di Kampung Rawajati Jakarta Selatan,” Kesmas Natl. Public Heal. J., vol. 3, no. 1, p. 9, 2008, doi: 10.21109/kesmas.v3i1.237.

[7] M. J. Bastiaans, “New Class of Uncertainty Relations for Partially Coherent Light.,” 13th Congr. Int. Comm. Opt. Opt. Mod. Sci. Technol. Conf. Dig., pp. 638–639, 1984, doi: 10.1364/josaa.1.000711.

[8] A. Fitria Salsabella, B. Suprianto, and M. Syariffuddien Zuhrie, “Analisis Pengerukan Sampah Pada Sungai Kawasan Jakarta Pusat Dengan Sistem Inferensi Fuzzy Takagi-Sugeno Berbasis Matlab,” J. Tek. Elektro, vol. 11, no. 2, pp. 288–296, 2022.

[9] D. Ardiatma, P. Lestari, and M. Chaerul, “Real data mapping of DKI Jakarta waste generation using the K-mean Clustering method at final disposal Bantargebang,” E3S Web Conf., vol. 485, 2024, doi: 10.1051/e3sconf/202448502015.

[10] D. Ruwandara, M. Jajuli, and A. Rizal, “Analisis Algoritma K-Means Clustering Untuk Daerah Penyebaran Sampah di Kota Bekasi,” JOINS (Journal Inf. Syst., vol. 6, no. 1, pp. 56–63, 2021, doi: 10.33633/joins.v6i1.4085.

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Published

2025-07-10

Issue

Vol. 9 No. 2 (2025): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2025

Section

Articles

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Copyright (c) 2025 aftor maulana, Aidina Ristyawan, Andika Firmansyah, Anastasia R R Ndun

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How to Cite

Prediksi Volume Sampah Perkotaan Berbasis Data Spasial Menggunakan Random Forest di DKI Jakarta. (2025). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 9(2), 1667-1672. https://doi.org/10.29407/5yeap977