Pengaruh Smoothing Data Terhadap Hasil Prediksi Volume dan Ritasi Sampah di Kota Bandung Menggunakan Metode Regresi Linear
DOI:
https://doi.org/10.32493/informatika.v9i3.43271Keywords:
waste, prediction, moving average, smoothing data, linear regressionAbstract
The waste problem is very important in big cities, especially Bandung. The population, people's lifestyles and waste management that has not been carried out professionally are a challenge in itself. One of the preparatory steps to deal with the waste problem is to predict the development of waste volume. In this study, a statistical time series approach, namely the linear regression method, is used to predict the volume and transportation of waste in the city of Bandung. In the prediction process, data processing before being used in the prediction process plays an important role, one of which is data smoothing. A process to smooth the data using the moving average method with intervals of 2.3 and 4 and moving averages with weights of 242 and 12421 will be used to see its effect on the prediction results. Scenario 1 of the data used is all monthly data in the dataset time range and scenario 2 uses the same month's data for each year to predict the results of the month in the following year. The results of the volume and transportation predictions of waste between the best results from the Smoothing method and the results without going through the data smoothing process in scenario 1 show less significant results, namely less than 1%, while in scenario 2 it shows quite significant results, namely around 10% when compared to the actual data. Patterns and data ranges affect the final result from scenarios above.
References
Abu-Faraj, M., Al-Hyari, A., & Alqadi, Z. (2022). Experimental Analysis of Methods Used to Solve Linear Regression Models. Computers, Materials & Continua, 72(3), 5699–5712. https://doi.org/10.32604/cmc.2022.027364
Anam, K., Salim, A., Handayani, T., & Ambarwati, A. (2023). Sosialisasi Sampah Organik dan Sampah Anorganik dalam Optimalisasi Proklim di Desa Rowoboni. Jurnal Bina Desa, 5(2), 225–230. https://doi.org/10.15294/jbd.v5i2.43886
Anggryawan, F., Mudjanarko, S. W., Wahyuni, A., & Wasono, S. B. (2020). ANALISIS KINERJA TRUK PENGANGKUT SAMPAH KOTA DI KECAMATAN BENOWO. ASTONJADRO, 9(1), 38. https://doi.org/10.32832/astonjadro.v9i1.2883
Ardhi, S., Putera Gunawan, T., Tjandra, S., & Dewi, G. L. (2023). Penerapan Metode Regresi Linear dalam Pengembangan Pengukuran Aliran Air pada Sensor YF-S201 (Vol. 26, Issue 1). http://univ45sby.ac.id/ejournal/index.php/industri/index
Ariefahnoor, D., Hasanah, N., & Surya, A. (2020). PENGELOLAAN SAMPAH DESA GUDANG TENGAH MELALUI MANAJEMEN BANK SAMPAH. Jurnal Kacapuri : Jurnal Keilmuan Teknik Sipil, 3(1), 14. https://doi.org/10.31602/jk.v3i1.3594
Aziza, J. N. A. (2022). Perbandingan Metode Moving Average, Single Exponential Smoothing, dan Double Exponential Smoothing Pada Peramalan Permintaan Tabung Gas LPG PT Petrogas Prima Services. Jurnal Teknologi Dan Manajemen Industri Terapan, 1(I), 35–41. https://doi.org/10.55826/tmit.v1iI.8
Fan, C., Chen, M., Wang, X., Wang, J., & Huang, B. (2021). A Review on Data Preprocessing Techniques Toward Efficient and Reliable Knowledge Discovery From Building Operational Data. Frontiers in Energy Research, 9. https://doi.org/10.3389/fenrg.2021.652801
Guan, T., Alam, M. K., & Rao, M. B. (2023). Sample Size Calculations in Simple Linear Regression: A New Approach. Entropy, 25(4), 611. https://doi.org/10.3390/e25040611
Gunawansyah, Laluma, R. H., & Prasetya, A. (2022). Prediksi Volume Dan Ritasi Pengelolaan Sampah Di Kota Bandung Dengan Metode Regresi Linear. Techno-Socio Ekonomika, 15(1), 49. https://doi.org/10.32897/techno.2022.15.1.1195
Hanafi, M., Warsito, B., & Gernowo, R. (2022). Sistem Informasi Manajemen Pengumpulan dan Pengangkutan Sampah Padat dengan Efisiensi Rute Menggunakan K-Means Clustering dan Travelling Salesman Problem. https://doi.org/10.21456/vol12iss2pp107-115
Hidayat, E., Faizal, L., Tetap, D., Syariah, F., Raden, U., & Lampung, I. (2020). STRATEGI PENGELOLAAN SAMPAH SEBAGAI UPAYA PENINGKATAN PENGELOLAAN SAMPAH DI ERA OTONOMI DAERAH.
Hope, T. M. H. (2020). Linear regression. In Machine Learning (pp. 67–81). Elsevier. https://doi.org/10.1016/B978-0-12-815739-8.00004-3
Mulyati, B., Ilmi, Y. F., & Basri, A. (2023). Sosialisasi Pengelolaan Sampah sebagai Upaya Peningkatan Peran Masyarakat dalam Mengelola Sampah di Kota Serang. BANTENESE : JURNAL PENGABDIAN MASYARAKAT, 5(1), 26–34. https://doi.org/10.30656/ps2pm.v5i1.6285
Nurdiansah, T., Purnomo, E. P., & Kasiwi, A. (2020). IMPLEMENTASI PEMBANGKIT LISTRIK TENAGA SAMPAH (PLTSa) SEBAGAI SOLUSI PERMASALAHAN SAMPAH PERKOTAAN; STUDI KASUS di KOTA SURABAYA. JURNAL ENVIROTEK, 12(1), 87–92. https://doi.org/10.33005/envirotek.v12i1.47
Poh, D. K. H., Lim, C. Y., Tan, R. Z., Markus, C., & Loh, T. P. (2021). Internal quality control: Moving average algorithms outperform Westgard rules. Clinical Biochemistry, 98, 63–69. https://doi.org/10.1016/j.clinbiochem.2021.09.007
Prami Swari, M. H., Susila Handika, I. P., & Susila Satwika, I. K. (2021). Comparison of Simple Moving Average, Single and Modified Single Exponential Smoothing. 2021 IEEE 7th Information Technology International Seminar (ITIS), 1–5. https://doi.org/10.1109/ITIS53497.2021.9791516
Putra, R., Sinurat, P., Keuangan, P., Stan, N., & Korespondensi, A. (2023). POTENSI PENERIMAAN PAJAK PENGHASILAN DI INDONESIA: SEBUAH ANALISIS DERET WAKTU.
Ramdhan, M., & Hermawan, E. (2022). Permasalahan Sampah di Kota Bogor Sebagai Wilayah Penyangga DKI Jakarta. Jurnal Riset Jakarta, 15(2). https://doi.org/10.37439/jurnaldrd.v15i2.59
Suryadana, K., & Sarasvananda, I. B. G. (2024). Streamlining Inventory Forecasting with Weighted Moving Average Method at Parta Trading Companies. Jurnal Galaksi, 1(1), 12–21. https://doi.org/10.70103/galaksi.v1i1.2
Vimala, J., & Nugroho, A. (2022). FORECASTING PENJUALAN OBAT MENGGUNAKAN METODE SINGLE, DOUBLE, DAN TRIPLE EXPONENTIAL SMOOTHING ( STUDI KASUS : APOTEK MANDIRI MEDIKA). IT-Explore: Jurnal Penerapan Teknologi Informasi Dan Komunikasi, 1(2), 90–99. https://doi.org/10.24246/itexplore.v1i2.2022.pp90-99
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