Prediction of Clean Water Supply Using the Fuzzy Time Series Cheng Method at PDAM Tirta Silau Piasa
DOI:
https://doi.org/10.20956/j.v20i2.32071Keywords:
Supply, Clean Water, Fuzzy Time SeriesAbstract
This research aims to determine predictions of clean water supply at PDAM Tirta Silau Piasa in 2023 using the Fuzzy Time Series Cheng method. This type of research is quantitative research using data sources, namely secondary data. This research data was taken from clean water supply data at PDAM Tirta Silau Piasa, namely data on the volume of clean water for the period January 2021 to May 2023. From the calculation results of the prediction analysis of clean water supply at PDAM Tirta Silau Piasa using the Fuzzy Time Series Cheng method, for the amount of water supply clean water in June 2023 is 443,620, with a total predicted clean water supply from 2021 to June 2023 of 12,031,703. With a MAPE value of 3%, if we look at the MAPE which is less than 10%, the results of predicting clean water supply using the Fuzzy Time Series Cheng method produce the best prediction value.Downloads
References
Arif Ikhsanudin, K. I., 2022. Metode Fuzzy Time Series Model Chen Untuk Memprediksi Jumlah Kasus Aktif Covid-19 Di Indonesia. Jurnal Transformasi (Informasi & Pengembangan Iptek)(STMIK BINA PATRIA), 18, No. 1, 40-53.
Aswi, & Sukarna., 2017. Analisis Data Der et Waktu. Teori dan Aplikasi.
Chung-Ho Su, Ching-Hsue Cheng, & Wei-Lun Tsai. (2013, January). Fuzzy Time Series Model Based on Fitting Function for Forecasting TAIEX Index. Interntional Journal of Hybrid Information Tecnology, 6(1), 111-121.
Dedrizaldi, E. M., 2019. Anaisis Perencanaan Persediaan Air Mineral dengan Pendekatan Metode Monte Carlo pada PT. Agrimitra Utama Persada. Jurnal Kajian Manajemen dan Wirausaha, 4, No. 2.
Ikhsanudin, A., Santoso, K. I., & Wahyudioo, S., 2022. Metode Fuzzy Time Series Model Chen Untuk Memprediksi Jumlah Kasus Aktif Covid-19 . Jurnal Transformasi (Informasi & Pengembangan IPTEK), 40-53.
Indah, D. R., & Risasti, E. Y., 2017. Analisis Pengendalian Persediaan Bahan Baku pada PT.Tri Agro Palma Tamiang. Jurnal Samudra Ekonomi dan Bisnis, 8, 134-148.
Jamaludin, A., 2017. Peramalan Jumlah Pinjaman Menggunakan Metode Fuzzy Time Series Cheng. SYNTAX Jurnal Informatika, 69-77.
J., Haidar, W. E. & Rustamaji, H. C., 2022. Prediction of IDR- USD Exchange Rate using the Cheng Fuzzy Time Series Method with Particle Swarm Optimization. Internasional Journal of Artificial Inteligence & Robotics, Volume 4, pp. 59-69.
Laily, Y. H., Rakhmawati , F., & Husein, I., 2023. Penerapan Metode Fuzzy Time Series Markov Chain Dalam Peramalan Curah Hujan Sebagai Jadwal Tanaman Padi. Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, 16-174.
Maricar, M. A., 2019. Analisa Perbandingan Nilai Akurasi Moving Average dan Exponential Smoothing untuk Sistem Peramalan Pendapatan pada Perusahaan XYZ. Sistem dan Informatika, 13, 36-45.
Nababan, D., dkk., 2020. Implentasi Metode Fuzzy Time Series dengan Model Algoritma Chen Untuk Memprediksi Harga Emas. Jurnal Teknik Informatika, 13, 71-78.
Nasution, P., Prasetya, N. H., & Rakhmawati, F., 2021. Peramalan Jumlah Penumpang Untuk KA Medan-Kualanamu Dengan Time Invariant Fuzzy Time Series Metode. Jurnal Matematika dan Komputasi Ilmiah dengan Aplikasi, 125-135.
Patria, L., 2021. Fuzzy Time Series Application in Predicting the Number of Confirmation Cases of Covid-19 Patients in Indonesia. International Journal of Quantitative Research and Modeling, Volume 2, pp. 193-200.
Perwira, R. I., dkk., 2020. Fuzzy Time Series Cheng Untuk Meramalkan Volume Hasil Panen Pada Tanaman Garut. Telematika, 17, 11-17.
Rachim, F., Tarno, & Sugito., 2020. Perbandingan Fuzzy Time Series Dengan Metode S.R Singh (Studi Kasus : Nilai Impor di Jawa Tengah Periode Januari 2014 - Desember 2019). Jurnal Gaussian, 9, No. 3, 306-315.
Rachman, R., 2018. Penerapan Metode Moving Average dan Exponential Smoothing pada Peramalan Produksi Industri Garment. Informatika, 211-220.
Rahmawati, Cynhia, E. P., & Susilowati, K., 2019. Metode Fuzzy Time Series Cheng dalam Memprediksi Jumlah Wisatawan di Provinsi Sumatera Barat. Journal of Education Informatic Technology and Science (JeITS), 1, 11-23.
Rasyid, R., Sumarauw, J. S., & D. Palandeng, I., 2016. Analisis Persediaan Air Bersih Di PT. Air Manado. Jurnal EMBA, 206-214.
Ritha, N., Matulatan, T., & Hidayat, R., 2020. Penerapan Fuzzy Time Series Stevenson Porter pada Peramalan Pergerakan Nilai Forex. Seminar Nasional Inovasi Teknologi.
Ronny, Bun Yamin, M. B., Jasman, Rusli, Hari, N. B., & Hari, B. N. (2020). The Combination of Aeration and Filtration System in Reducing Water Pollution: An Experimental Study. International Journal on Advanced Science Engineering Information Technology, 10(5).
Rusli, M., 2017. Dasar Perancangan Kendali Logika Fuzzy. Malang: UB Press.
Sibel, A., Cagdas, H. A., Turhan, M., & Erol, E. (2012). A New Seasonal Fuzzy Time Series Method Based on the Multiplicative Neuron Model And Sarima. Hacettepe Journal of Mathematics and Statistics , 41(3), 337-345.
Sihombing, A. T., 2019. Analisis Kinerja Sistem Distribusi Air Bersih PDAM Tirta Silaupiasa Kabupaten Asahan. Jurnal Pionir LPPM Universitas Asahan, 5, No.2.
Sumartini, Hayati, M. N., & Wahyuningsih, S., 2017. Peramalan Menggunakan Metode Fuzzy Time Series Cheng. Eksponensial, 51-56.
Walid, F. H., Dur, S., & Aprilia, R. (2020). Monte Carlo Simulation In Estimating Clean Water Supplies. Journal of Mathematics and Scientific Computing With Applications, 31-35.
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