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Enoni Febrila Telaumbanua
Universitas Samudra
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Public Health

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PERAMALAN JUMLAH PENDUDUK MISKIN DI KABUPATEN ACEH TAMIANG MENGGUNAKAN METODE EXPONENTIAL SMOOTHING Enoni Febrila Telaumbanua; Nurviana Nurviana
JURNAL GAMMA-PI Vol 4 No 01 (2022): Jurnal Gamma-Pi (Matematika dan Pendidikan Matematika)
Publisher : Program Studi Matematika, Fakultas Teknik, Universitas Samudra. Langsa, Aceh.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/jgp.v4i01.5516

Abstract

Kemiskinan dapat mempengaruhi berbagai aspek kehidupan, seperti meningkatnya kriminalitas, tingginya angka kematian, akses pendidikan tertutup dan meningkatnya pengangguran. Tujuan dari penelitian ini adalah untuk peramalan jumlah penduduk miskin di Kabupaten Aceh Tamiang tahun 2022-2025. Data yang digunakan adalah data tahunan dengan jenis data adalah data sekunder yang diperoleh dari Badan Pusat Statistik Kabupaten Aceh Tamiang. Metode peramalan exponential smoothing terbagi menjadi tiga yaitu single exponential smoothing, double exponential smoothing dan triple exponential smoothing. Berdasarkan analisa data yang telah dilakukan, diketahui bahwa data tidak stasioner, memiliki unsur trend dan tidak dipengaruhi musiman. Sehingga metode peramalan yang tepat digunakan adalah double exponential smoothing, dengan menggunakan dua parameter yaitu dan . hasil forecasting dengan metode ini untuk tahun 2022-2025 berturut-turut 39.32 ribu jiwa, 38.80 ribu jiwa, 38.27 ribu jiwa dan 37.74 ribu jiwa. Dalam hal ini hasil forecasting mengalami penurunan secara terus-menerus setiap tahunnya. Kata kunci : Kemiskinan, peramalan, metode exponential smoothing.
PERBANDINGAN UJI AKURASI FUZZY TIME SERIES MODEL CHENG DAN MODEL LEE DALAM FORECASTING JUMLAH PRODUKSI KELAPA SAWIT DI PROVINSI SUMATERA UTARA Nurviana; Riezky Purnama Sari; Enoni Febrila Telaumbanua
JURNAL GAMMA-PI Vol 8 No 1 (2026): Jurnal Gamma-Pi (Matematika dan Pendidikan Matematika)
Publisher : Program Studi Matematika, Fakultas Teknik, Universitas Samudra. Langsa, Aceh.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/gamma-pi.v8i1.13391

Abstract

Palm oil is a plantation commodity that demonstrates strong resilience during economic crises and serves as one of Indonesia’s major sources of foreign exchange. In North Sumatra Province, palm oil production has shown a steady increase over the past five years, with a cultivated area reaching 490.16 thousand hectares. This study aims to forecast the amount of palm oil production in the province using the fuzzy time series method, which applies the concept of fuzzy sets as its analytical foundation. Several fuzzy time series models, including the Cheng and Lee models, are compared to determine the model that produces the smallest forecasting error based on the criteria of MAE, MSE, MPE, and MAPE. The forecasting results with Cheng's fuzzy time series were 7270.418 thousand tons, while the forecasting results with Lee's fuzzy time series were 7275.425 thousand tons. The results of the analysis of the accuracy level of the MAE value for the Cheng model are 1293.873 and the Lee model is 1463.606, the MSE value for the Cheng model is 5,885,351.768 and the Lee model is 6,304,592.844, the MPE value for the Cheng model is -0.016% and the Lee model is -0.225%, and The MAPE value for the Cheng model is 0.345% while the Lee model is 0.423%. So it was concluded that Cheng's fuzzy time series method was stated to be better for forecasting the amount of palm oil production in North Sumatra province because it produced smaller error values.
Co-Authors Nurviana Riezky Purnama Sari