Model Hybrid untuk Prediksi Jumlah Penduduk yang Hidup dalam Kemiskinan

Toni Wijanarko Adi Putra^1*, Solikhin Solikhin², M Zakki Abdillah³

Abstrak

Kemiskinan merupakan permasalahan global yang saling berkaitan dengan permasalahan sosial lainnya. Sebagian besar negara berkembang di dunia pasti mengalami hal tersebut dan berusaha mencari solusi untuk mengentaskan kemiskinan, seperti yang terjadi di provinsi Jawa Tengah, Indonesia. Kemiskinan di Jawa Tengah mengalami fluktuasi selama lima tahun terakhir. Secara spesifik, menurut data Badan Pusat Statistik, jumlah penduduk miskin pada tahun 2018, 2019, 2020, 2021, dan 2022 sebanyak 3.897,20 ribu, 3.743,23 ribu, 3.980,90 ribu, 4.109,75 ribu, dan 3.831,44 ribu jiwa. Tinjauan terhadap naik turunnya kemiskinan pada tahun-tahun mendatang sangatlah penting. Untuk memerangi kemiskinan secara efektif, tidak hanya memahami penyebab kemiskinan tetapi memprediksi kemiskinan juga sangatlah penting. Penelitian ini bertujuan untuk memprediksi garis kemiskinan, jumlah penduduk miskin, dan persentase penduduk miskin di Jawa Tengah. Penelitian ini mengusulkan model peramalan hybrid untuk memperkirakan perubahan kemiskinan di Jawa Tengah. Di sini kami mengintegrasikan teknik statistik Holt-Winter triple exponential smoothing ke dalam fuzzy time series dengan pendekatan algoritma rate of change. Hasil uji kesalahan prediksi dengan metode Mean Absolute Percentage Error sangat kecil yaitu: garis kemiskinan sebesar 0,003%, jumlah penduduk miskin sebesar 0,005%, dan persentase penduduk miskin sebesar 0,004%. Temuan penelitian ini diyakini akan membantu pembuat kebijakan dalam mengembangkan strategi efektif untuk memerangi kemiskinan. Pengetahuan ini dapat menjadi dasar pengambilan keputusan alokasi sumber daya bagi pemerintah daerah dan pusat serta pembuat kebijakan.

 Abstract

Poverty is a global problem that is interconnected with other social problems. Most developing countries in the world certainly experience this and are trying to find solutions to alleviate poverty, as is the case in the province of Central Java, Indonesia. Poverty in Central Java has fluctuated over the last five years. Specifically, according to data from the Central Statistics Agency, the number of poor people in 2018, 2019, 2020, 2021, and 2022 is 3,897.20 thousand, 3,743.23 thousand, 3,980.90 thousand, 4,109.75 thousand, and 3,831.44 thousand people. A review of the rise and fall of poverty in the coming years is very important. To fight poverty effectively, not only understanding the causes of poverty but also predicting poverty is essential. The aim of this research is to predict the poverty line, number of poor people, and percentage of poor people in Central Java. This research proposes a hybrid forecasting model to estimate changes in poverty in Central Java. Here we integrate Holt-Winter's triple exponential smoothing statistical technique into fuzzy time series with a rate of change algorithm approach. The prediction error test results using the Mean Absolute Percentage Error method are very small, namely: the poverty line is 0.003%, the number of poor people is 0.005%, and the percentage of poor people is 0.004%. It is believed that the findings of this research will assist policymakers in developing effective strategies to combat poverty. This knowledge can be the basis for resource allocation decisions for local and central governments and policymakers.

DOI : https://doi.org/10.25126/jtiik.1067484

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