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All Journal Enthusiastic : International Journal of Applied Statistics and Data Science Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Lazuardy Ilham Effendie
Universitas Islam Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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PERBANDINGAN ANALISIS PERAMALAN DOUBLE EXPONENTIAL SMOOTHING DAN TRIPLE EXPONENTIAL SMOOTHING PADA INDEKS HARGA KONSUMEN DI YOGYAKARTA Lazuardy Ilham Effendie; Utami Putri Wysnawati; Qurratul Ainunnisa
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 3 No. 1 (2023): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (337.025 KB) | DOI: 10.46306/bay.v3i1.54

Abstract

The Consumer Price Index, commonly known as the CPI, is an index derived from calculating the average price change of a good and service in a period consumed by the population for a certain period of time. The CPI is a vital indicator used in calculating inflation, and inflation plays an important role in the economy. Thus, the CPI movement greatly affects the cost of living needed by each citizen for goods and services consumed and can provide an overview of inflation or deflation. This paper aims to provide a future picture to the government to provide an upcoming policy and show that it needs special attention for all circles. The data used in this research is the CPI in DI Yogyakarta from January 2012 to April 2022. The CPI data from January 2012 to April 2022 is forecasted using two methods, namely Double Exponential Smoothing and Triple Exponential Smoothing. MSE (Mean Square Error) and MAPE (Mean Absolute Percentage Error). Then the two methods are compared, and the best method is Double Exponential Smoothing with the MAPE value is 0.976, the MAPE value <10% means that forecasting with Double Exponential Smoothing can be said to be good and can be used
MSME Sales Clustering Based on Business Aid Distribution Priority Using K-Affinity Propagation Tarisya Qurrota A'yuni; Baiq Nina Febriati; Lazuardy Ilham Effendie; Muhammad Muhajir; Rahmadi Yotenka
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol3.iss1.art10

Abstract

In rural areas of Indonesia, micro, small, and medium enterprises (MSMEs) are often isolated; however, they have been proven to play an important role as the economic backbone of millions of communities. In fact, the sluggish development of MSMEs in Indonesia become a severe problem for the community welfare. The government continues to strive for the welfare of the local communities, one of which is by supporting the existing MSMEs. However, the provision of government assistance may not be optimal for the incorrect target of the MSMEs. This study informs the government and other related parties regarding subdistrict groups whose MSMEs are considered to be their target. The k-affinity propagation method was used to find a set of representative examples, called exemplars, that best summarize the data. The result shows that sub-districts clusters based on general welfare in five commodities. K-affinity propagation algorithm clusters vary by commodity. Data fluctuation from each commodity’s three factors causes this. From this research, it can be determined which subdistricts have the most or least prosperous MSMEs in each of the five commodities analyzed.
Co-Authors Baiq Nina Febriati Muhammad Muhajir, Muhammad Qurratul Ainunnisa Rahmadi Yotenka Tarisya Qurrota A'yuni Utami Putri Wysnawati