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All Journal Media Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Pengabdian Masyarakat Bumi Raflesia Journal of Midwifery Griya Journal of Mathematics Education and Application Journal of Statistics and Data Science
rachmawati, Ramya
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Transportation Other

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Journal : Journal of Statistics and Data Science

 1 
Forecasting A Weekly Red Chilli Price in Bengkulu City Using Autoregressive Integrated Moving Average (ARIMA) and Singular Spectrum Analysis (SSA) Methods Putriasari, Novi; Nugroho, Sigit; Rachmawati, Ramya; Agwil, Winalia; Sitohang, Yosep O
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21007

Abstract

Red chili occupies a strategic position in the Indonesian economic structure because its use applies to almost all Indonesian dishes. Therefore, controlling the price of red chili is anecessity to maintain national economic stability. The purpose of this research is to forecast a red chili weekly price using ARIMA and SSA based on the weekly data of chili prices from January 2016 - December 2019 sourced from Statistics Indonseia (BPS) Branch Office of Bengkulu Province. The data have been analyzed using software R. Based on MAPE, ARIMA (2,1,2) provides the best forecasting with value 0.49% while SSA 10.64%.
Agglomerative Nesting (AGNES) Method and Divisive Analysis (DIANA) Method For Hierarchical Clustering On Some Distance Measurement Concepts Wijuniamurti, Susi; Nugroho, Sigit; Rachmawati, Ramya
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21009

Abstract

Clustering data through hierarchical approach could be performed by Agglomerative Nesting (AGNES) Method and Divisive Analysis (DIANA) Method. The objective of this research is to compare both the methods based on Euclid and Manhattan distance measurements. Of this research the clustering procedures of agglomerative method are conducted by exploring all techniques including single linkage, complete linkage, average linkage, and Ward. The data used are the National Socio-Economic Survey (SUSENAS) data which are selected specifically for the percentage of over 5 year old residents in each province, for both living in urban or rural, who access the internet in the last 3 months in 2017 but classified according purpose of accessing. By applying Mean Square Error (MSE) for 2 and 3 clusters, it can be concluded that the single linkage technique is the best performance of clustering procedure for both Euclidean and Manhattan distances.
A Comparison of Weighted Least Square and Quantile Regression for Solving Heteroscedasticity in Simple Linear Regression Fransiska, Welly; Nugroho, Sigit; Rachmawati, Ramya
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21011

Abstract

Regression analysis is the study of the relationship between dependent variable and one or more independent variables. One of the important assumption that must be fulfilled to get the regression coefficient estimator Best Linear Unbiased Estimator (BLUE) is homoscedasticity. If the homoscedasticity assumption is violated then it is called heteroscedasticity. The consequences of heteroscedasticity are the estimator remain linear and unbiased, but it can cause estimator haven‘t a minimum variance so the estimator is no longer BLUE. The purpose of this study is to analyze and resolve the violation of heteroscedasticity assumption with Weighted Least Square(WLS) and Quantile Regression. Based on the results of the comparison between WLS and Quantile Regression obtained the most precise method used to overcome heteroscedasticity in this research is the WLS method because it produces that is greater (98%).
Forecasting A Weekly Red Chilli Price in Bengkulu City Using Autoregressive Integrated Moving Average (ARIMA) and Singular Spectrum Analysis (SSA) Methods Putriasari, Novi; Nugroho, Sigit; Rachmawati, Ramya; Agwil, Winalia; Sitohang, Yosep O
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Red chili occupies a strategic position in the Indonesian economic structure because its use applies to almost all Indonesian dishes. Therefore, controlling the price of red chili is a necessity to maintain national economic stability. The purpose of this research is to forecast a red chili weekly price using ARIMA and SSA based on the weekly data of chili prices from January 2016 - December 2019 sourced from Statistics Indonseia (BPS) Branch Office of Bengkulu Province. The data have been analyzed using software R. Based on MAPE, ARIMA K (2,1,2) provides the best forecasting with value 0.49% while SSA 10.64%.
Co-Authors Agwil, Winalia Alwansyah, Muhammad Arib APRIANISA, TRI Asmariyah Deni Maryani Dewiani, Kurnia Firdaus Fransiska, Welly Novianti Novianti Nur Afandi Nurul Hidayati Putriasari, Novi Saniyyah, Nabilah Sarumpaet, Mey Yanti Septri Damayanti Sigit Nugroho Siska Yosmar Sitohang, Yosep O Suriyati, Suriyati Widayati, Ratna Wijuniamurti, Susi Yusanti, Linda