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All Journal FORUM STATISTIKA DAN KOMPUTASI Jurnal Media Infotama Indonesian Journal of Statistics and Its Applications
Cici Suhaeni
Institut Pertanian Bogor (IPB)
Computer Science & IT Mathematics Other

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PENDUGAAN SELANG KEPERCAYAAN BOOTSTRAP BAGI ARAH RATA-RATA DATA SIRKULAR (Bootstrap Confidence Interval Estimation of Mean Direction for Circular Data) Cici Suhaeni; I Made Sumertajaya; Anik Djuraidah
FORUM STATISTIKA DAN KOMPUTASI Vol. 17 No. 2 (2012)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (570.579 KB)

Abstract

The confidence interval is an estimator based on the sampling distribution. When the sampling distribution can not be derived from population distribution, the bootstrap method can be used to estimate it. Three methods used to estimate the bootstrap confidence interval for circular data were equal-tailed arc (ETA), symmetric arc (SYMA), and likelihood-based arc (LBA). In this study, three methods were evaluated through simulation study. The most important criterion to evaluate them were true coverage and interval width. The simulation results indicated in all methods, the interval width shortened when the concentration parameter increased. True coverage approached confidence level when the concentration parameter were one or more. For small concentration parameter, all three methods appeared unstable. Based on the true coverage, SYMA was the best, while in terms the interval width, LBA was the best one. For both criterion could be summarized that ETA is the best result. ETA applicated for estimate the period of Dengue Fever outbreaks in Bengkulu. The estimation showed that Dengue Fever outbreaks in 2009 were October through January. In 2010, it were January through March, and in 2011, it were June through September.Keywords : Circular, Bootstrap confidence interval, Equal-tailed arc, Symmetric arc, Likelihood-based arc.
Perbandingan Hasil Pengelompokan menggunakan Analisis Cluster Berhirarki, K-Means Cluster, dan Cluster Ensemble (Studi Kasus Data Indikator Pelayanan Kesehatan Ibu Hamil) Cici Suhaeni; Anang Kurnia; Ristiyanti Ristiyanti
Jurnal Media Infotama Vol 14 No 1 (2018)
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (398.364 KB) | DOI: 10.37676/jmi.v14i1.469

Abstract

Pengelompokan merupakan kegiatan di bidang riset yang banyak digunakan hingga saat ini. Terlebih di era big data seperti sekarang. Banyak metode yang berkembang untuk keperluan tersebut. Penelitian ini membandingkan hasil pengelompokan menggunakan metode cluster hierarki, k-means cluster, dan cluster ensemble pada pengelompokan provinsi di Indonesia berdasarkan indikator pelayanan kesehatan ibu hamil. Hasil analisis menunjukkan bahwa cluster ensemble merupakan metode yang paling tepat dalam mengelompokkan provinsi-provinsi tersebut. Cluster yang dihasilkan adalah 3 (tiga) cluster. Kata Kunci: analisis cluster, cluster ensemble, cluster hierarki, k-means cluster.
KAJIAN SIMULASI PENDUGAAN SELANG KEPERCAYAAN BOOTSTRAP BAGI ARAH MEDIAN DATA SIRKULAR Cici Suhaeni; I Made Sumertajaya; Anik Djuraidah
Indonesian Journal of Statistics and Applications Vol 2 No 1 (2018)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v2i1.64

Abstract

The median direction is one of central tendency of circular data. The estimation process usually requires information about sampling distribution of statistic that want to be used as a parameter estimate. Theoretically, sampling distribution derived from population distribution. But, it is not easy to get sampling distribution of median although the population distribution is known. When the sampling distribution cannot be derived easily from population distribution, the bootstrap method can be an alternative to handle it. This study wants to evaluate the effect of increasing concentration parameter to the performance of bootstrap confidence interval estimation for median direction through simulation study. Three methods were used to estimate the interval which are equal-tailed arc (ETA), symmetric arc (SYMA), and likelihood-based arc (LBA). The most important criterion to evaluate them were true coverage and interval width. The simulation results that in general, the increasing of concentration parameter followed by more narrow interval. For small concentration parameter (k<1), all methods give unstable true coverage and interval width. The authors also identify that those three methods produce intervals with identical width when the parameter concentration is 20 or more. In terms of coverage and interval width, the best method was ETA.
Co-Authors Anang Kurnia Anik Djuraidah I Made Sumertajaya Ristiyanti Ristiyanti