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All Journal FORUM STATISTIKA DAN KOMPUTASI Jurnal Gaussian Jurnal Media Infotama Indonesian Journal of Applied Statistics BAREKENG: Jurnal Ilmu Matematika dan Terapan IJID (International Journal on Informatics for Development) Xplore: Journal of Statistics Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications Diophantine Journal of Mathematics and Its Applications

Cici Suhaeni

Statistics And Data Science, School Of Data Science, Mathematics, And Informatics, IPB University, Indonesia

Author-ID : 3379219

Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Transportation 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)

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

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.

Perbandingan Metode Dalil Limit Pusat Transformasi dan Resampling Bootstrap dalam Pembentukan Selang Kepercayaan Yuli Eka Putri; Kusman Sadik; Cici Suhaeni
Xplore: Journal of Statistics Vol. 2 No. 2 (2018): 31 Agustus 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v2i2.108

YULI EKA PUTRI. A Comparative Study of Central Limit Theorem, Transformation and Bootstrap Resampling in Determining Confidence Interval. Supervised by KUSMAN SADIK and CICI SUHAENI. The confidence interval is usually established under normality assumption. But, many real-life data does not belong to normal distribution. Many of them are skewed, such as chi-square distribution, generalized extreme value (GEV) or other distribution. For such data, we can use central limit theorem, transformation and bootstrap resampling method to construct confidence intervals. The performance of the methods in constructing the interval can be evaluated using confidence interval accuracy value, interval width, and standard deviation of the interval width. Thus we can determine the best method. The method is determined for having better performance if it has higher accuracy value, smaller interval width, and smaller standard deviation of interval width.This research use both simulated and real-life data. Simulated data is generated from the chi-square distribution, GEV and modified non-normal distribution. The modified non-normal distributed data is a modification of normal distributed data using quadratic and logaritm transformation. So that the data is no longer normally distributed. The results show that transformation method is well used for small sample sizes. Bootstrap resampling dan central limit theorem are better used for large sample sizes.

Two Step Method for Clustering Mixed Data untuk Menggerombolkan Toko Mainan Anak Digital Muhammad Shalih; Cici Suhaeni; Septian Rahardiantoro
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.131

The development of digital trading system today, triggering the proliferation of shops that sell various needs in various marketplace. This is supported by the large number of internet users in Indonesia that facilitate the store with commercial-based digital to reach market share. One of the growing categories in a marketplace is the stores that sell toys. However, not all toy stores have a good reputation. Clustering based on store reputation indicators can be done to find out how the condition of toy stores in a marketplace. The store reputation indicators used are categorical and numerical scale variables. This study uses A Two-Step Method for Mixed Categorical and Numerical Data (TMCM), which is a clustering method that can cluster mixed numerical and categorical data that using a co-occurence concept. The result of this clustering found that the optimal number of cluster is five cluster based on the maximum value of Pseudo-F and the minimum value of ratio (R ).

Deteksi Titik Panas dan Pola Spasio-Temporal Kejadian Penyakit Demam Berdarah Dengue Di DKI Jakarta Rere Kautsar; Bagus Sartono; Cici Suhaeni; Bimandra Adiputra Djaafara
Xplore: Journal of Statistics Vol. 8 No. 1 (2019): 30 April 2019
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v8i1.138

Dengue virus is one of the causes of infectious diseases in human with mosquitoes as vector of transmission. In Jakarta, dengue infection is still one of the most important health problems, particularly its severe clinical manifestation which is known as dengue hemorrhagic fever (DHF). Spatio-temporal approach was used in this research to analyze the spatial pattern of DHF spread in Jakarta. The data used for analysis are consisted of total number of people suffering from DHF in Jakarta at the sub-district per week, monthly total precipitation, and the total population each sub-district in DKI Jakarta per year since 2008 until 2016. Incidence rate of dengue fever in Jakarta tend to be higher in March to April period compared to the other months. The spread of DHF burden tend to be clustered during the period of 2008 until 2011 whereas in the next five years, clustered pattern was not observed. The hotspots of DHF cases were more likely to occur in the north, east, and south part of DKI Jakarta.

Pemodelan Faktor Risiko Penyakit Campak pada Balita di Provinsi DKI Jakarta: Pemodelan Faktor Risiko Penyakit Campak pada Balita di Provinsi DKI Jakarta Ayu Annisa Rahmah; Itasia Dina Sulvianti; Cici Suhaeni; Bimandra Adiputra Djaafara
Xplore: Journal of Statistics Vol. 9 No. 1 (2020)
Publisher : Department of Statistics, IPB

Measles is one of the infectious caused by virus. The disease is easily transmitted and has become one of the main causes of child mortality especially toddlers. In 2016, Jakarta experienced the highest measles case in the last ten years and found the difference in the number of measles cases in each sub-district of Jakarta. This can be caused by the existence of effect of spatial location i.e. spatial heterogeneity. Geographically weighted regression (GWR) is a method that can be applied to address the presence of spatial heterogeneity in the process of developing the model. In this study, the weighting function used was the Gaussian kernel. The modelling process generated 42 local models at sub-district level. Explanatory variables that influence the incidence rate of measles in toddlers (Y) signiï¬cantly are the percentage of immunization coverage measles (X1), the total annual rainfall (X4), and the percentage of the number of toddlers (X5). In this study, the GWR model is better than multiple linear regression model which were indicated by higher value of and smaller value of AIC.

Penggerombolan Babyshop pada Marketplace X Menggunakan Cluster Ensemble berbasis Algoritme Squeezer Gita Lestari; Cici Suhaeni; Pika Silvianti
Xplore: Journal of Statistics Vol. 8 No. 1 (2019): 30 April 2019
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v8i1.202

Marketplace is one of the most popular digital business in Indonesia. One of the category that grow in Marketplace X is shops that sell baby equipment or better known as babyshop. In order to provide the best service and keep the credibility of babyshop specialty shops, important to do qualitry monitoring on of them through clustering. Clustering based on store reputation assessment indicators consisting of variables that are categorical and numerical in scale. This study aims to classify babyshop on Marketplace X based on the characteristics of the store using cluster analysis with cluster ensemble based mixed data clustering (CEBMDC) based on the weigthed squeezer algorithm. This study use the stream data from 218 babyshop at Marketplace X which consists of service factors, reputation level, type and location of the babyshop. The optimal cluster results was into three clusters in which cluster one consists of 21% babyshop, cluster two 48% babyshop, and 31% babyshop at cluster three. The first cluster is a cluster with the tendency of the babyshop to be classified as good, the cluster two tend to have a normal (neutral) reputation, while members of cluster three has a for poor reputation.

METODE CART UNTUK MENGIDENTIFIKASI FAKTOR-FAKTOR YANG MEMENGARUHI WAKTU PEMBELIAN KENDARAAN KEDUA Eka Setiawaty; Farit Mochamad Afendi; Cici Suhaeni
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

Increased competition between personal vehicle dealers make them need strategies to hold their customers and increase their sales. One of the strategies they could apply is prospecting their customers at the right time. We could predict the right time by identifying the relationship between the length of their purchase time and its factors based on the transaction data of Z Company from year 2002 to 2015 using Classification and Regression Trees (CART). Data analysis is separated between groups of customers who made the second purchase maximum of 10 years after the first purchase (group A) and more than 10 years after the first purchase (group B). Group Aâ€™s regression tree produces 8 terminal nodes with MAD value 1.84 years. The independent variables that plays a role are tenor, job, age, and brand. Group Bâ€™s regression tree produces 4 terminal nodes. Authorized service and job come out as independent variables which affect the splitting process. MAD value for Group Bâ€™s regression tree is 0.56 years.

Evaluasi Produk Multivitamin Baru Berdasarkan Penilaian Responden Noer Endah Islami; Utami Dyah Syafitri; Cici Suhaeni
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

In order to lead in the market, companies should have an innovation product. Before the innovation product lauch to the market, the marketing research should be done. The goal of the reasearch is to determine whether the new product is accepted or rejected in the market. This study was to identify the characteristics of the new product based on organoleptic point of view and performance the three type of new multivitamin products based on location and social economic classes (SEC) of respondents. MANOVA and biplot analysis were used in this research. Based on MANOVA, there were differences on the organoleptic point of view of respondents among three type of new multivitamin products. The three products had differences on the assessment of aroma, sour taste, and sour after taste. In addtion with biplot analysis, it was concluded that each product had different location for sale and the target of respondents based on sosial economic classes. According to respondents, product A was too sweet taste and too sour after taste in the mouth compared to others. This product was preferred by respondents who reside in South Jakarta with social economic classes (SEC) A2 and C1. Unlike product A, product B was too hard with a bit of bitter after taste in the mouth. This product was relatively preferred by respondents in various residential with social economic classes (SEC) B. Product C was strong aroma with smooth texture and more bitter taste than others. This product was preferred by respondents who reside in North Jakarta and Depok with social economic classes (SEC) A1. Overall, product B was preferred by respondents compared to other products.

Penggerombolan Daerah 3T di Indonesia Berdasarkan Rasio Tenaga Kesehatan dengan Metode Penggerombolan Berhierarki dan Cluster Ensemble Kesuma Millati; Cici Suhaeni; Budi Susetyo
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

Health is a major factor in community development. Inequality on health is most felt by people living in disadvantaged, outermost, and leading areas (3T) because of the difficulty of access to transportation and communication. Effective efforts are needed to achieve the optimal distribution of health services, one of which is by clustering 3T areas based on the ratio of health workers to see which areas are experiencing shortage of health workers and know the adequacy of the number of health workers spread in 3T areas. The object used in this research is 27 provinces 3T region in Indonesia and the applied statistical method is various hierarchical methods and Cluster Ensemble. Based on the results of this study, 3T area is divided into four clusters. The first cluster consists of 22 provinces and has good characteristics because all categories of the variables are in the medium category. The second and the third cluster consists of two provinces. The characteristics of the second cluster are good enough. The characteristics of the third cluster are not been good enough because there is one variable in the low category. The fourth cluster consists of one province and has characteristics that are not been good enough because there are several categories of the variables are in the low category.

Co-Authors Adib Roisilmi Abdullah Agus M Soleh Agus M. Soleh Agus Mohamad Soleh Agus Muhammad Saleh Anang Kurnia Anik Djuraidah Ayu Annisa Rahmah Bagus Sartono Bimandra Adiputra Djaafara Bimandra Adiputra Djaafara Budi Susetyo Eka Setiawaty Fani Fahira Fani Fahira Farit Mochamad Afendi Fitrianto, Anwar Gerry Alfa Dito Gita Lestari Hari Wijayanto Hwan-Seung Yong I Made Sumertajaya Itasia Dina Sulvianti Jefita Resti Sari Kesuma Millati Kusman Sadik La Ode Abdul Rahman Laily Nissa Atul Mualifah Muhammad Shalih Muhammad Yusran Naufalia Alfiryal Noer Endah Islami Panji Lokajaya Arifa Pika Silvianti Rahardiantoro, Septian Rere Kautsar Ristiyanti Ristiyanti Sabrina Adnin Kamila Sabrina Adnin Kamila Uswatun Hasanah Utami Dyah Syafitri Yuli Eka Putri

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