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All Journal Xplore: Journal of Statistics
Cici Suhaeni
Department of Statistics, IPB
Decision Sciences, Operations Research & Management Engineering Mathematics

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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

Abstract

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

Abstract

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

Abstract

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.
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

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (789.92 KB) | DOI: 10.29244/xplore.v10i2.237

Abstract

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 A’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 B’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 B’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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (807.521 KB) | DOI: 10.29244/xplore.v10i2.244

Abstract

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.
Co-Authors Bagus Sartono Bimandra Adiputra Djaafara Eka Setiawaty Farit Mochamad Afendi Gita Lestari Kusman Sadik Muhammad Shalih Noer Endah Islami Pika Silvianti Rahardiantoro, Septian Rere Kautsar Utami Dyah Syafitri Yuli Eka Putri