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Analisis Kepuasan Pelayanan dan Literasi TIK Pengunjung Dinas-Dinas di Kota Bogor Ryska Putri Madyasari; Anang Kurnia; Rahma Anisa; Yani Nurhadryani
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.v8i1.152

Abstract

Determining Public Satisfaction Index using analysis of Importance Performance Analysis (IPA) and Customer Satisfaction Index (CSI) can be utilized to improve service quality of Governmental Departments in X City. Analysis of IPA and CSI were used to measure the level of respondents’ satisfaction regarding the provided services. The departments were selected using purposive sampling method. Four selected departments were Population and Civil Registry Department, Transportation Department, Housing and Settlement Department, and Social Department. The result showed that customers were moderately satisfied with the services, with the following CSI index value: 70.09%, 72.95%, and 76.61% respectively for each departments. Moreover, Social Department’s customers were very satisfied with the CSI index 81.56%. In this study, aspect of Information and Communication Technology (ICT) literacy indicator were more exposing the ability to operate personal computer. There were six indicator of ICT literacy, i.e access, manage, integrate, evaluate, create, and communication. The value of evaluate indicator were quite high, it has reached score higher than 50% for each departments were. However, based on overall score, it was shown that 60% respondents still have low ICT literacy. This study also showed that ICT literacy were related to responden’s education and age. It increased along with the higher level of education that has been completed by respondents, and with the age of 17-39 years old.
Seleksi Peubah menggunakan Algoritme Genetika pada Data Rancangan Faktorial Pecahan Lewat Jenuh Dua Taraf Ani Safitri; Rahma Anisa; Bagus Sartono
Xplore: Journal of Statistics Vol. 10 No. 1 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (606.618 KB) | DOI: 10.29244/xplore.v10i1.473

Abstract

In certain fields, experiments involve many factors and are constrained by costs. Reducing runs is one of the solutions to reduce experiment costs. But that can cause the number of runs to become less than the number of factors. This case of experimental design also is known as a supersaturated design. The important factors in this design are generally estimated by involving variable selection such as forward selection, stepwise regression, and penalized regression. Genetic algorithm is one of the methods that can be used for variable selection, especially for high dimensional data or supersaturated design. This study aims to use a genetic algorithm for variable selection in the supersaturated design and compare the genetic algorithm results with a stepwise regression which is generally used for a simple design. This study also involved fractional factorial design principles. The result showed that the main factors and interactions of the genetic algorithm and stepwise regression were quite different. But the principle was the same because the variables correlated. The genetic algorithm model had a smaller AIC and BIC and all of the main factors and interactions which had chosen were significant on the 0.1%. Therefore genetic algorithm model was chosen although computation time was much longer than stepwise regression.
PENDUGAAN FAKTOR – FAKTOR YANG MEMENGARUHI KASUS STUNTING DI JAWA BARAT TAHUN 2021 MENGGUNAKAN REGRESI SPASIAL BINOMIAL NEGATIF Anik Djuraidah; Mely Amelia; Rahma Anisa
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 1 (2023): SEPTEMBER, 2023
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i1.26984

Abstract

Stunting is a childhood growth and development disorder characterized by below-normal height.  West Java, with its stunting rate of 24.5 percent, is one of the provinces included in the top 12 priority provinces in implementing the National Action Plan to Accelerate Stunting. Stunting cases are count data and their occurrence is rare. The analysis for the count data is Poisson regression with the assumption that equidispersion must be met. One way to overcome overdispersion is to use negative binomial regression. This study aimed to determine predictors/factors affecting stunting cases in West Java province in 2021 using negative binomial spatial regression. The data in this study comes from the publication of the West Java Health Service and the West Java Central Statistics Agency in 2021 with districts/cities as the object of observation. There is a spatial effect in the stunting data, so the spatial regression model is suitable. The results show that there is an overdispersion in the Poisson regression. The spatial effect test shows that there is a spatial dependence on the response variable and some predictors. The negative spatial autoregressive binomial is the best model with the lowest AIC value. The factors that have a significant effect are the percentage of infants aged less than six months who are breastfed, the percentage of food processing establishments that meet the requirements, and the percentage of infants with low birth weight.
Determining Critical Yield Index of Area Yield Insurance based on Basis Risk Constraint Valantino Agus Sutomo; Dian Kusumaningrum; Aurellia Layvieda; Rahma Anisa
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
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.v5i1p205-219

Abstract

 Area yield index insurance at district level faces heterogeneous basis risk due to geographical conditions which implies to obtain unprecise critical index . Clustering and zone-based area yield scheme can reduce heterogeneous basis risk that leads to determine the suitable alternative for . On the previous research, we have obtained 7 clusters and 2 level of paddy productivity based on clustering assumption from primary data in Java. The suitable clustering assumption for calculating  is cluster based assumption, which gives the homogeneous paddy productivity under 7 clusters in Java. Therefore, our goal is to develop area yield index at district level (cluster based) with minimize basis risk at certain constraints for paddy farmer productivity in Java Indonesia. There are some methods for calculating  such as mean, median, winsor mean, one sigma, two sigma and  (first quartile) method on the basis risk constraints using confusion matrix. Furthermore, two basis risk constraints are the difference between overpayment and shortfall is not extremely far, and total basis risk does not exceed 20% of its total claim occurrence. Two sigma method has the lowest basis risk, overpayment, and shortfall, but it has lowest pure premium, small probability of claim, and low range of claim. Hence, we consider to use  (first quartile) method as alternative and suitable method to calculate  that satisfied two basis risk constraints. In conclusion, our research provides analytical calculation for area yield index at district level with pure premium as Rp 152,151 using  ( method), which is sufficient to cover the total claim and consistent with the simulation.
Nested Mixed Models with Repeated Measurements for Analyzing Gross Profit of Public Companies in West Java: Model Campuran Tersarang dengan Pengamatan Berulang untuk Analisis Data Laba Bruto Perusahaan Terbuka di Jawa Barat Alina Witri; Khairil Anwar Notodiputro; Rahma Anisa
Indonesian Journal of Statistics and Applications Vol 6 No 2 (2022)
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.v6i2p296-308

Abstract

The company's gross profit plays an important role in boosting the Gross Regional Domestic Product (PDRB) which will affect the revenue of local governments, known as Pendapatan Asli Daerah. Local governments often need information how gross profits of companies are different within each sector. It is not easy to investigate this matter especially if these companies are observed repeatedly and subsectors are nested within the sector. In this study, three factors were involved, i.e., sectors, subsectors which are nested in a particular sector, and time. It is assumed that the sectors and time of observation are fixed, whereas the subsectors are random. The response variable is the average gross profit per subsector of public companies in West Java. The objective of this study is to identify the variation of the subsectors, the effects of sectors as well as time on the average of the gross profit. Since the study involves fixed and random factors and the gross profit rate was observed more than one time, then a nested mixed model with repeated measurement is used. The results showed that there was no sector effect on the average gross profit, there is a variation in the average gross profit per subsector that is nested within the sector, and the time of observation did not influence the average gross profit.