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All Journal Hemera Zoa JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Agro Ekonomi JTSL (Jurnal Tanah dan Sumberdaya Lahan) Jurnal Agro Ekonomi Jurnal Pusat Inovasi Masyarakat Xplore: Journal of Statistics Indonesian Journal of Statistics and Its Applications
Rahma Anisa
Department Of Statistics, IPB University, Bogor, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Mathematics Social Sciences Other

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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 : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

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 : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

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.
Co-Authors . Erfiani A.S. Satyaningtijas Aam Alamudi Abdullah Ilman Fahmi Aidi, Muhammad N Alina Witri Anang Kurnia Andhika Yudha Prawira Andhika Yudha Prawira Andhika Yudha Prawira Ani Safitri Anik Djuraidah Annisa Nur Hapsari Aurellia Layvieda Bagus Sartono Budi Susetyo Danang Dwi Cahyadi Desrayni Hanadhita Desrayni Hanadhita Desrayni Hanadhita Desrayni Hanadhita Dian Kusumaningrum Fahrizal Hazra Fajar Agus Pradana Haidar Muhammad Yasin Haryastuti, Rizqi HERA MAHESHWARI Herwin Pisestiyani I Made Sumertajaya Indonesian Journal of Statistics and Its Applications IJSA Latief Mahir Rachman Mely Amelia Muhammad N Aidi Muhammad Nur Aidi Nur Indah Andini Nur Laela Fitriani Pasaribu, Sahat M. Pika Silvianti Pika Silvianti Putu Gita Karlina Jayanti Qomsatun Istiqomah Rama Adi Rianto Rizqi Haryastuti Ryska Putri Madyasari Sahat M. Pasaribu Sandra Dewi Hartanti SATRIYAS ILYAS Savitri Novelina Srihadi Agungpriyono Supratikno . Sutomo, Valantino A Valantino A Sutomo Valantino Agus Sutomo Wulan Andriyani Pangestu Yani Nurhadryani