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Inferensi
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : 0216308X     EISSN : 27213862     DOI : http://dx.doi.org/10.12962/j27213862
Core Subject : Science, Education, Social, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences
The aim of Inferensi is to publish original articles concerning statistical theories and novel applications in diverse research fields related to statistics and data science. The objective of papers should be to contribute to the understanding of the statistical methodology and/or to develop and improve statistical methods; any mathematical theory should be directed towards these aims; and any approach in data science. The kinds of contribution considered include descriptions of new methods of collecting or analysing data, with the underlying theory, an indication of the scope of application and preferably a real example. Also considered are comparisons, critical evaluations and new applications of existing methods, contributions to probability theory which have a clear practical bearing (including the formulation and analysis of stochastic models), statistical computation or simulation where the original methodology is involved and original contributions to the foundations of statistical science. It also sometimes publishes review and expository articles on specific topics, which are expected to bring valuable information for researchers interested in the fields selected. The journal contributes to broadening the coverage of statistics and data analysis in publishing articles based on innovative ideas. The journal is also unique in combining traditional statistical science and relatively new data science. All articles are refereed by experts.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 7 Documents
 1 
Search results for , issue "Vol 6, No 2 (2023)" : 7 Documents clear
Pemetaan Risiko Relatif Kasus Demam Berdarah Dengue di Kota Makassar Menggunakan Model Bayesian Spasial Andi Feriansyah; Idul Fitri Abdullah; Siti Choirotun Aisyah Putri; Mardatunnisa Isnaini; Aswi Aswi
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15931

Abstract

Dengue Hemorrhagic Fever (DHF) is a disease that is still a main problem in public health in Indonesia. This study aims to map the relative risk (RR) of dengue cases in Makassar City using the Spatial Conditional Autoregressive (CAR) model with Bayesian approaches: Besag-York-Molliѐ (BYM) and Leroux models. The data used in this study is DHF case data from 2016 to 2018 for 15 sub-districts in Makassar City. The best model was based on the model fit criteria, namely Watanabe Akaike Information Criteria (WAIC) and Deviance Information Criteria (DIC). The results indicate that the best model used to map the RR for DHF cases in 2016 and 2017 is the BYM CAR model, while the best model for 2018 is the Leroux CAR model. Based on the results of the analysis, it was concluded that in 2016 the area with the highest RR was Manggala District and the lowest RR was Tamalate District. In 2017, the area with the highest RR was Ujung Pandang District and the lowest RR was Biringkanaya District. Meanwhile, in 2018, the area with the highest dan the lowest RR was Ujung Tanah and Tamalate Districts, respectively. The results of this study are expected to be able to assist the government in implementing the program to control dengue fever in Makassar City effectively and efficiently.Keywords⎯ Dengue Hemorrhagic Fever, Relative Risk Mapping, CAR BYM, CAR Leroux.
Modeling the Number of Pneumonia in Toddlers in East Java Province in 2021 with Generalized Poisson Regression Fittrofin Amalia Farisa; Syarifah Nisrina Hasna Salby; Annisa Auliya Rahman; Purhadi Purhadi
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15339

Abstract

Pneumonia is one of the highest causes of toddler’s mortality, including Indonesia. In East Java 2021, the discovery of pneumonia is 50%. It is relatively high, especially among children under five. This study aimed to obtain the factors that influence the number of pneumonias in toddlers in East Java by using Generalized Poisson Regression (GPR) model with and without exposure variable. GPR is used when the assumption of Poisson regression is not met due to the overdispersion. Data was obtained from the East Java province health office containing the number of Pneumonia patients in East Java by districts/cities and the factors that allegedly affect them. Based on the analysis, GPR with exposure variable is better than GPR without exposure variable. The possible GPR models with exposure that has the smallest AICc is model that included the percentage of low-birth-weight babies, percentage of coughing/difficulty breathing toddlers given standard management, and percentage of toddlers getting vitamin A. All independent variables included in the model has significance effect to the number of pneumonias in toddlers.
Penerapan Synthetic Minority Oversampling Technique terhadap Data Perokok Anak di Nusa Tenggara Barat Tahun 2021 Rahma Mutiara Sari; Achmad Prasetyo
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.18472

Abstract

Indonesia is ranked as the country with the highest number of young smokers in Southeast Asia. This situation is very worrying considering the negative impact of smoking can cause various health problems and even lead to death. West Nusa Tenggara Province has the highest percentage of children who smoke in Indonesia in 2021 at 2.28%. Data on children's smoking status is identified as unbalanced data because the ratio between children who smoke and do not smoke is very lame. Therefore, the binary logistic regression analysis method of the Synthetic Minority Oversampling Technique approach was applied to handle the problem. This study aims to determine an overview and identify variables that influence children's smoking behavior in West Nusa Tenggara in 2021 and their trends. The data used in this study are secondary data from the 2021 National Socio-Economic Survey with the unit analysis of children aged 5 to 17 years in West Nusa Tenggara in 2021. The results showed that gender, economic status, age, status of region of residence, education level of the head of household, and schooling status influenced children's smoking behavior in West Nusa Tenggara in 2021 with children who didnt attend school having the greatest tendency to smoke.
Analisis Pengaruh Sanitasi Total Berbasis Masyarakat (STBM) terhadap Kondisi Kurang Gizi dan Stunting di Kota Surabaya Adma Novita Sari; Agnes Happy Julianto; Davina Shafa Vanisa; Muhammad Rosyid Ridho Az Zuhro; Dita Amelia; M.Fariz Fadillah Mardianto; Elly Ana
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15434

Abstract

Kasus stunting dan kurang gizi di kota Surabaya masih menjadi permasalahan pelik. Pasalnya, meski sudah mengalami penurunan drastis hingga 50%, tetapi prevalensi kasus positifnya masih melebihi ambang batas maksimal yang ditetapkan oleh BKKBN. Dilansir dari BPS dan BKKBN Provinsi Jawa Timur pada tahun 2021, kasus stunting di Kota Surabaya mencapai lebih dari 1.000 kasus atau setara 28,9% dan kasus kurang gizi mencapai lebih dari 160 kasus yang tersebar di seluruh wilayah kota Surabaya. Salah satu penyebab tingginya kasus ini adalah standar sanitasi masyarakat atau Sanitasi Total Berbasis Masyarakat (STBM) masih belum memenuhi indikator baik atau bersih. Oleh karena itu, dengan menggunakan analisis Multivariate Analysis of Variance (MANOVA) akan dibuktikan sekaligus menjawab hasil penelitian terdahulu terkait pengaruh standar sanitasi terhadap kedua kasus tersebut. Dengan menggunakan metode studi literatur dan mengambil data sekunder dengan pendekatan statistik kuantitatif dimana prevalensi stunting dan kurang gizi sebagai variabel dependen dan standar sanitasi sebagai variabel independen terbukti bahwa standar sanitasi memang berpengaruh terhadap kondisi kurang gizi dan stunting di kota Surabaya. Hasil ini sangat bermanfaat untuk menindaklanjuti kasus agar pemerintah, dinas terkait, serta masyarakat umum mampu bersinergi untuk menuju ”zero stunting and malnutrition” di kota Surabaya. 
Pengelompokan Daerah di Jawa Timur Berbasis Indikator Kesejahteraan Masyarakat dengan Pendekatan Analisis Cluster Hierarki dan Nonhierarki Muhammad Fikry Al Farizi; Faradilla Harianto; Maria Setya Dewanti; Cynthia Anggelyn Siburian; M. Fariz Fadillah Mardianto; Dita Amelia; Elly Ana
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15452

Abstract

Based on Central Statistics Agency (BPS) data in September 2021, East Java is a province with the largest number of poor people in Indonesia with a total of 26,503 million people. Poverty is one of the factors that affect people's welfare in East Java. Therefore, this research was conducted to classify regencies and cities in East Java based on indicators of community welfare through a hierarchical cluster analysis approach using the single linkage, complete linkage, average linkage, and ward methods, determine the optimum cluster for each method using Pseudo – F, then compare the four methods and determine the best method using the rated value, as well as identify the characteristics of each cluster group based on the best method. There are six variables that will be used in this study. All variable data is secondary data obtained from the official website of the Central Statistics Agency (BPS) of East Java Province. This study produced four clusters using the average linkage method as the best method. This research is expected to be useful as a consideration for evaluating the government and related agencies to overcome the main problems that still occur in each regency and city. Thus, the welfare of the people of East Java can be realized and the SDGs targets in Indonesia can be achieved.
Aplikasi Model ARIMAX dengan Efek Variasi Kalender untuk Peramalan Trend Pencarian Kata Kunci “Zalora” pada Data Google Trends Andrea Tri Rian Dani; Sri Wahyuningsih; Fachrian Bimantoro Putra; Meirinda Fauziyah; Sri Wigantono; Hardina Sandariria; Qonita Qurrota A'yun; Muhammad Aldani Zen
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15793

Abstract

ARIMAX is a method in time series analysis that is used to model an event by adding exogenous variables as additional information. Currently, the ARIMAX model can be applied to time series data that has calendar variation effects. In short, calendar variations occur due to changes in the composition of the calendar. The purpose of this study is to apply the ARIMAX model with the effects of calendar variations to forecast search trends for the keyword "Zalora". Data were collected starting from January 2018 to November 2022 in the form of a weekly series. Based on the results of the analysis, the ARIMAX model is obtained with calendar variation effects with ARIMA residuals (1,1,1). Forecasting accuracy using the Mean Absolute Percentage Error (MAPE) of 10.47%. Forecasting results for the next 24 periods tend to fluctuate and it is estimated that in April 2023 there will be an increase in search trends for the keyword "Zalora".
Aplikasi Pengelompokan Data Runtun Waktu dengan Algoritma K-Medoids Muhammad Aldani Zen; Sri Wahyuningsih; Andrea Tri Rian Dani
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15864

Abstract

The development of information technology will always be accompanied by the storage and accumulation of massive quantities of digital information. Cluster analysis is one of many data processing problems that require the selection of an appropriate algorithm when dealing with large data sets. Cluster analysis is a collection of techniques for dividing a set of observation objects into clusters. Cluster analysis is applicable to time series data, the processing of which differs slightly from that of cross-section data. Clustering time series is a technique for processing multivariable time series data. K-Medoids is the clustering algorithm used for time series clustering. The objective of this study is to obtain optimal K-values in determining the number of clusters based on silhouette coefficients and grouping outcomes using the K-Medoids algorithm. In this study, the dynamic time-warping distance is utilized as the similarity metric. This study provides cooking oil price data for 34 Indonesian provinces from October 2017 to October 2022. The optimal K value is determined for two clusters based on the results of the analysis, with 19 provinces joining cluster 1, where the cluster with cooking oil prices was below cluster 2 and 15 provinces joining cluster 2 which is the cluster with the highest cooking oil prices.

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