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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 147 Documents
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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.
Model Polinomial Sebagai Model untuk Melihat Hubungan Fungsional Antara Variable Respond dan Perlakuan Enny Supartini
Inferensi Special Issue: Seminar Nasional Statistika XI 2022
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v1i1.19117

Abstract

The use of waste as raw material for other products is a good thing to do, one of which is the use of fish skin waste which can be used as raw material for making gelatin which is one of the raw materials that is widely used for food products. In the process of making gelatin, it is affected by the concentration of malic acid when soaking the fish skin raw material and it is necessary to know what concentration of malic acid is right to obtain the desired quality. To see the effect of malic acid content on the acidity of the yield, analysis of variance was used and to see the functional relationship between the quality of the acidity of the marinade and the concentration of malic acid given, a polynomial model could be used. From the results of the analysis, it was found that there was an effect of the concentration of malic acid given on marinade, while the functional relationship obtained was a polynomial second-order model.
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.
Analisis Biplot Pada Pengelompokan Kecamatan Di Kabupaten Tasikmalaya Berdasarkan Indikator Kemiskinan Annisa Siti Utami; Anindya Apriliyanti Pravitasari; Irlandia Ginanjar
Inferensi Special Issue: Seminar Nasional Statistika XI 2022
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v1i1.19128

Abstract

Poverty is a social problem that continues to exist in people's lives according to Nurwati, 2008. Therefore, the problem of poverty is the center of attention of the Tasikmalaya Regency government. In the National Long-Term Development Plan (RPJPN) 2005-2025 the problem of poverty is seen in a multidimensional framework, therefore poverty is not only related to income measurement, but related to several things. This is because poverty is not only related to the size of income but involves several things. In the Tasikmalaya Regency Regional Medium-Term Development Plan (RPJMD), the target for achieving the poverty rate in 2021 is 10.23%. Based on BPS publications, there are 10.75% of the population of Tasikmalaya Regency who are categorized as poor, meaning that the Tasikmalaya Regency government's target has not been achieved. So it is necessary to make efforts to overcome the problem of poverty. This study aims to group sub-districts in Tasikmalaya Regency based on the similarity of poverty indicators owned by each sub-district by using biplot analysis. The data used is poverty indicator data for 39 sub-districts in Tasikmalaya Regency in 2021. From the research results it is known that the amount of variation that can be described is 97%, meaning that the plots formed can best describe actual conditions. data information. In addition, three clusters have the same poverty indicators. Cluster 1 contains sub districts that have an indicator in the form of a high student to school ratio in SMA/SMK/MA. Cluster 2 contains sub districts that have moderate to low indicators on all variables except the ratio of SMP/MTs students and the ratio of SMA/SMK/MA students. Meanwhile, Cluster 3 consists of sub-districts that have an indicator in the form of a high ratio of SMP/MTs students.
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.
Perhitungan Premi Tunggal Bersih pada Asuransi Jiwa Kredit Sinking Fund Gatot Riwi Setyanto
Inferensi Special Issue: Seminar Nasional Statistika XI 2022
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v1i1.19118

Abstract

Various types of banking product innovations were rolled out to keep up with the needs and more advanced developments, one of which is a credit or loan facility that can be utilized by the public. This credit facility is in great demand by the public because it is very helpful, especially in terms of additional capital. However, this credit activity can also be full of risks because most of the funds are entrusted to the public. Therefore, the provision of credit must be accompanied by strict risk management. As time goes on after credit is realized, banks are faced with credit risk problems, namely bad credit. Conducting a 5C (Character, Capacity, Capital, Economic Condition, and Collateral) analysis of customers is one way for banks to reduce the risk of bad credit. In fact, even though anticipatory steps have been taken by applying the 5C analysis, there is still a risk of default due to the death of the debtor, which causes the loan to not be fully paid off. In response to the possibility of the foregoing, financial/banking institutions adopted a policy requiring debtors to obtain term life insurance for a period of time equal to the term of the loan. For this reason, banks usually cooperate with life insurance institutions. Therefore, it must be ensured that the net single premium is paid at the beginning of the credit loan. With regard to the above, this paper will provide an overview and also discuss the concept of calculating the net single premium on credit life insurance, especially for debtors who make loan transactions to banking institutions that apply loan repayments with the sinking fund concept with a period according to the loan repayment tenor. So that when the debtor dies, he can pay the remaining unpaid loan to the lending institution or  bank.
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. 
Determinan Faktor Rendahnya Kepemilikan Jamban Keluarga dengan Regresi Logistik di Desa Penen, Kabupaten Deli Serdang, Sumatera Utara Novrika Silalahi; Elmina Tampubolon
Inferensi Special Issue: Seminar Nasional Statistika XI 2022
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v1i1.19129

Abstract

Towards 2025, health in Indonesia is moving towards having all citizens have basic sanitation or community-based total sanitation activities. With this program it is very important to support the importance of programs to increase awareness of family latrine ownership. In Deli Serdang Regency, in the Biru-Biru District, Penen Village is one of the villages whose residents income from agricultural sector has 40% of the family’s latrines. This percentage figure is a small number. For this reason, this study aims to determine the factors that influence low family latrine ownership and determine the biggest factor for low family latrine ownership by means of multivariate analysis, namely logistic regression. Logistic regression is a regression that has special characteristics from linear regression analysis which has the same goal of predicting value. Logistic regression is widely used in the application of the causal factors of several variables, to analyze the relationship of one or more independent variables with a dependent variable that is binary or dichotomous. The variables used in this study are knowledge, economic status, attitudes, behavior, and the role of health workers, to find the factors that cause low family latrine ownership in Penen Village. The research design used cross sectional with a sample of 76 heads of families, with random sampling. The results showed that the variable knowledge (p-value = 0,000), economic status (p-value = 0.001), attitude (p-value = 0,008), behavior (p-value = 0,008), and the role of health workers (p-value = 0,03). The final result of the logistic regression, the variable which is the biggest factor influencing the low family latrine ownership is knowledge with an Odd Ratio of 80,947. The probability value (p) is 0.0038 or 0.38% with the regression model equation formed, namely Y = -17,719 + 4,394 (Knowledge) + 2,272 (Attitude) + 1,34 (Behavior) + 4,14 (Role of Health Workers)
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.
Peramalan Curah Hujan di Kota Bandung dengan Metode SARIMA (Seasonal Autoregressive Integrated Moving Average) Muhammad Ilham Hakiqi; Arif Firmansyah; Restu Arisanti
Inferensi Special Issue: Seminar Nasional Statistika XI 2022
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v1i1.19119

Abstract

The need for future rainfall information, modeling and forecasting is important. The forecasting method is a method used to predict future conditions based on past data. Rainfall data is time-series data in the form of seasonality, a pattern that repeats at fixed time intervals, so the authors use the Seasonal Autoregressive Integrated Moving Average (SARIMA) method, which is appropriate for data with seasonal characteristics. The author takes monthly rainfall data in Bandung city for the period January 2016 to December 2021 to forecast rainfall in Bandung city for next year. After calculations using the SARIMA method, the best model for forecasting rainfall in the city of Bandung is then obtained, namely the SARIMA model (0,0,0)(0,1,1)12.

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