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Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population)
Published by Universitas Airlangga
ISSN : 2302707X     EISSN : 25408828     DOI : -
Core Subject :
Jurnal Biometrika dan Kependudukan is a journal that contains articles about the development of statistical methods in the field of health, the application of statistical methods on solving health problems, the development of demography and demography, solving reproductive health problems, solving the problems of maternal and child health as well as the themes surrounding the development of biostatistics and population. This journal is published twice a year in July and December.
Arjuna Subject : -
Articles 213 Documents
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THE ROLE OF "PAGUYUBAN REMAJA PEDULI HIV/AIDS SIDOARJO" (PARPAS) ON KNOWLEDGE, ATTITUDE, AND ACTION FOR HIV/AIDS PREVENTION IN SENIOR HIGH SCHOOLS IN SIDOARJO Adelia Dwi Pratiwi; Windhu Purnomo
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.10-17

Abstract

There were total of 2,100,000 new HIV infections worldwide and 1,500,000 deaths from AIDS recorded in 2013. The total HIV/AIDS cases in 2017 in Sidoarjo reached 476 cases and cumulatively reached 1,245 cases. HIV/AIDS is a well-known topic among teenagers. Teenagers are often associated with physical development in puberty phase which usually followed by sexual development. Furthermore, they also experience changes emotionally and physically which are projected in their behavior and attitude.  These circumstances make teenagers prone to the risky behavior towards HIV/AIDS transmission. This study aims to analyze the role of "Paguyuban Peduli HIV/AIDS Sidoarjo" or PARPAS on teenagers' knowledge, attitude, and behavior towards HIV/AIDS prevention. This research is an observational analytic using cross-sectional research design. The population of the study is all students of SMAN 1 Taman and SMAN 1 Sidoarjo, 2,370 students in total. The sampling technique uses simple random sampling and the sample size is 100 students. The result shows that there is correlation between PARPAS role on knowledge and attitude of students' in Sidoarjo towards HIV/AIDS prevention. Nevertheless, there is no correlation between PARPAS role on students' behavior towards HIV/AIDS prevention. Suggestions concluded from the results are including early detection, attempt in joining organization related to HIV/AIDS awareness, and health education given to both students and parents.
FORECASTING OF UNMET NEEDS PERCENTAGE IN EAST JAVA PROVINCE USING AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) METHOD Feri Styaningsih
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.53-61

Abstract

ARIMA uses present and past values as the dependent variable. The accuracy of the ARIMA forecasting method results is good to be used to obtain short-term forecasts. Compared to other time series methods, the advantage of ARIMA method is that it can be used in the percentage of unmet needs data in East Java Province since ARIMA method does not require any specific data motives. Unmet need is a group of women who do not want to have any more children or want to minimize their pregnancy but refuse to use contraception to prevent pregnancy. This study aims to determine the percentage of unmet needs in East Java Province in the future. This study will analyze the value of forecasting and determine the best model for ARIMA. The data used is the monthly data of unmet needs percentage of East Java Province starting from January 2014 to April 2019 (64 data plots). The results showed that the percentage of the number of unmet needs in East Java Province can be predicted using ARIMA model (12,1,0) without constant. The model is based on ARIMA (12,1,0) diagnostic test without constant meeting all the test requirements. The results of forecasting held a MAPE value of 2.369% and MAE of 0.26%. Based on MAPE and MAE, the model has a very good forecasting ability with a fairly small error value. Forecasting results indicated fluctuations in unmet needs data, where from December 2019 to February 2020 there was an increase in number of unmet needs in East Java Province. In the interim, starting in March 2020, the data needs in East Java Province tend to be constant at a higher position than the previous increase.
PREDICTION MODEL FOR THE NUMBER OF ARI CASES IN CHILDREN IN SURABAYA USING ARIMA METHOD Alvin Zulhazmi Priambodo; Mahmudah Mahmudah
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.18-26

Abstract

Forecasting is an important element in planning decision-making related to estimating future events. Forecasting techniques that are often developed and used today are the Time Series. Time series is a measurement of events through the stages of time in hours, days, months, and years format. This research uses the ARIMA time series method. The ARIMA method is used to model acute respiratory infections (ARI) in children. The best model is determined using the smallest error through the Mean Absolute Percentage Error (MAPE). The study aims to predict the number of ARI cases in children in Surabaya. This research is an unobtrusive/nonreactive research. The researcher conditioned the subjects to not being aware that the subject is being studied and therefore, left the subject uninterrupted. The data used was the number of ARI cases in children from January 2014 to December 2018. The data was obtained from the monthly report of the Health Information System Unit (HIS) of the Surabaya Health Office. The conclusion from this study showed that the ARIMA method obtained the best model results, namely ARIMA (2,1,2) with a MAPE value of 15.024. Forecasting results fluctuated and a downward trend in the case of ARI children in Surabaya. In certain months, the number of acute respiratory infections has increased significantly, including in February and March. 
IMPLEMENTATION OF CLUSTERING USING K-MEANS METHOD TO DETERMINE NUTRITIONAL STATUS Stefanny Surya Nagari; Lilik Inayati
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.62-68

Abstract

Cluster analysis aims to classify data objects into two categories: objects that are similar in characteristics in one cluster and objects that are different in characteristics with the other objects of another cluster. K-Means is a method included in the distance-based clustering algorithm that starts by determining the number of desired clusters. Malnutrition is one of the biggest concerns in Indonesia. According to Riskesdas 2018 data, as many as 17.7% infants under 60-month-old are still having problems with nutrition intake while 3.9% are having malnutrition. This might result in higher death rate. This research was conducted to classify the nutritional status of infants under 60-month-old conducted by the C-Means Clustering method. This research is non-reactive, using secondary data in Ponkesdes Mayangrejo, Bojonegoro without direct interaction with the subject. This study concluded that the grouping of nutritional status is possible by using K-Means with 4 clusters formed which are 23 malnourished toddlers, 17 undernourished toddlers, 7 nourished toddlers, and 10 over-nourished toddlers.
DETERMINING THE FACTORS RELATED TO FIRST TIME POSTNATAL BREASTFEEDING Armita Mayang Sari
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.27-35

Abstract

Infant Mortality Rate (IMR) is a problem in Indonesia that must be addressed in various aspects. New-borns need more attention in fulfilling their intake for growth and development. The best baby intake for early life after childbirth is exclusive breast milk. The importance of the time when breastfeeding is first given is closely related to the success of the Early Breastfeeding Initiation (EBI). Besides being able to handle the problem of infant intake, EBI is useful in strengthening the relationship between mother and child due to the interactions formed during breastfeeding. The goal to be achieved by researchers is to determine factors related to the time when breastfeeding was first given after birth. This type of research is analytic descriptive using the Spearman correlation test and chi-square statistical tests. The data used are secondary data from the Indonesian Demographic and Health Survey (IDHS) in 2017. The results of the descriptive analysis of the study are that the majority of mothers as respondents gave breastfeeding for the first time immediately at 62.8%. The results of the bivariate analysis of the study are the relationship between maternal parity (p = 0.001 and r = -0.072), infant birth weight (p = 0.03 and r = 0.049), area of residence (p = 0.013) and type of delivery (p = 0.013) p = 0.001) to the time of first breastfeeding.
ANALYSIS OF FACTOR AFFECTING INFANT MORTALITY RATE (IMR) IN EAST JAVA USING MULTIPLE LINEAR REGRESSION Weike Retno Palupi; Lailatul Khusnul Rizki
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.69-76

Abstract

Infant Mortality Rate (IMR) is one of the important indicators in public health. Indonesia still has a relatively high IMR compared to the neighboring countries. Based on the Indonesian Demographic Health Survey (IDHS) in 2012, IMR in East Java reached 25.50 deaths per 1000 births. IMR decline occurred during 2012 to 2015. Achievement depends on the factors that influence it. This study aims to create a model of IMR based on maternal and external factors in East Java. The method used was a non-reactive study using 38 districts/cities as sample units in East Java, which came from Central Bureau of Statistics secondary data in 2015. Statistical analysis used multiple linear regression. The results showed the independent variables together affected the IMR (p-value = 0,000 <0.05), but partially influenced by the age of the first married mother (p-value = 0,000 <0.05) and the helper delivery of non-medical personnel (p-value = 0.014 <0.05). The conclusion of this study is the regression equation model for IMR in East Java in 2015, which is IMR = 1,064 + 1,319 * (age of first marriage) + 0.439 * (helper of non-medical births). Suggestions for the Government of East Java Province to implement strategies so that infant mortality cases can be reduced.
DECOMPOSITION METHOD FOR FORECASTING THE NUMBER OF PARTICIPANTS OF NEW FAMILY PLANNING IN SURABAYA Dinana Izzatul Ulya; Mahmudah Mahmudah
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.36-43

Abstract

Indonesia is a country that has a large population and Family Planning Program was initially designed to control the population. This study aimed to forecast new Family Planning Program participants in the city of Surabaya in 2019 using the decomposition method. This study used secondary data, which is the number of participants for new Family Planning Program in January 2014 to December 2018 (60 plots of data) obtained from the PCWECP Surabaya. The researcher chose decomposition method in this study because decomposition is a one-time series method that has rarely been applied in a research. Based on the results of the study, the number of participants for new Family Planning Program from January to December 2019 was 2,776; 2,663; 2,504; 2,340; 2,440; 1,912; 2,034; 2,291; 2,223; 2,123; 2,123; 2,130 and 2,560 participants. The error value generated by this study is MAPE of 9, MAD of 365, MSD 197,738, and MSE of 2.1675. The best error value is the one that has the smallest value, so the MSE is the best model.
SEX PREFERENCE ON CHILD AND MODERN CONTRACEPTION USE IN FERTILE AGE WOMEN IN INDONESIA (ANALYSIS OF IDHS 2017) Deby Novita Sari
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.77-86

Abstract

Generally, this study aims to describe the characacteristics of modern contraception users in fertile age women in Indonesia. Specifically, this study will examine the effect of the children's sex preferences on the use of modern contraception. Furthermore, the control variables used are age, education taken by the mothers, mothers' working status, marital status, Family Planning Field Officer (Petugas Lapangan Keluarga Berencana/PLKB) visits, and internet usage. The data used in this study was taken from the results of the Indonesian Demographic and Health Survey (IDHS) 2017. Data analysis was using descriptive and inferential analysis. Descriptive analysis used is in the form of a single table and a cross-tabulation, while the inferential analysis used is binary logistic regression. Based on the descriptive analysis results, it can be concluded that 79.35% of fertile age women (15-49 years old) in Indonesia do not have particular sex preference on their children. Moreover, the inferential analysis results with a significance level by 1%, it appears that child's sex preference will reduce the chance of modern contraception use. Women's age, the number of children that safely delivered, marital status, and FPFO visits are having the positive effect on the modern contraception use, while the residential area, education taken, and internet usage are negatively affect the modern contraception use.
IMPLEMENTATION OF CLUSTER K-MEANS FOR THE EAST JAVA ENVIRONMENTAL HEALTH AREAS GROUPING IN 2017 Saarah Puspita Dewi; Mahmod Bin Othman
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.1-9

Abstract

An unhealthy environment is a threat that possibly leads to diseases. Consequently, effective environmental monitoring is needed as an effort to improve environmental quality. The basis for implementing the program to determine the fulfilment of environmental health indicators is program targets. Achievements will be compared with program targets as program evaluations to determine the distribution priority areas for improving environmental health indicators. In order to illustrate the coverage of environmental health services by each district or city in East Java Province, K-Means cluster analysis was administered. The objective of cluster analysis application is to determine the regional distribution status based on the environmental health indicators’ achievement in East Java in 2017. This type of research is a descriptive study using non-reactive methods. The data collected was secondary data based on indicators on the Environmental Health Program in 2017. The results of this study illustrated the distribution of environmental health areas in East Java, there are 3 clusters including cluster 1 (high strata) covering 17 districts or cities, where several environmental health indicators had fulfilled the target, cluster 2 (middle strata) covers 16 districts or cities where several environmental health indicators were almost reaching the target. Finally, cluster 3 (lower strata) covers 5 districts, where several environmental health indicators had not been achieved yet. In conclusion, the Environmental Health Program in 2017 at East Java Province was considered quite successful.
GROUPING OF PROVINCES IN INDONESIA BASED ON MATERNAL HEALTH INDICATORS USING VARIABLE WEIGHTING K-MEANS AND FUZZY C-MEANS Elvira Mustikawati Putri Hermanto
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.44-52

Abstract

Maternal Mortality Rate (MMR) is an indicator used to assess maternal health as well as the health status of a country. MMR is a target that must be achieved by Indonesian Government in Sustainable Development Goals (SDGs) in 2030. The Government of Indonesia has made various efforts to reduce MMR. This study aims to determine the distribution pattern of indicators for improving maternal health by grouping provinces in Indonesia based on the characteristics of maternal health indicators. The variables used are indicators that affect maternal mortality, namely K4 coverage (x1), Td2+ immunization coverage (x2), maternity assisted by health workers in health facilities coverage (x3), post-partum check up coverage (x4), Puskesmas implementing pregnant classes (x5), Puskesmas implementing P4K (x6), participant of KB coverage (x7) in Indonesia in 2017. The grouping methods are Variable Weighting K-Means (VWKM) and Fuzzy C-Means (FCM). The selection of the best grouping results uses the Internal Cluster Dispersion Rate (icdrate). Based on the analysis results, the best grouping is generated by the FCM method. The icdrate value generated by FCM is 0.325 while the icdrate value generated by VWKM is 0.552. FCM produces five groups which can be categorized as groups with maternal health indicator characteristics with very low, low, medium, high, and very high scores. Provinces in a group tend to be geographically close. East Java and Bali are provinces included in the indicator group of very high maternal health. Papua and West Papua fall into the group for maternal health which is very low.

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