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APLIKASI ANALISIS FAKTOR DENGAN METODE PRINCIPAL COMPONENT ANALYSIS DAN MAXIMUM LIKELIHOOD DALAM FAKTOR-FAKTOR YANG MEMENGARUHI PEMBERIAN MAKANAN TAMBAHAN PADA BAYI USIA 0-6 BULAN DI DESA PEMATANG PANJANG KECAMATAN AIR PUTIH KABUPATEN BATUBARA TAHU iska simarmata; Abdul Jalil Armi Arma; arnita .
Kebijakan, Promosi Kesehatan dan Biostatiskik Vol 1, No 2 (2015): Jurnal Kebijakan, Promosi Kesehatan dan Biostatiskik
Publisher : Kebijakan, Promosi Kesehatan dan Biostatiskik

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Factor analysis is one of the multivariate statistical analysis techniques.This analysis is included in the interdependence technique with the aim of reconciling data in a grouping or the formation of a new set of variables which is named factor. The parameter estimation that is commonly used in this analysis is the principal component analysis method and the maximum likelihood method. This research aims to know the comparison of suitability of the model by principal component method and maximum likelihood method within the factors that affect the complementary feeding in infants ages 0-6 months in Pematang Panjang Village Air Putih Subdistrict Batubara District 2013. Based on its purpose, this research is implementative research and based on its explanation level it is comparative research. The population of the research was all mothers who have baby in age of 0-6 months which are as many as 52 persons. The sampleis all population made as sample. The result of factor analysis using the principal component analysis method forms factor 1 (education, culture, economy, job, and mother’s health) and factor 2 (knowledge, baby’s health, and health/medical officer), while the result of factor analysis using maximum likelihood method forms factor 1 (education, culture, economy and job) and factor 2 (knowledge, baby’s health, mother’s health and health/medical officer). Research results by using analysis of factors suggest that the maximum likelihood method has a better model accuracythan the principal component analysis method, because the RMSE value of maximum likelihood method which is 0,0222 < RMSE value of principal component analysis method which is 0,0409. It is suggested to the next research which uses factor analysis aplication that it is better to firstly see the result of the analysis using principal component analysis and maximum likelihood methods and then using method with less RMSE value.

PENERAPAN TWO WAY MANOVA DALAM MELIHAT PERBEDAAN LAMA STUDI DAN INDEKS PRESTASI MAHASISWA REGULER 2009 BERDASARKAN JALUR MASUK DAN AKTIVITAS MAHASISWA FKM USU TAHUN 2013 Jehan Mutiarany; Abdul Jalil Armi Arma; Maya Fitria
Kebijakan, Promosi Kesehatan dan Biostatiskik Vol 1, No 2 (2015): Jurnal Kebijakan, Promosi Kesehatan dan Biostatiskik
Publisher : Kebijakan, Promosi Kesehatan dan Biostatiskik

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MANOVA is an extension of the Analysis of Variance (ANOVA), which have long been widely used in various fields of science. Technically, MANOVA can be interpreted as a statistical method to explore the relationship between several independent variables are categorical type nominal or ordinal scale with multiple dependent variables are type numerical interval or ratio scale. This research aims to determine whether there are differences in length of study and student achievement index based on admission selection and student activity which was followed by regular student 2009 Public Health Faculty University of Sumatera Utara in 2013. This research was conducted by survey method with a correlation study is to find out relationship between the dependent and independent variables in a group of subjects. The results of the analysis using the Two-Way MANOVA test for admission selection variable at the significance level (α) of 0,05 indicates that there are significant differences on variables length of study and student achievement index which is tested simultaneously based on admission selection regular students 2009 Public Health Faculty University of Sumatera Utara with a significance value of Pillai’s Trace is 0,013. For a student activity variables at significance level (α) of 0,05 indicates that there is no real difference on variables length of study and student achievement index which is tested simultaneously by the activity of the regular students 2009 Public Health Faculty University of Sumatera with a significance value of Pillai’s Trace is 0,505 at 5% confidence level. For other studies were suggested to implement Two-Way MANOVA to test the effect of a set of independent variables to a set of dependent variables simultaneously. Keyword: Two-Way MANOVA, Pillai’s Trace, student

PERBANDINGAN PREFERENSI PESERTA BPJS TERHADAP KUALITAS PELAYANAN DI RUMAH SAKIT DR. PIRNGADI DAN RUMAH SAKIT MARTHA FRISKA MEDAN TAHUN 2015 wilda try wahyuni; Abdul Jalil Armi Arma; Maya Fitria
Kebijakan, Promosi Kesehatan dan Biostatiskik Vol 1, No 2 (2015): Jurnal Kebijakan, Promosi Kesehatan dan Biostatiskik
Publisher : Kebijakan, Promosi Kesehatan dan Biostatiskik

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ABSTRACT Dissatisfaction of BPJS members toward hospital service quality encourages them to have health service based on their preferences, so their need and hope is properly fulfilled. The objectives of this research are to identify and compare the preferences of BPJS members toward service quality in General Hospital of Dr. Pirngadi and Martha Friska Medan by using conjoint analysis. There are 5 attributes of hospital services, i.e. reliability, responsiveness, assurance, empathy and tangible in which each attribute consists of sub Attribute and Level. The conjoint analysis is one of the methods for obtaining the level combination and most important attribute based on patients’ preferences in which each hospital serves 50 BPJS patients and the sample was taken by purposive sampling method. The result of this research indicates that the preferences of BPJS members toward service quality based on the sequences of the most important sub attributes between the General Hospital of Dr. Pirngadi and Martha Friska were responsiveness, assurance and empathy, while the differences were found on reliability and tangible. The level combination of the same sub attributes between those general hospitals were found on empathy attribute, and for the attribute of reliability, responsiveness, assurance, tangible, it produced the different combination. It is suggested to the General Hospital of Dr. Pirngadi and Martha Friska to provide the health service based on the preferences of BPJS members and for the future study, it is suggested to apply the conjoint analysis in another health case.

PENERAPAN ANALISIS REGRESI RIDGE PADA DATA PASIEN HIPERTENSI DI RUMAH SAKIT UMUM DAERAH SIDIKALANG TAHUN 2014 medis pasaribu; Abdul Jalil Armi Arma; Ria Masniari Lubis
Kebijakan, Promosi Kesehatan dan Biostatiskik Vol 1, No 2 (2015): Jurnal Kebijakan, Promosi Kesehatan dan Biostatiskik
Publisher : Kebijakan, Promosi Kesehatan dan Biostatiskik

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ABSTRACT Multicollinearity is the correlation between some independent variables which makes coefficient regression yielded by multiple regression analysis cannot be used in estimating. The problem of multicollinearity which is indicated by the value of Variance Inflation Factor (VIF) > 10 occurs when the influence of age, obesity (IMT), and cholesterol were modeled toward systole and diastole blood pressure. The objective of the research was to obtain the regression model of age, obesity (IMT), and cholesterol with systole blood pressure and with diastole blood pressure of patients suffered from hypertension at the Inpatient Wards of the RSUD (Regional General Hospital) Sidikalang, in 2014. The samples consisted of 105 patients. The data were secondary data and using α=0,1. Analyzed by using ridge regression in order to obtain correct regression model. The result of ANOVA test showed that p < 0.000 which indicated that, simultaneously, there was the influence of age, obesity (IMT), and cholesterol on systole and diastole blood pressure. The equation for modeling blood pressure was obtained at k = 0.07; they were Y systole = 21.2828 + 0.7169 Age + 1.7986 IMT + 0.2222 Cholesterol, and Y diastole = 24.5290 + 0.5025 Age + 0.6648 IMT + 0.0946 Cholesterol. It is recommended that the next researchers solve the problems of multicollinearity during the modeling; one of them is by using ridge regression analysis.

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