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All Journal Jurnal Pengolahan Hasil Perikanan Indonesia Edcomtech Jurnal Kajian Teknologi Pendidikan Jurnal Matematika Sains dan Teknologi Jurnal Pendidikan Terbuka Dan Jarak Jauh Prosiding Konferensi Nasional PKM-CSR Agridev Journal : Agribusiness Digitalization & Community Development
Deddy Ahmad Suhardi
Universitas Terbuka
Agriculture, Biological Sciences & Forestry Arts Humanities Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Mathematics Nursing Public Health Social Sciences Veterinary Other

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Journal : Jurnal Matematika Sains dan Teknologi

 1 
BEBERAPA KONSEKUENSI SITUASI MEDIASI SEMPURNA PADA STRUKTUR KORELASI, KONTRIBUSI MEDIATOR, DAN UKURAN SAMPEL Suhardi, Deddy A; Isfarudi, Isfarudi
Jurnal Matematika Sains dan Teknologi Vol 11 No 1 (2010)
Publisher : LPPM Universitas Terbuka

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Abstract

A very popular article by Baron and Kenny (1986), later extended by Kenny, Kashy, and Bolger (1998), recommended to social psychologists a test of mediation based on a set of steps involving correlations and regression weights. The serial published tests of mediation has come to be known as the Baron-Kenny approach. By the Baron-Kenny approach, a simple complete mediation is to be indicated which is a test of the direct path between an independent variable (X) and a dependent variable (Y) with a mediator variable (M) controlled is not significant. A simple mediation model has three correlations of their variables each. According to sequential regression analysis on a simple mediation model, a mediator M come after an independent variable X exist in the model, has a contribution of the mediator. Otherwise, sample size is a critical component to test as well as statistically significances. We argue the importance of investigating condition and interrelation of the three correlations, sequential contribution of the mediator, and sample size in the simple complete mediation cases by using hypotetical data generated by Microsoft Excel. We indicate some general consequences of simple complete mediation cases that are: (i) average of correlation XY is lower than average of correlation XM that lower than average of correlation MY; (ii) average contribution of mediator, indicated by R2 change, at interval of 23% up to 27%; (iii) distribution of effects X on Y when M controlled is influenced by sample size, the higher sample size, the lower distribution is; and (iv) average of mediation effects is at interval: 0.4 and above for levels of small sampel size (10 up to 40), between 0.2 and 0.4 for levels of medium sample size (50 up to 300), and under 0.2 for levels of large sample size (500 or above).  
PENERAPAN REGRESI LOGISTIK BINER UNTUK MENGUKUR RESIKO ANEMIA DENGAN STATUS GIZI IBU HAMIL Deddy A Suhardi; Ila Fadila
Jurnal Matematika Sains dan Teknologi Vol. 17 No. 1 (2016)
Publisher : LPPM Universitas Terbuka

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Abstract

The prevalence of anaemia is an important health indicator for pregnant women. This paper demonstrates the use of logistic regression modelling techniques for an ordinal binary in terms of both response and predictor variables. By using 120 cross-sectional data to measure the attitude of pregnant women observed at three Community Healthcare Center (CHC) in the Serang District - Banten Province on September 2012, we investigated a factor predicting anaemia and tested whether changes in nutritional status were associated with changes in anaemia status. The anaemia status threshold using haemoglobin concentration (g/dl) was measured by the Cyanmethemoglobin method, and the nutritional status was categorized by measuring Upper Arm Circumference (cm). This paper discusses the roles of nutritional status determining the risks of anaemia and compares the results obtained using the contingency analytical methods. The paper also demonstrates how the logistic regression modelling approach dealing with the odds ratio statistic can better explain the risks of anaemia determined by nutritional status found in the CHC studied. We found that anaemia status is affected by nutritional status (coef. 1,07; p. 0,066), and the results of contingency analysis reveals that anaemia satus is associated with nutritional status (chi-sq. 3,60; p. 0,058). According to odds ratio statistic of the logistic regression (OR 2,92), the risks of anaemia on pregnant women with cronic energy deficiency would be 2,92times higher than they are on normal nutritions. Prevalensi anemia pada kehamilan merupakan salah satu indikator penting kesehatan ibu hamil. Paper ini membahas teknik regresi logistik untuk mengukur resiko anemia ibu hamil berdasarkan status gizinya. Rancangan model hanya terdiri dari satu variabel respon dan satu prediktor skala biner. Hasil analisis regresi logistik dibandingkan dengan analisis chi-kuadrat tabel kontingensi. Estimasi parameter regresi menggunakan data cross-sectional 120 ibu hamil yang diamati langsung dari tiga Puskesmas di Kabupaten Serang, Banten, pada September 2012. Status anemia dikategorikan dari pengukuran kadar hemoglobin (g/dl) menggunakan metode cyanmethemoglobin, sedangkan status gizi dari pengukuran pita lingkar lengan atas (cm). Analisis regresi logistik menunjukkan satus anemia dipengaruhi status gizi (koefisien regresi status gizi 1,07; odds ratio 2,92; p. 0,066). Analisis chi-kuadrat menunjukkan status anemia berhubungan dengan status gizi (chi-kuadrat 3,60; p. 0,058). Statistik odds ratiopada kasus ini mendeskripsikan sejauh mana peran status gizi menentukan resiko anemia ibu hamil. Resiko anemia 2,92 kali lebih tinggi bagi ibu hamil dengan kondisi gizi kurang energi kronik daripada ibu hamil dengan gizi baik.
EFEKTIVITAS VARIABEL MEDIATOR BERDASARKAN KONTRIBUSINYA DALAM MODEL MEDIASI SEDERHANA Deddy A Suhardi; Settings Isfarudi Isfarudi
Jurnal Matematika Sains dan Teknologi Vol. 10 No. 1 (2009)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.38 KB) | DOI: 10.33830/jmst.v10i1.566.2009

Abstract

Structurally relationship of variables is important in deeply analysis of path models, but the process of effect distribution must be concerned. In this situation, one or more variable would be a mediator variable which assessing effect of an independent to a dependent variable. We studied the simple mediation model that is one of path analytical models which contain of one independent variable, dependent variable and mediator variable. A necessary component of mediation is effectiveness that is a statistically significant indirect effect, formal significance tests of indirect effects are early conducted by Sobel (1982). According to sequential regression analysis on a simple mediation model, a mediator variable come after an independent variable exist in the model, the contribution of upcoming variable to the model could be obtained. We argue the importance of investigating empirical relationship between the significance of indirect effects and sequential contribution of mediator variable with a normal theory approach using Microsoft Excel simulation tools developed by Myerson (2000). We find that the higher contribution of mediator variable to the model, the more effectiveness is. This result comes up with three level correlation of independent and dependent variable which each 1000 times iteration that gives relatively immediate information about the recent empirical relationship between the significance of indirect effects and sequential contribution of mediator in the simple mediation models.
Co-Authors Adhi Susilo Dian Nursantika Ernik Yuliana Fadila, Ila Heny Kurniawati Isfarudi Lintang Patria Ojat Darojat Sri Utami