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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Range : Jurnal Pendidikan Matematika BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas Sangkabira Journal of Health, Education, Economics, Science, and Technology (J-HEST) Malcom: Indonesian Journal of Machine Learning and Computer Science KOLONI Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat STATISTIKA EBAMUKAI; JURNAL PENGABDIAN ILMU PENGETAHUAN DAN TEKNOLOGI
Winda Ade Fitriya B
Universitas Cenderawasih
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The Effect of Improving Human Resources for Student Interest in Selecting University on Food Security and Health: Structural Equation Modeling (SEM) Justin Eduardo Simarmata; Ferdinandus Mone; Debora Chrisinta; Winda Ade Fitriya B
RANGE: Jurnal Pendidikan Matematika Vol. 6 No. 1 (2024): Range Juli 2024
Publisher : Pendidikan Matematika UNIMOR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jpm.v6i1.6308

Abstract

The selection of State Universities by students has a significant impact on improving the quality of human resources, so it can also affect the improvement of food security and health. This study aims to understand the extent of students' interest in selecting university which contributes to improving human resources and can indirectly affect food security and health. This study uses the Structural Equation Modeling (SEM) method to analyze the interaction between latent variables. Data was collected through questionnaires from high school students on the Indonesia-Timor Leste border. The data used in this study include students' interest in selecting university (Y), education and knowledge (X1), skills and abilities (X2), food security (X3), and health (X4). The results showed that students' interest in selecting university had a significant correlation with improving human resources through education by 90% (X1) and 84% (X2). The impact of this increase in human resources is also seen in the improvement of food security and public health which provides a correlation of 98% (X3) and 81% (X4).
Analisis Faktor yang Mempengaruhi Harga Beras di Provinsi Papua Menggunakan Regresi Linear Berganda Kobak, Unyil; Paranoan, Nicea Roona; Aryanto, Aryanto; B, Winda Ade Fitriya
Journal of Health, Education, Economics, Science, and Technology Vol. 7 No. 2 (2025): Journal of Health, Education, Economics, Science, and Technology
Publisher : Journal of Health, Education, Economics, Science, and Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/

Abstract

The food security of a country decreases, then the price of staple foods will increase. This price increase can worsen the economic gap and can trigger an increase in poverty rates. Indonesia is one of the countries that has a major food need, namely the need for rice, which is very large. The importance of rice as a staple food and maintaining the stability of rice prices are things that need to be considered. The instability of rice prices can affect the lives of people in a country or region. This study using the price of rice as a response variable and four predictor variables including the farmer's exchange rate, total rice production, and corn prices. The analysis method using multiple linear regression analysis. To see the goodness of the model formed by looking at the coefficient of determination (R2). The results of this study indicate that all research variables do not have a significant effect on influencing the price of rice in Papua Province. The coefficient of determination value obtained from the multiple linear regression model formed is 4.4%.
Analysis of Stunting Data in Indonesia Using K-Means and Self Organizing Map (SOM) Allo, Caecilia Bintang Girik; Nicea Roona Paranoan; Winda Ade Fitriya B; Bobi Frans Kuddi; Feby Seru
Statistika Vol. 25 No. 2 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i2.7778

Abstract

Abstract. Stunting is a global public health concern, including in Indonesia. The Indonesian government establishes a target for stunting prevalence reduction every year. The government is aiming for a stunting prevalence of 18% in 2025. The government certainly requires policy recommendations to achieve this target. Clustering analysis can be used to identify provinces with similar characteristics or those that still require special attention based on stunting related indicators. There are several clustering methods, including K-Means and Self-Organizing Map (SOM). This study aims to classify provinces in Indonesia based on indicators related to stunting and to compare the performance of two clustering methods. Based on the obtained data, it was found that the data contains outliers. The best clustering method can be determined using the Silhouette Coefficient (SC) and Davies Bouldin Index (DBI). The results showed that the highest SC value, 0.62, was obtained using the SOM method and the lowest DBI, 0.75, was obtained also using SOM method. Two clusters were formed using the SOM method. Cluster 1 consisted of 36 provinces in Indonesia. Cluster 2 consisted of 2 provinces, namely Highland Papua and Central Papua.
Co-Authors Allo, Caecilia Bintang Girik Allo, Cecilia Bintang Girik Aryanto Aryanto Bobi Frans Kuddi Caecilia Bintang Girik Allo Chrisinta, Debora FEBY SERU Felycitae Ekalaya Appa Hamzah, Hardi Imam Mishbach Kobak, Unyil Lolita Tuhumena mone, ferdinandus Muhammad Hisyam Musakar, Rafika Dewitasari Kahar Nazal, Muhammad Asghar Nicea Roona Paranoan Papriani, Nada Pertiwi Rahmadhan, Richardo Valentino Saputro, Agung Dwi Sari, Nur Nilam Simarmata, Justin Eduardo Sitti Rosnafi’an Sumardi Sumardi, Sitti Rosnafi'an