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All Journal Journal of Mathematics and Scientific Computing With Applications Al-Aqlu : Jurnal Matematika, Teknik dan Sains
Luthfiyah, Farica
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Engineering Mathematics

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DETERMINASI FAKTOR SOSIAL-EKONOMI TERHADAP FASILITAS PENDIDIKAN MENGGUNAKAN PEMODELAN LOGISTIK ORDINAL DI DESA TUNTUNGAN: Determination Of Socio-Economic Factors On Educational Facilities Using Ordinal Logistic Mideling In Tuntungan Village Maulana, Putri Jehan; Luthfiyah, Farica; Citra, Indah Tribuana; Siregar, Anisa Hafizah
Al-Aqlu: Jurnal Matematika, Teknik dan Sains Vol. 3 No. 1 (2025): Januari 2025
Publisher : Yayasan Al-Amin Qalbu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59896/aqlu.v3i1.129

Abstract

The purpose of this study was to use an ordinal logistic regression model to analyze socioeconomic factors in children's educational institutions in Tuntungan village. This study collected primary data on family economic status (high, medium and low categories) and social environment (very supportive, supportive, less supportive and non-supportive categories) from 100 respondents. The results of the analysis show that families' economic status significantly affects the quality of education facilities for their children, with families with higher economic status having better access compared to families with medium and low economic status. In addition, although not as large as economic position, socio-ecological status is also important. The resulting logit model shows that economic variables have a greater influence on the quality of children's educational institutions compared to social variables. This study emphasizes the importance of improving the local economy to expand access to high-quality education
PROFIT OPTIMIZATION IN WET CAKE SALES USING THE SIMPLEX METHOD AND ITS APPLICATION IN POM-QM Luthfiyah, Farica; Aulia, Riska; Irfan, Muhammad; Wahyu Nuraini, Adinda; Firliansyah Purba, Muhammad
Journal of Mathematics and Scientific Computing With Applications Vol. 4 No. 2 (2023)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The development of population increases every year causing food needs to increase, to meet food needs by increasing food crop productivity so that food availability can be sufficient. Food crops consist of rice, corn, green beans, peanuts, cassava, and sweet potatoes. Productivity in each region has different characteristics and therefore it is necessary to group the regions so that solution can be implemented in accordance with each of the characteristics of the region. The purpose of this study is to group districts/cities in North Sumatera Province based on food crop productivity using the k-means clustering method. Clustering k-means is method of grouping non-hierarchical data that attempts to partition existing data into one or more cluster or groups so that data that has the same characteristics are grouped into one same characterstics are grouped into other groups. The result of this study are the formation of 3 city district clusters namely, cluster 1 amounting to 1 regency/city, cluster 2 totaling 7 districts/cities, and cluster 3 totaling 25 districts/cities.
PROFIT OPTIMIZATION IN WET CAKE SALES USING THE SIMPLEX METHOD AND ITS APPLICATION IN POM-QM Luthfiyah, Farica; Aulia, Riska; Irfan, Muhammad; Wahyu Nuraini, Adinda; Firliansyah Purba, Muhammad
Journal of Mathematics and Scientific Computing With Applications Vol. 4 No. 2 (2023)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v4i2.972

Abstract

The development of population increases every year causing food needs to increase, to meet food needs by increasing food crop productivity so that food availability can be sufficient. Food crops consist of rice, corn, green beans, peanuts, cassava, and sweet potatoes. Productivity in each region has different characteristics and therefore it is necessary to group the regions so that solution can be implemented in accordance with each of the characteristics of the region. The purpose of this study is to group districts/cities in North Sumatera Province based on food crop productivity using the k-means clustering method. Clustering k-means is method of grouping non-hierarchical data that attempts to partition existing data into one or more cluster or groups so that data that has the same characteristics are grouped into one same characterstics are grouped into other groups. The result of this study are the formation of 3 city district clusters namely, cluster 1 amounting to 1 regency/city, cluster 2 totaling 7 districts/cities, and cluster 3 totaling 25 districts/cities.
Co-Authors Aulia, Riska Citra, Indah Tribuana Firliansyah Purba, Muhammad Maulana, Putri Jehan Muhammad Irfan Siregar, Anisa Hafizah Wahyu Nuraini, Adinda