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All Journal Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa Algoritma: Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian dan Angkasa
Rizky Saputra Tobing
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Astronomy Earth & Planetary Sciences Mathematics

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Peran Vital Kemampuan Bahasa Indonesia Yang Tepat Dalam Pembelajaran Himpunan Matematika Bagi Peserta Didik Ika Febriana; Fuji Winanti; Mikolis Etimanta Ginting; Rizky Saputra Tobing; Usnul Marisa Siregar
Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa Vol. 2 No. 3 (2024): Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bilangan.v2i3.79

Abstract

This research aims to determine the role of good use of Indonesian in the learning process for students, especially in mathematics set material. Apart from that, this research also aims to reveal various theories that are relevant to the problem being researched, and is carried out by re-analyzing data that has been collected from other research results in order to prove the correctness of the data and its validity based on the title of the research. The scope of this research is to measure students' understanding using good Indonesian regarding understanding elements in mathematical set material. The research method used is quantitative research. From the research that has been carried out, it can be seen that every reference used in this research states that the use of Indonesian plays a very important role in the learning process for students.
Penerapan Principal Component Analysis (PCA) untuk Reduksi Dimensi dan Pemetaan Karakteristik Nutrisi pada Produk Makanan Kemasan di Indonesia Rizky Saputra Tobing; Sigalingging, Ocha Hosea; Sinaga, Roberto Karlos; Lubis, Rhamanda Ardiansyah
Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa Vol. 4 No. 1 (2026): Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/algoritma.v4i1.891

Abstract

The increasing consumption of packaged food products in Indonesia reflects modern lifestyle changes but simultaneously raises public health concerns related to high calorie, sugar, and fat intake. Nutritional information presented on food labels consists of multiple interrelated variables, making it difficult to identify dominant nutritional factors that characterize packaged food products. This study aims to apply Principal Component Analysis (PCA) to reduce the dimensionality of nutritional data and to map the nutritional characteristics of packaged food products in Indonesia. The research employs a quantitative exploratory approach using secondary data obtained from nutrition facts labels of 1,651 packaged food products. Seven nutritional variables were initially analyzed, namely total energy, protein, total fat, total carbohydrates, sugar, sodium, and dietary fiber. Data preprocessing included data cleaning, Z-score standardization, and iterative variable selection based on the Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s Test of Sphericity to ensure sampling adequacy and sufficient correlation among variables. Variables with low sampling adequacy and perfect multicollinearity were eliminated, resulting in five variables retained for the final PCA model. Principal components were extracted using the eigenvalue greater than one criterion and confirmed through a scree plot, followed by Varimax rotation to enhance interpretability. The results indicate the formation of two principal components explaining approximately 69.7% of the total variance. The first component represents energy density and macronutrient richness, while the second component reflects carbohydrate-related characteristics, particularly the contrasting pattern between sugar and dietary fiber. Biplot visualization further illustrates product distribution based on these components. The findings demonstrate that PCA effectively simplifies complex nutritional information and provides a clear nutritional mapping of packaged food products, offering practical insights for consumers, producers, and policymakers in supporting healthier food choices in Indonesia.
Co-Authors Fuji Winanti Ika Febriana Lubis, Rhamanda Ardiansyah Mikolis Etimanta Ginting Sigalingging, Ocha Hosea Sinaga, Roberto Karlos Usnul Marisa Siregar