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All Journal Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika International Journal of Information Engineering and Science
Dita Mawarni
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Computer Science & IT Engineering

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Sistem Pendukung Keputusan Menentukan Pemilihan Lokasi untuk Cabang Baru Toko Liv Beauty Cosmetic menggunakan Metode TOPSIS David Dermawan; Dita Mawarni; Herdina Putri Ahmadi; Indah Permata Sari; Safrizal Safrizal
Uranus : Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Vol. 3 No. 1 (2025): Uranus : Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/uranus.v3i1.657

Abstract

Toko Liv Beauty is one of the business players in the beauty sector that is developing in North Sumatra, specifically in the West Binjai sub-district, Binjai City. As a store that provides various beauty products, this research aims to assist Toko Liv Beauty in determining a strategic location for opening a new branch using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The TOPSIS method was chosen for its ability to analyze alternatives based on positive and negative ideal solutions objectively. A case study was conducted at three potential locations in Binjai: Binjai City, Binjai South, and Binjai North, considering five main criteria: population density, ease of transportation access, number of competitors, rental costs, and building area. The analysis process involves normalizing the decision matrix, calculating weighted values, identifying ideal solutions, and determining alternative preferences. The analysis results show that the location with the highest preference is Binjai North (1), followed by Binjai South (0.5885) and Binjai City (0). Thus, Binjai North is recommended as a strategic location for opening a new branch of Toko Liv Beauty. The implementation of the TOPSIS method in this research is expected to contribute to more effective data-driven decision-making for the business development of Toko Liv Beauty.
Grouping of Toddler Nutritional Status Based on Anthropometric Data in Pekan Kuala Village Using the K-Means Clustering Method Dita Mawarni; Relita Buaton; Kristina Annatasia
International Journal of Information Engineering and Science Vol. 2 No. 3 (2025): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i3.300

Abstract

Nutritional issues among toddlers continue to be a pressing public health challenge in Indonesia, including in Kelurahan Pekan Kuala, where although anthropometric data have been systematically collected through the e-PPGBM application, they have not been thoroughly explored in terms of clustering patterns that may provide deeper insights. This study seeks to classify toddler nutritional status by applying the K-Means Clustering method to anthropometric indicators such as age, weight, height, and weight-to-height index. A dataset consisting of 648 entries recorded between January and March 2025 was processed using MATLAB R2014b with cluster variations set at 5, 7, and 9. The analysis revealed that the majority of toddlers were categorized as having good nutritional status, while a portion of the sample was identified as undernourished and some at risk of overnutrition, indicating the diverse nutritional challenges faced by this community. Furthermore, testing the variance across cluster configurations demonstrated that the 9-cluster model yielded the lowest variance score of 0.20, thereby representing the most optimal solution since it produced more homogeneous, balanced, and stable clusters compared to other configurations. These outcomes highlight the importance of data-driven approaches in public health planning, as the clustering results not only provide a clearer picture of nutritional distribution among toddlers but also serve as a foundation for more evidence-based and targeted intervention strategies. By offering a more granular understanding of nutritional variations, this research is expected to support local health authorities in developing customized nutrition programs, allocating resources more effectively, and ultimately improving child health outcomes in Kelurahan Pekan Kuala and similar communities across Indonesia, where malnutrition and overnutrition risks continue to coexist.
Co-Authors Buaton, Relita David Dermawan Herdina Putri Ahmadi Indah Permata Sari Kristina Annatasia Safrizal Safrizal