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All Journal Building of Informatics, Technology and Science
Rizawanti, Riftika
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Computer Science & IT

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Penerapan Metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Dalam Penentuan Media Promosi Terbaik Rajiansyah, Rajiansyah; Rizawanti, Riftika
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6079

Abstract

The development of increasingly sophisticated technology provides a function which assists salespeople in promoting a product using technology. With the existence of technology, a seller can use this technology as a media tool for the promotion of the products they are marketing or selling. Promotional media is a way that is used by entrepreneurs in conveying, spreading, and offering the products or services they sell so that consumers are interested in buying. In helping carry out promotional media, it is necessary to have social media, where social media is useful or one of the tools used to promote goods or services to consumers. However, as an entrepreneur the selection of a promotional media tool can be a consideration for an entrepreneur. And in solving a problem researchers really need criteria including Location, Fisheries, Cost and Target Market. So with that researchers really need tools in making decisions using methods that can produce values ​​that are in accordance with the expectations of the authors. The tool is SPK and the method used is TOPSIS. So from this it can be concluded that the best promotional media falls on alternative A3 on behalf of Facebook with the first rank with the highest score of 0.953
Classification of High Risk of Obesity in Women using Decision Tree Methods Rizawanti, Riftika; Rajiansyah, Rajiansyah
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7518

Abstract

Excessive body fat accumulation characterizes obesity, a medical condition primarily caused by an energy imbalance. This excess fat is stored throughout the body, including the abdomen, thighs, and arms. Obesity is a global health concern, prevalent in Indonesia, impacting physical, psychological and social well-being. Women are more susceptible to obesity due to a combination of biological and lifestyle factors. A community health center study of 156 patients revealed that 71.20% exhibited central obesity, with women comprising 76.60% of this group and men 31.6%. This study focuses on the disproportionate impact of obesity on women. To better understand and address obesity, classification is crucial. This study uses a Decision Tree method to classify 898 women based on 14 assessments for high obesity risk, comparing its performance using three attribute selection criteria. The Decision Tree (Gini Index) model achieved 77.22% overall accuracy (Figure 12). The Normal category has 83% precision and 88.30% recall. The Overweight category had 62.50% precision and 63.83% recall. The Obese category had 75% precision and 66.67% recall. The Underweight category achieved 100% precision and recall. While the model demonstrates good classification performance, particularly for Normal and Underweight categories, it requires further refinement to better differentiate between Overweight and Obese individuals.
Co-Authors Rajiansyah, Rajiansyah