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All Journal Jurnal Informatika dan Rekayasa Perangkat Lunak
Fadhil Muhamad Basysyar
STMIK IKMI Cirebon
Computer Science & IT

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Analisis Sentimen Opini Supporter Pengguna Youtube terhadap Sistem Pembelian Tiket Pertandingan Persib menggunakan Metode Naïve Bayes Adam Arifian Alamyah; Rini Astuti; Fadhil Muhamad Basysyar
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10310

Abstract

Reporting about Persib cannot be separated from the role of the media from the era of the union until today. The first news about Persib in the media was at least in November 1904, when the Priangan Association (PVB) was recorded as the first association in Bandung. Using Descriptive Analysis, in the form of a word cloud, which is used in this research to identify and form word patterns that can be associated with other words that are considered important. Naïve Bayes Classifier Method. used in this research to identify and form word patterns that can be associated with other words to obtain information that is considered important. YouTube has become one of the largest platforms for sharing visual content on the internet. One of the topics that is being widely discussed is the ticket purchasing system for Persib Bandung matches. This has invited a lot of reactions, especially from the community, especially residents of West Java. This causes the controversy to become a polemic. Therefore, a method is needed to classify reviews automatically by conducting sentiment analysis. In this research, 2129 comment data in several contents discussed the Persib Bandung match ticket system. The aim of this research is to classify the analysis. review of the polemic of the match ticket system using the Naïve Bayes algorithm.
Menentukan Nilai Gizi pada Balita Menggunakan Algoritma Support Vektor Machine (SVM) di Posyandu Kelurahan Ciherang Silvia Dini Widianti; Rini Astuti; Fadhil Muhamad Basysyar
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10274

Abstract

Determining nutritional status in toddlers is based on age, weight and height. The process is still done manually, resulting in the resulting data being less relevant. This research serves to provide information about determining the nutritional status of toddlers so that the community and officers at Posyandu Ciherang Village. The problem of this study is to determine the growth and development of nutritional status in toddlers at Posyandu Ciherang Village. Data obtained from Posyandu at the village level whose activities are carried out once a month by cadres under the technical guidance of the puskesmas. Based on the existing problems, a system for determining the nutritional status of toddlers is needed to make it easier to get the right results. The method to be used is Support Vector Marchine (SVM) which is a method of classifying data and providing a basis for early preventive action in overcoming nutritional problems in toddlers. The purpose of this study is to determine the nutritional status of toddlers there are 3 criteria needed, namely the age of toddlers, weight and height. The Support Vector Marchine (SVM) algorithm is considered more optimal because it is able to analyze the best results. The results of this study are expected to provide better insight into determining nutritional values in toddlers. Based on the results show True Less (TK) on pred.NORMAL is 31 records classified as malnutrition and True Normal (TN) on pred.NORMAL is 267 records classified as normal nutrition with the smallest result of class recall 76.52% and the smallest result of class precision 76.52%. From these results it can be concluded that the accuracy rate with the Support Vector Marchine (SVM) algorithm is 85.58%.
Co-Authors Adam Arifian Alamyah Rini Astuti Silvia Dini Widianti