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Menampilkan 1–4 dari 4 artikel
Analisis Data Sentimen Pemain Game Role-Playing Game (RPG) Honkai Star Rail dengan Algoritma Naive Bayes
Firmansyah, Yudis
; Kurniawan, Rudi
; Wijaya, Yudhistira Arie
Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 6
, No 1
(2024)
In the rapidly evolving digital age, the gaming industry has experienced significant growth. One of the games that is currently popular is Honkai Star Rail. This research uses Honkai Star Rail game player reviews as the object of sentiment data research. However, the problem found in sentiment data analysis is the existence of reviews that provide positive or negative ratings as a response from players. There are situations where these labels do not fully reflect the true essence of whether the...
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Analisis Data Sentimen Ulasan Aplikasi Dana di Google Play Store Menggunakan Algoritma Naïve Bayes
Astuti, Windy
; Kurniawan, Rudi
; Wijaya, Yudhistira Arie
Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 6
, No 1
(2024)
In an era of rapid technological advancement, mobile applications, especially e-wallets such as Dana Apps, are becoming increasingly easy to use for digital payment transactions. This innovation drives research on how digital payment platforms build information systems and business strategies through digital platforms. To compete in a growing industry, companies must produce products and services that meet customer needs. Internet user opinions, especially about apps, are important in gathering...
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Analisis Data Sentimen Ulasan Pengguna Aplikasi Shopee di Google Play Store dengan Klasifikasi Algoritma Naïve Bayes
Wartumi, Wartumi
; Kurniawan, Rudi
; Wijaya, Yudhistira Arie
Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 6
, No 1
(2024)
This research focuses on analyzing sentiment data from users of the Shopee e-commerce application using the Naïve Bayes Algorithm method. From 1000 datasets obtained from web scraping, reviews were analyzed to classify sentiment into positive or negative. With a ratio of 80% training data and 20% test data, the model developed achieved an accuracy of 95.5%. The classification results show precision 86.76%, recall 1%, and f1-score 92.91%. Even though the recall is low, the high accuracy shows th...
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Analisis Data Stok Alat Kesehatan menggunakan Metode Regresi Linier Berdasarkan Nilai RMSE
Nurmansyah, Trian
; Kurniawan, Rudi
; Wijaya, Yudhistira Arie
Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 6
, No 1
(2024)
Inventory of healthcare equipment, whether in hospital or clinic settings, represents a significant investment requiring substantial cost allocation. However, estimating these equipment needs often relies solely on the overall available stock, as monthly or yearly requirements tend to fluctuate. Consequently, this approach leads to an inability to meet all necessary equipment needs, resulting frequently in surplus inventory. Therefore, anticipating this issue requires predicting healthcare equip...
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