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All Journal Kurawal - Jurnal Teknologi, Informasi dan Industri Jurnal Ilmiah Wahana Pendidikan
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ANALISIS DAN PERANCANGAN APLIKASI IBU SIAGA DENGAN PENDEKATAN METODE WATERFALL Frisky Nita Rahman Saputri; Wahyudi Harianto; Danang Aditya
Kurawal - Jurnal Teknologi, Informasi dan Industri Vol 4 No 1 (2021): Jurnal Kurawal Volume 4, Nomor 1, Maret 2021
Publisher : Universitas Ma Chung

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Abstract

Dalam upaya peningkatan kualitas kesehatan penduduk Indonesia peranan teknologi sangat membantu tenaga medis dalam penyampaian suatu informasi. Dengan memanfaatkan Teknologi mobile dapat dimanfaatkan sebagai penyalur informasi mengenai kesehatan terutama pada imunisasi dasar lengkap, dengan memberikan informasi jelas dan terperinci tentang jenis, manfaat, jangka waktu dan efek samping pemberian vaksin imunisasi sehingga dapat membuat orang tua sadar pentingnya imunisasi sehingga mematuhi dan melengkapi imunisasi dasar lengkap dengan begitu dapat memberikan kekebalan daya tahan tubuh bagi balita sehingga tidak mudah tertular atau terjangkit penyakit tertentu. Dengan perancangan aplikasi yang matang diharapkan mampu memberikan kemudahan bagi programmer dalam mengkoding kedalam bahasa pemrograman. Perancangan aplikasi menggunakan empat model diagram UML (Unified Modeling Language) diantaranya ada beberapa macam diagram yaitu class, activity, sequence dan use case diagram sudah dapat mewakili. Dengan menggunakan pendekatan metode waterfall memberikan data terperinci dan terdokumentasi pada tahapannya.
Analisis Sentimen Komentar Video Youtube Dengan Metode K-Nearest Neighbor Dickna Niken Larasakti; Abdul Aziz; Danang Aditya
Jurnal Ilmiah Wahana Pendidikan Vol 9 No 5 (2023): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (181.567 KB) | DOI: 10.5281/zenodo.7728573

Abstract

This study discusses the result of sentiment analysis of comments on Youtube videos using the K-Nearest Neighbor method. It contains various opinionsabout video content that have been watched. Opinnios given in comments can be used as an assessment and analyze how the sentiment rises. WhileYouTube only facilitates like and dislike buttons which can be seen from the number of clicks, the comments in a video will be used to analyze a sentiment that appears. Through this research, the system will classify each comment contained in the video, and make categories into positive and negative sentences. Before the classification results are obtained, it will go through several stages such as preprocessing, term weighting, similarity calculations and arrive at the calculation of accurate results. In addition to the calculation accuracy, there are also calculations of precision and recall. In this study using 4 scenarios with differences in the percentage of the amount of testing, training data and the value of K, with the aim of finding the best accuracy. The conclusion based on the results of the study is the large amount of training data, testing data and the value of K affects the accuracy results.The amount of testing data and training data also affects the accuracy search time. The highest accuracy is 92.71% with 3% testing data and 97% training data with k-7. The utilization of this KNN method has a good and accurate performance in the process of classifying YouTube video comments
Co-Authors Abdul Aziz Dickna Niken Larasakti Frisky Nita Rahman Saputri Wahyudi Harianto