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All Journal UNP Journal of Statistics and Data Science
Nufhika Fishuri
Universitas Negeri Padang
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Analisis Sentimen Review Aplikasi Chatting di Google Play Store Menggunakan Alghoritma Naïve Bayes Classifer Muhammad Luthfi Alfathan; Dodi Vionanda; Nufhika Fishuri
UNP Journal of Statistics and Data Science Vol. 3 No. 1 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss1/347

Abstract

Chatting application is a medium used to connect two or more people through social media platforms. Based on the results of the survey report, there are 5 chat applications that are often used as a medium of communication, including WhatsApp, Facebook, Telegram, Instagram and Line applications. This research aims to see the sentiment of chat application users, and see how naive bayes performs in analyzing the sentiment of chat application users. The purpose of sentiment analysis in this research is to assess whether a comment related to an issue is negative or positive, as well as a guide in improving the quality or service of a product. From the analysis results obtained, the Naïve Bayes model showed mixed performance depending on the type of application and sentiment. The model generally showed better performance in identifying positive reviews, especially on Facebook, Telegram, and Instagram apps, where recall reached 100%. However, the model performed very poorly in identifying neutral reviews across all apps. To increase accuracy and more balanced sentiment detection capabilities, improvements in data preprocessing, handling data imbalance, or the use of more complex classification methods are needed.
Perbandingan metode Double Moving Average(DMA) dan Double Exponential Smoothing (Brown) Terhadap Tingkat Pengangguran Terbuka (TPT) di Kota Padang Panjang. Nufhika Fishuri; Fadhilah Fitri; Dony Permana
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss2/366

Abstract

The Open Unemployment Rate (TPT) is the percentage of unemployed people in the total labor force. The population included in the labor force is the population aged 15 years and over who has a job but is temporarily not working. Unemployment occurs because of a mismatch between the demand for employment and the qualifications of job seekers. Many job vacancies require graduates with a diploma or degree, so unemployment is one of the problems faced by Padang Panjang City. To overcome TPT in Padang Panjang City, one of the needs is to do forecasting to see how the TPT rate will occur in the coming year. This research uses a forecasting method by comparing the Double Moving Average (DMA) and Double Exponential Smoothing (DES) forecasting values of the Unemployment Rate in Padang Panjang City from 2006 to 2023. This forecasting is done to provide insight into the future condition of the workforce in Padang Panjang City. The results of the forecasting indicate that in 2024, there will be an increase of 0.42%, and for the next 2 years, there will be a decrease
Co-Authors Dodi Vionanda Dony Permana Fadhilah Fitri Muhammad Luthfi Alfathan