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All Journal UNP Journal of Statistics and Data Science
Eujeniatul Jannah
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Panel Data Regression on Gross Regional Domestic Product in West Sumatra Eujeniatul Jannah; Admi Salma; Syafriandi Syafriandi
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-iss1/328

Abstract

Economic growth is assessed by the amount of gross regional domestic product (GRDP) as part of the development of people's welfare. West Sumatra Province needs a development plan that is able to produce GRDP per capita population of 9 to 11 times the current economic growth. To examine the economic growth of a country, not only using cross section data, because it is important to observe the behavior of the research unit over several periods of time. So that research is carried out whether there is an influence on the level of labor force participation, average length of schooling, life expectancy, and the number of poor people on GRDP per capita in districts / cities in West Sumatra in 2020-2023 using panel data regression. This research is an applied research with secondary data obtained from the Regency / City RPJPD document and the official website of the West Sumatra Statistics Agency consisting of 19 districts / cities as objects and the period 2020-2023.   The factors that are significant to GRDP per capita are average years of schooling and life expectancy with the selected model, namely the fixed effect model. The model has a good ability to explain the dependent variable with a value of 82.72%
Implementation of Text Mining for Emotion Detection Using The Lexicon Method (Case Study: Tweets About Pemilu 2024) Afifah Salsabilah Putri; Eujeniatul Jannah; Dodi Vionanda; Syafriandi
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-iss1/348

Abstract

The presidential election is a five-year event that is an important and crucial moment in the realisation of democracy in the Unitary State of the Republic of Indonesia (NKRI). In the modern political era, the development of information technology has had a significant impact in changing the way people interact and express their views on political issues, including in the Presidential election.  One of the social media platforms that is often used to debate political and social issues is Twitter. The analysis method used in this research is sentiment and emotion analysis with a lexicon-based approach. The research stages consist of twitter data collection, data preprocessing, and emotion feature extraction. The first word to be highlighted in the 2024 election series on twitter social media is Anies. Trust is the most dominant emotion towards the three candidate pairs, namely Anies Muhaimin, Prabowo Gibran, and Ganjar Mahfud, showing high public trust.
Fuzzy C-Means Based Clustering of Central Java’s Regencies and Cities Using Economic Welfare Indicators 2023 Winda Fariza, Winda Fariza; Syafriandi Syafriandi; Fadhira Vitasya Putri; Eujeniatul Jannah
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (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-iss4/414

Abstract

This study aims to cluster the regencies and cities in Central Java Province based on economic welfare indicators using the Fuzzy C-Means (FCM) method. The motivation for this research arises from the evident disparities in development outcomes across regions in Indonesia, particularly in Central Java. Several areas in this province continue to experience high poverty rates, low income, and poor human development despite improvements in labor force participation in others. Five key indicators were used: Labor Force Participation Rate (TPAK), Open Unemployment Rate (TPT), Percentage of Poor Population (PPM), Average Net Income (RPB), and Human Development Index (HDI). The data, obtained from Badan Pusat Statistik (2023), were standardized and analyzed using the FCM algorithm with optimal clusters determined via the elbow method. The clustering results show three distinct regional groupings: Cluster 0 includes areas with relatively high HDI and income despite lower labor participation and higher poverty; Cluster 1 comprises urbanized areas with high labor participation but lower HDI; and Cluster 2 represents the most disadvantaged areas with low income, high unemployment, and poor development outcomes. These findings offer a valuable foundation for targeted policy interventions and strategic regional development planning. Fuzzy C-Means proves to be an effective approach for uncovering nuanced regional profiles in socio-economic development.
Co-Authors Admi Salma Afifah Salsabilah Putri Dodi Vionanda Fadhira Vitasya Putri Syafriandi Syafriandi Syafriandi Winda Fariza, Winda Fariza