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All Journal Jurnal Statistika dan Aplikasinya Journal of Data Insights
Zahra Aura Hisani
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Mathematics Social Sciences Other

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Sentiment Analysis of Public Opinion on Handling Stunting in Indonesia using Random Forest Ningrum, Ariska Fitriyana; Ihsan Fathoni Amri; Zahra Aura Hisani
Jurnal Statistika dan Aplikasinya Vol. 8 No. 1 (2024): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.08103

Abstract

The issue of stunting is important to address, as it has the potential to affect the human resource potential and is related to health levels, and even child mortality. The Indonesian government targets to reduce the stunting rate to 14 percent by 2024 through an accelerated stunting reduction program as an effort to improve the nutritional status of the society and also reduce the prevalence of stunting or stunted children. Understanding public sentiment towards the stunting initiative is crucial for policymakers and stakeholders to design effective interventions and allocate resources efficiently. This study aims to analyze public sentiment related to stunting in Indonesia, which impacts children's growth and development. Through the use of sentiment analysis techniques, this study aims to understand public perceptions and attitudes towards the issue of stunting, evaluating whether the general sentiment is positive, negative or neutral. The results of this analysis are expected to provide useful insights for policymakers and health practitioners in designing and implementing more effective strategies to address the issue of stunting. This study conducted sentiment analysis from crawled Twitter data, showing positive and negative sentiments of the public regarding stunting handling in Indonesia. Furthermore, classification analysis using random forest was conducted and resulted in an accuracy score of 97.5%. The model is good enough but, we suggest trying other algorithms in further research.
Fuzzy Gustafson Kessel for Infrastructure Development Strategy in South Sumatra Province: Fuzzy Gustafson Kessel Untuk Strategi Pembangunan Infrastruktur Di Provinsi Sumatera Selatan Ariska Fitriyana Ningrum; Oktaviana Rahma Dhani; Febi Anggun Lestari; Zahra Aura Hisani; Alwan Fadlurohman
Journal of Data Insights Vol 2 No 2 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v2i2.650

Abstract

Infrastructure development is a strategic element in improving public services and economic growth. South Sumatra Province, with its large economic potential, faces challenges in managing efficient and sustainable infrastructure development. This research aims to apply the Fuzzy Gustafson Kessel (FGK) method in decision making related to infrastructure development in South Sumatra Province. FGK combines fuzzy logic with Gustafson Kessel clustering algorithm to handle uncertainty and data variation from various stakeholders. The data used in this study includes population and geographic census data from the Central Bureau of Statistics of South Sumatra Province in 2023, with five indicators: population, area, population growth rate, population density, and poverty rate. The results show that South Sumatra is divided into three main clusters based on its infrastructure and demographic characteristics. This clustering is expected to improve the effectiveness and efficiency of infrastructure development decision-making, provide more appropriate policy recommendations, and potentially be applied in other regions with similar challenges.
Co-Authors Alwan Fadlurohman Ariska Fitriyana Ningrum Febi Anggun Lestari Ihsan Fathoni Amri Oktaviana Rahma Dhani