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All Journal Jurnal Informatika Jurnal Ilmiah KOMPUTASI Jurnal Pengabdian UntukMu NegeRI Journal of Information Technology and Computer Science Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini Journal of Information Technology and Computer Science (JOINTECS) Teknika: Engineering and Sains Journal Jurnal Sains dan Informatika Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOISIE (Journal Of Information Systems And Informatics Engineering) JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Jurnal Pengabdian Masyarakat IPTEKS Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Tekinkom (Teknik Informasi dan Komputer) Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Indonesian Journal of Cultural and Community Development Indonesian Journal of Law and Economics Review Jurnal Penelitian Sekolah Tinggi Ilmu Kesehatan Nahdlatul Ulama Tuban Jurnal Teknik Informatika (JUTIF) Community Empowerment JPM: JURNAL PENGABDIAN MASYARAKAT Proceedings Series on Physical & Formal Sciences PELS (Procedia of Engineering and Life Science) Procedia of Social Sciences and Humanities Jurnal Algoritma Indonesian Journal of Islamic Studies Publikasi Pengabdian Masyarakat Komputer dan Teknologi (PUNDIMASKOT) JOINCS (Journal of Informatics, Network, and Computer Science) SAGA: Journal of Technology and Information Systems Jurnal Penelitian Innovative Technologica: Methodical Research Journal PEDAMAS (Pengabdian Kepada Masyarakat) SAINTEK Physical Sciences, Life Science and Engineering Indonesian Journal of Applied Technology Journal of Internet and Software Engineering Prosiding Seminar Nasional Unimus Advances in Cancer Science Journal of Electrical Engineering Manajemen Pelayanan Kesehatan IJHCS Smatika Jurnal : STIKI Informatika Jurnal Academia Open
Uce Indahyanti
Universitas Muhammadiyah Sidoarjo
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Journal : Academia Open

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Sentiment Analysis of Potential Presidential Candidates 2024: A Twitter-Based Study: Analisis Sentimen Calon Presiden Potensial 2024: Sebuah Studi Berbasis Twitter Yulian Findawati; Uce Indahyanti; Yunianita Rahmawati; Ratih Puspitasari
Academia Open Vol. 8 No. 1 (2023): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.8.2023.7138

Abstract

This study aims to analyze the sentiment towards potential presidential candidates for the 2024 election in Indonesia based on Twitter users' opinions. Three prominent figures, Ganjar Pranowo, Anies Baswedan, and Prabowo Subianto, were surveyed to gauge their electability. Using machine learning classification methods, Support Vector Machine, Bernoulli Naïve Bayes, and Logistic Regression, sentiment classification was performed. The findings indicate that Twitter users expressed predominantly positive sentiments towards each potential candidate. The evaluation of the classification algorithms showed SVM with 84% accuracy, Bernoulli Naïve Bayes with 77%, and Logistic Regression with 84%. This research sheds light on public sentiment towards potential leaders, offering valuable insights for political strategists and decision-makers in shaping effective election campaigns. Highlight: Sentiment Analysis: The study employs machine learning techniques to analyze the sentiments expressed by Twitter users towards potential presidential candidates for the 2024 election in Indonesia. Positive Sentiments: The findings reveal that Twitter users predominantly exhibit positive sentiments towards all three potential candidates, Ganjar Pranowo, Anies Baswedan, and Prabowo Subianto. Election Insights: This research provides valuable insights into public sentiment, offering valuable information for political strategists and decision-makers in devising effective election campaigns for the upcoming presidential election. Keyword: Sentiment Analysis, Twitter Users, Potential Presidential Candidates, Machine Learning, Election 2024
Optimization of Stunting Prevention and Reduction through Early Detection Application, Sunting, based on Forward Chaining Inference Machine. : Optimalisasi Pencegahan dan Penurunan Stunting Melalui Aplikasi Deteksi Dini Sunting Berbasis Mesin Inferensi Forward Chaining Ika Ratna Indra Astutik; Uce Indahyanti; Evi Rinata
Academia Open Vol. 8 No. 2 (2023): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.8.2023.7267

Abstract

Stunting is a chronic malnutrition problem caused by a prolonged lack of sufficient nutrient intake, resulting in impaired growth and shorter stature (dwarfism) in children compared to age standards. In Indonesia, the prevalence of stunting remains high according to WHO standards, mainly due to the limited information available on stunting, particularly regarding preventive measures. In the era of Industry 4.0, rapid technological advancements, especially in the field of healthcare, have provided enhanced access to information and early disease diagnosis through expert system-based applications. The objective of this research is to design an application that assists the community in early detection of stunting in children, enabling timely intervention. The chosen approach involves forward chaining inference machine, testing input symptoms to draw conclusions based on the knowledge rules stored in the knowledge base. The outcome of this research is an application that facilitates parents and integrated service posts in preventing stunting disorders in children. Highlight: Intervensi Tepat Waktu: Aplikasi ini memungkinkan deteksi dini stunting, memungkinkan intervensi tepat waktu untuk mencegah gangguan pertumbuhan pada anak. Pendekatan Sistem Pakar: Memanfaatkan inferensi rantai maju, aplikasi menggunakan pengetahuan Integrasi Teknologi dan Layanan Kesehatan: Memanfaatkan kemajuan Industri 4.0, aplikasi ini menjembatani kesenjangan antara teknologi dan layanan kesehatan, memberdayakan masyarakat dan pos layanan terpadu untuk memerangi stunting secara efektif. Kata kunci: Stunting, Sistem pakar, Deteksi dini, Pelayanan kesehatan terpadu, Industri 4
Co-Authors Abidin, Husnul Ade Eviyanti Ade Eviyanti Aditya, M. Fahrul Rizki Afidah, Dewi Nur Aisha Hanif Alfinda Ayu Hadikasari Anis Farihah, Anis Ariansyah, Achmad Arif Senja Fitrani Arif Senja Fitroni Aris Hendra Prayoga Astutik, Ika Ratna Indra Awalludin, Krisna Azizah, Risma Nur Azmuri Wahyu Azinar Berlian Putri Pertiwi Busono, Suhendro Cecep Kusmana Cholifah, Cholifah Cholifah, Cholifah Cindy Cahyaning Astuti Dafit Setiawan Jaya Damasta, Ifanda Reza Deby Kurniawan Armananda Dewi Komala Sari Edi Widodo, Edi Eko Agus Suprayitno Eriyanto, Sandi Eko Evi Rinata Fahmawati, Zaki Nur Fahmi, M. Yusril Fery Febbyanto Firdausi Usqi Salsabilah Firmansah, Noval Fitri Nur Latifah Fitroni, Arif Senja Hadikasari, Alfinda Ayu Hamzah Setiawan Ika Ratna Indra Astutik Irwan Alnarus Kautsar Khubro, Jamaluddin Jumadil Krisfianto, Moh Ifan Krisnaningsih, Diah Kurniawan, Wildan Lely Ika Mariyati Lily Puspa Dewi Maghfiroh, Alfiah Malihatin S, Ulfah Mauliana, Metatia Intan Metatia Intan Mauliana Moch. Aji Bagus Firmansyah Mochamad Alfan Rosid Mochammad Donni Kurniawan Muhammad Arsyad Dhani Muhammad Syamsuddin Nisak , Umi Khoirun Novia Ariyanti Nuril Lutvi Azizah Pertiwi, Berlian Putri Prayugah, Indra Putra, Rolando Jordan Permana Rafiiqa, Tasya Ramdansyah, Adiffanani Ratih Puspitasari Rohman Dijaya Rolando Jordan Permana Putra Setiawan, Hamzah Siti Nur Haliza Suhendro Busono Suhendro Busono Sukarjadi Sukarjadi Sumadyo, Sasmito Bagus Sumarno Sumarno Suryani, Siti Dwi Suseno Ardiansyah Syahrul Ibnu Rafi Tutut Anjarsari Umi Khoirun Nisak Usabili, Syaikhina Vevy Liansari via nabila banda Wahyu Santoso Yahya Anugerah Dwi Khurrota A'yunan Yoyok Supriyono Yulian Findawati Yulius Hari Yunianita Rahmawati Yunianita Rahmawati, Yunianita Yuwanto, Mahmud Adi Zaki Nur Fahmawati Zamorano, Ifan