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All Journal Pendidikan Bahasa dan Sastra Indonesia Jurnal Lemuru : Jurnal Ilmu Perikanan dan Kelautan Indonesia Journal of Coastal and Ocean Sciences Ikhtisar: Jurnal Pengetahuan Islam Jurnal Ilmiah AgriSains Innovative: Journal Of Social Science Research Journal of Learning and Technology in Physics Journal of Marine Studies Journal of Aceh Aquatic Sciences Innotech
Rika Astuti
Jaringan Kualisi Untuk Laut Aceh (Kuala), Banda Aceh
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Physics Public Health Social Sciences Other

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Journal : Innotech

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PERANCANGAN SISTEM INFORMASI PENJUALAN BERBASIS WEB PADA UMKM CHEESE STICK ALFAN Astuti, Rika
Innotech: Jurnal Ilmu Komputer, Sistem Informasi dan Teknologi Informasi Vol 1 No 1 (2024): Innotech Issue Januari 2024
Publisher : Universitas Siber Indonesia

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Abstract

Cheese Stick Alfan is one of the micro, small and medium businesses, which until now the production and sales process is still carried out by buyers who come directly. There are still many weaknesses found in the sales process at Cheese Stick Alfan, for example, they have not used technology. a tool to market a product they will sell. so that business actors can sell their products using the existing WEBSITE to cities or villages that are connected to the internet. Therefore, Cheese Stick Alfan requires an information system such as e-commerce to better identify the products being sold and provide convenience. The purpose of this writing is to give even better results, at the Alfan Cheese Stick store, by implementing the concept in the form of a web-based application. The design of this sales system will use the waterfall method and the end result is a web-based application which is also expected to help the sales process at the Cheese Stick Alfan store.
KLASIFIKASI BERITA HOAX POLITIK PADA MEDIA SOSIAL X MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN RANDOM FOREST Astuti, Rika; Tiarma Sipahutar, Angel
Innotech: Jurnal Ilmu Komputer, Sistem Informasi dan Teknologi Informasi Vol 2 No 1 (2025): Innotech Issue Januari 2025
Publisher : Universitas Siber Indonesia

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Social media has become a major source of information as well as a fertile ground for the spread of hoax news, particularly political news. This study examines two classification algorithms, Naive Bayes and Random Forest, to detect hoax news. The data used consists of political news labelled as hoax or non-hoax. The results show that the Random Forest algorithm has better accuracy and performance compared to Naive Bayes in terms of precision, recall, and F1-score. In conclusion, Random Forest is more effective for classifying political hoax news on social media. This research provides important insights into the application of machine learning algorithms in text classification and emphasizes the importance of selecting the right algorithm for optimal results.
Co-Authors . Ermanto Akip, Muhamad Edwarsyah Edwarsyah, Edwarsyah Fahreza, Muhammad Reza Feta, Neneng Rachmalia Fitria Fitria Friyuanita Lubis Giovanni Oktavinanda Gunandar, Jerry Hayatun Nufus Inayah, Safa Aulafi Martoyo, Anang Muhamad Faizul Amirudin Muhammad Haikal Muhammad Kadri, Muhammad MUHAMMAD RIZAL Munandar, Roni Arif Neneng Marlian, Neneng Nur Hikmah Nurmaini Nurmaini Putri, Levi Rianti Rahul, Rahul Riri Ezraneti Saputra, Dedi Dwi Simatupang, Desima Natasya Sulastri, Mila SYAHRIAL SYAHRIAL Syahrul R. Tiarma Sipahutar, Angel Umbekna, Sara Wardhani, Diky Zurba, Nabil