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All Journal Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) SIENNA
Muhammad Yusril Pratama
Universitas Muhammadiyah Kotabumi
Computer Science & IT Engineering Other

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WEB BASED ONLINE SHOP DESIGN SYSTEM AT AR SHOP Ulfa Arma; Muhammad Yusril Pratama; Putri Afifah; Khusnul Khotimah
Sienna Vol 4 No 1 (2023): Sienna Volume 4 Nomor 1 Juli 2023
Publisher : LPPM Universitas Muhammadiyah Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

An online store website facilitates both buyers and sellers to view products anytime and anywhere, while allowing sellers to easily promote their items to a wide audience. The lack of effective product promotion has resulted in a decrease in the store's revenue and manual inventory management. The purpose of this research is to enhance sales at AR Store and assist in checking product inventory to streamline and expedite services at AR Store. The Waterfall method is employed, which involves the following steps: Analysis, Design, Coding, and Testing. The system is designed using programming languages such as HTML, CSS, and PHP. This research yields an online store website that provides information about products and available stock.
Analisis Sentimen Chat GPT sebagai Masa Depan Pekerja pada Media Sosial Youtube menggunakan Algoritma Klasifikasi Naive Bayes Muhammad Yusril Pratama; Ulfa Arma Putri; Putri Afifah Daina Angraini; Dian Puspita; Fandi Kurniawan
Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Vol 14, No 2 (2023): Desember
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jsit.v14i2.3391

Abstract

Penelitian ini fokus pada implementasi analisis sentimen dalam percakapan di YouTube dengan bantuan Chat GPT dan teknik klasifikasi Naive Bayes. Eksperimen menggunakan data percakapan antara pengguna YouTube dan chatbot GPT untuk memahami bagaimana algoritma Naive Bayes dapat mengenali dan mengelompokkan sentimen dalam interaksi tersebut. Hasilnya menunjukkan akurasi yang tinggi dalam klasifikasi sentimen, meskipun tantangan seperti variasi bahasa dan konteks percakapan dapat mempengaruhi hasil analisis. Studi ini menyoroti potensi besar algoritma Naive Bayes dalam membantu memahami interaksi manusia dengan teknologi di media sosial dan menekankan perlunya penyesuaian teknologi untuk masa depan pekerjaan, terutama dalam konteks kompleksitas interaksi di platform seperti YouTube.
Co-Authors Dian Puspita Fandi Kurniawan Khusnul Khotimah Putri Afifah Putri Afifah Daina Angraini Ulfa Arma Ulfa Arma Putri