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Pelatihan Aplikasi Perpustakaan Berbasis Web Pada Sekolah Budi Satrya Marwan Elhanafi, Andi; Ruswan Nurmadi; Annisa Ashari; Fahrika Ariyani Lubis; Muhammad Azhari; M. Dahrul Rizki; Dedy Irwan
Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2023): Juni 2023
Publisher : Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/japamas.v2i1.60

Abstract

Web-based library application training at Budi Satrya School is a solution designed to improve the efficiency and accessibility of library services. The purpose of this application training is to make it easier for students and library staff to find, borrow, and return books. Training The app also describes administrative features that allow library staff to manage book collections, student data, and borrowing more efficiently. In this application training, various important menus have been explained such as book search, admin management, student data management, book information management, and website display settings. These menus ensure users can easily access and use the features provided. With this web-based library application training, it is hoped that the library staff of Budi Satrya School can improve skills in library management, improve the better experience for library staff and improve the management of book collections. Evaluation needs to be done to ensure the sustainability and improvement of the quality of services carried out by library staff in managing this application. Keywords: Library, Website, Library Application, Budi Satrya School
ANALISIS SENTIMEN TERHADAP ULASAN APLIKASI MEDIA SOSIAL DI GOOGLE PLAY MENGGUNAKAN ALGORITMA NAIVE BAYES Zainuddin Siregar, Maksum; Marwan Elhanafi, Andi; Irwan, Dedy
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.12841

Abstract

Di era digital saat ini, media sosial seperti Instagram dan TikTok memiliki jutaan pengguna yang aktif memberikan ulasan di platform Google Play Store. Ulasan pengguna ini merupakan sumber data berharga yang dapat membantu pengembang memahami sentimen dan persepsi pengguna. Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna terhadap aplikasi Instagram dan TikTok di Google Play Store menggunakan algoritma Naive Bayes. Metode ini dipilih karena kesederhanaan dan efisiensinya dalam klasifikasi teks. Penelitian ini menunjukkan bahwa sebagian besar ulasan pengguna dikategorikan sebagai sentimen negatif dengan persentase mencapai 87,5%, mengindikasikan ketidakpuasan yang dominan di antara pengguna. Namun, hasil analisis juga mengungkapkan keterbatasan algoritma Naive Bayes dalam menangani variasi bahasa informal dan konteks spesifik dari ulasan. Model cenderung memberikan bias ke arah prediksi negatif meskipun terdapat ulasan yang seharusnya diklasifikasikan sebagai positif atau netral.