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All Journal Teknika Jurnal Informatika Jurnal Informatika Proceeding International Conference on Information Technology and Business International conference on Information Technology and Business (ICITB) Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Edukasi Islami: Jurnal Pendidikan Islam JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Restikom : Riset Teknik Informatika dan Komputer
Yuni Arkhiansyah
IBI Darmajaya
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering

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Implementasi Naive Bayes Classifier Dalam Menganalisis Sentimen Pelanggan Mie Gacoan Pada Instagram Audina Tazkia; Yuni Arkhiansyah
TEKNIKA Vol. 18 No. 1 (2024): Teknika Januari - Juni 2024
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10851075

Abstract

Pada era digital saat ini, media sosial telah menjadi sesuatu yang umum dan telah banyak digunakan untuk memenuhi kebutuhan masyarakat. Salah satu platform media sosial yang banyak digunakan adalah Instagram. Instagram merupakan sebuah aplikasi yang memungkinkan pengguna untuk memberikan komentar terhadap foto atau video yang dibagikan. Opini dan permasalahan tersebut kemudian dapat diolah menjadi sebuah informasi analisis sentimen. Mie Gacoan merupakan salah satu restoran mie pedas yang populer Indonesia selama beberapa tahun belakangan ini. Dibalik kepopuleran Mie Gacoan pada saat ini, tentunya tidak dapat dipungkiri bahwasannya ada penilaian positif dan penilaian negatif dari pelanggan. Pada penelitian ini ekstraksi fitur dengan menerapkan metode TF-IDF. Kemudian data dibagi menjadi 80% data latih dan 20% data uji. Hasil penelitian ini menunjukan tingkat akurasi sebesar 90.59%, precision 87.50%, recall 95.45%, dan f1-score 91.30%.
Designing An Athlete Selection Application Using The Topsis Method Napitupulu, Erikson Josua; Arkhiansyah, Yuni; Karnila, Sri
Prosiding International conference on Information Technology and Business (ICITB) 2023: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 9
Publisher : Proceeding International Conference on Information Technology and Business

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Abstract

Athletes are a profession that is of great interest to young people in various sports. Psychological factors that support success and the role of coaches in sports are very necessary for the success of talented athletes in their fields. Currently, coaches have certain training programs that aim to increase the athlete's agility, strength, and speed. This program is felt to be less effective because decision-making is done by considering the weighting of two categories, namely physical and psychological. The weight of the criteria obtained will assist coaches in maximizing the physical and psychological abilities of athletes in order to achieve the expected championship targets. For this reason, a plan was created to select talented athletes using the Topsis method (Technique for Others Reference by Similarity to Ideal Solution). This design is facilitated by an Android-based interface with simple logic, an easy-to-understand category calculation input process, and a mathematical model for determining the best athletes so that it can help coaches and be effective in selecting talented athletesKeywords: athletes, training programs, system design, criteria weights, TOPSIS
Co-Authors - Nurjoko -, Rasikun Agus Pahrudin Agus Rahardi Ahmad Muslim Pratama Audina Tazkia Azhar, NorHafizah Binti Chairani Chairani Dani Rofianto dodi setyawan Dwi Saputra, Riko Fitria - Fitria - Hary Sabita Hendra Kurniawan Idin, Nadialyn Binti Koderi Komang Tirte Muhammad Hidayat Nadialyn Binti Idin Napitupulu, Erikson Josua NorHafizah Binti Azhar Rasikun - Rian Sefriadi Rio Kurniawan Rizal, Ruki Safitri, Egi Setiawan, Dodi Yudo Sherli Trisnawati Siti Patimah Sri Karnila Sulyono, Sulyono Vivia Khoirunnisa, Chandry