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All Journal Jurnal Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi ANDHARUPA Jurnal Informatika Jurnal Pilar Nusa Mandiri Indonesian Journal of Artificial Intelligence and Data Mining JITK (Jurnal Ilmu Pengetahuan dan Komputer) JTAM (Jurnal Teori dan Aplikasi Matematika) JURTEKSI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jurnal Teknologi Informasi dan Multimedia JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Indonesian Journal of Data and Science Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Journal of Technology and Informatics (JoTI) Decode: Jurnal Pendidikan Teknologi Informasi Indonesian Journal of Innovation Studies Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi JOMPA ABDI: Jurnal Pengabdian Masyarakat Digital Transformation Technology (Digitech) ABDINE Jurnal Pengabdian Masyarakat Bulletin of Social Informatics Theory and Application Jurnal Pengabdian Kepada Masyarakat Ceria Jurnal Medika: Medika Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif TECHNOVATE Edu Komputika Journal
Subarkah, Pungkas
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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
A Study Concentration Selection With a C4.5 Algorithm, KNN, and Naive Beyes Busyro, Muhammad; Astuti, Tri; Astrida, Deuis Nur; Arsi, Primandani; Subarkah, Pungkas
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4157

Abstract

The course of concentration is a crucial aspect for students at the university amikom purwokerto.This decision doesn't just affect their academic journey., but also determine their readiness in the face of the working world.Various factors that affect the concentration selection, the challenges that students face, as well as solutions to help them choose concentrations that fit their interests and career goals.There are still many students who have been confused in deciding which courses best fit their interests and career goals..This confusion is often caused by a lack of adequate information and proper guidance. This study attempts to analyze the lecture amikom purwokerto concentration of students in the universities of the use of the method c4.5 algorithm 3, k-neareset naighbors and naïve beyes. Academic student data used as the basis analysis to determine the dominance in the lecture concentration.Of the result of the research uses phon 60,24 % decision is, there are using k-neareset naighbors 75.36 % and use naïve beyes 100,00 % there are, the prediction could be the basis for deciding the lecture the concentration by mainstream student.The result is expected to help the university in recommended it to students study concentration related to the election.
IMPROVEMENT OF NAIVE BAYES ALGORITHM IN SENTIMENT ANALYSIS OF SHOPEE APPLICATION REVIEWS ON GOOGLE PLAY STORE Elistiana, Khoerotul Melina; Bagus Adhi Kusuma; Subarkah, Pungkas; Awal Rozaq, Hasri Akbar
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.1486

Abstract

Reviews of the shopee application on the google play store are included in useful information if processed properly. Old or new users can analyze app reviews to get information that can be used to evaluate services. The activity of analyzing application reviews is not enough just to see the number of stars, it is necessary to see the entire contents of the review comments to be able to know the intent of the review. A sentiment analysis system is a system used to automatically analyze a review to obtain information including sentiment information that is part of an online review. The data is classified using Naive Bayes. A total of 1,000 shopee app user reviews were collected to form the sample dataset. The purpose of this study is to determine the sentiment analysis of shopee application reviews in the Google Play Store using the Naive Bayes algorithm. The stages of this research include, data collection, labeling, pre-processing, sentiment classification, and evaluation. In the pre-processing stage there are 6 stages, namely Cleaning, Case folding, Word Normalizer, Tokenizing, Stopword Removal and Stemming. TF-IDF (Term Frequency - Inverse Document Frequency) method is used for word weighting. The data will be grouped into two categories, namely negative and positive. The data will then be evaluated using accuracy parameter testing. The test results show an accuracy value of 81%, this result shows that shopee application reviews tend to be negative.
Co-Authors Adam Prayogo Kuncoro Adhimah, Laily Farkhah Aditya Permana, Reza Afifah, Erika Luthfi Alifian , Raditya Sani Amin, M. Syaiful Anggraeni, Epri Anggraini, Nova Anshari, Muhammad Rifqi Anunggilarso, Luky Rafi Arief Rachman Hakim Arsi, Primandani Astrida, Deuis Nur Aunillah, Puteri Johar Awal Rozaq, Hasri Akbar Awali, Uston Azhar Andika Putra Azzahra, Delia Oktaviana Bagus Adhi Kusuma Baihaqi, Wiga Maulana Busyro, Muhammad Damayanti, Aulia Shafira Tri Damayanti, Wenti Risma Darmo, Cahyo Pambudi Dermawan, Riky Dimas Dhanar Intan Surya Saputra Dias Ayu Budi Utami, Dias Ayu Budi Dwi Krisbiantoro, Dwi Elistiana, Khoerotul Melina Fadilah, Alif Nur Fandy Setyo Utomo Farizi, Amar Al Firmanda, Reza Arief Hellik Hermawan Hendra Marcos Hendra Marcos, Hendra hidayatulloh, hanif Ikhsan, Ali Nur Ilham, Fatah Irma Damayanti Irma Darmayanti Katiandhago, Bryan Jerremia Khoerida, Nur Isnaeni Khofiyah, Salma Ngarifatul Kholifah Dwi Prasetyo Kartika, Nur Kisma, Atmaja Jalu Narendra Kusuma, Bagus Adhi Kusuma, Velizha Sandy Lestari, Tri Endah Widi Lestari, Vika Febri Marlita, Reva Merliani, Nanda Nurisya Mohammad Imron Muflikhatun, Siti Mustolih, Akhmad Nandang Hermanto Nasar Ghanim, Nadif Nuraini , Rema Sekar Nurul Hidayati Pramudya, Reyvaldo Shiva Prasetya, Eko Budi Prasetyo Kartika, Nur Kholifah Dwi Prastyadi Wibawa Rahayu Prayoga, Iphang Primandani Arsi Pritama, Argiyan Dwi Purba, Mariana Purwadi Ramadani, Nevita Cahaya Ratih Anggraeni Riandini, Dini Riyanto Riyanto Rizki Wahyudi Rofiqoh, Dayana Rohman, M. Abdul Romadoni, Nova Salma Rujianto Eko Saputro Sabaniyah, Arbangi Puput Sadewo, Rizki Salsabiela, Ayuni Sandy Kusuma, Velizha Saputra, Dhanar Sari, Rida Purnama Sarmini Sarmini Satrio Nugroho, Chendri Irawan Septiana Putri, Refida Sugiarti Sugiarti Suhaman, Jali Susanto, Wachyu Dwi Syabani, Amin Syamsiar, Syamsiar Tarwoto, Tarwoto Tri Astuti Triana, Latifah Adi Umma, Rofiqul Utami, Melida Ratna Utomo, Anwar Tri V, Jay Wahyu, Herta Tri Widiawati, Neta Tri Yunita, Ika Romadhoni Yunita, Ika Romadoni