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All Journal JSI: Jurnal Sistem Informasi (E-Journal) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknoinfo Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Ekonomi Bisnis REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Bulletin of Information Technology (BIT) Brilliance: Research of Artificial Intelligence Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan SIGMA: Information Technology Journal Jurnal INKOFAR Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Pengabdian Mandiri Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Lentera Pengabdian Jurnal Informatika Ekonomi Bisnis Riwayat: Educational Journal of History and Humanities VIDHEAS: Jurnal Nasional Abdimas Multidisiplin RECORD Journal of Loyality and Community Development
Butsianto, Sufajar
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Neuroscience Social Sciences Transportation Other

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Sentiment Analysis on Social Media X (Twitter) Against ChatGBT Using the K-Nearest Neighbors Algorithm Arwan Sulaeman, Asep; Danny, Muhtajuddin; Butsianto, Sufajar; Pratama, Suria
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4105

Abstract

This research aims to analyze the public's response to ChatGPT through data obtained from Twitter. Apart from that, it is also to understand whether people's responses tend to be positive or negative towards ChatGPT, as well as to test the performance of the K-Nearest Neighbors (KNN) method in classifying sentiment patterns in tweet data. The sentiment analysis method is carried out by dividing public responses into positive and negative categories. Next, the performance of the K-Nearest Neighbors (KNN) method was tested with varying k values ??to classify sentiment patterns in tweet data. This testing includes dataset division, vectorization of text data using TF-IDF, initialization and training of the KNN model, and evaluation of model performance using metrics such as precision, recall, and f1-score. The results of sentiment analysis show that the majority of people's responses to ChatGPT are positive (74.3%), while 25.7% of responses are negative. Performance testing of the KNN model shows that the highest accuracy of 88% is achieved when the k value is 5. Evaluation of model performance also shows satisfactory levels of precision, recall and f1-score. Based on the research results, it was concluded that sentiment analysis and classification using KNN were effective in understanding people's responses to ChatGPT
Prediction of Employee Assessments for Contract Extensions at PT Sagateknindo Sejati Using the Naïve Bayes Algorithm Naya, Candra; Siswandi, Arif; Butsianto, Sufajar; Febriyanti, Febriyanti
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4170

Abstract

Companies must be selective in conducting employee assessments in order to retain employees with the best performance. When assessing employee performance, it is seen from their perseverance and discipline. However, in reality, good employee performance sometimes gets bad reviews and even gets reprimanded by their superiors. This is caused by the employee assessment monitoring system used, namely only personal assessment without using an assessment system and the data collected is less than optimal. This research uses the Naive Bayes method to process data using a data mining algorithm to obtain predictions that can be used as additional references in making employee performance assessment decisions. Aims to predict employee assessments of contract extensions at PT Sagateknindo Sejati. This research is important because it helps in making more accurate decisions regarding employee contract extensions based on existing historical data. Naive Bayes is a data processing algorithm that is classified as a calculation that is easy to understand but its accuracy results are reliable. It is used because it is efficient in managing data with various attributes and is able to produce predictions based on the probability of each existing attribute. The data used in this research includes various variables, using the Rapidminer supporting application to test the accuracy of the system created. Testing was carried out by preparing 320 data and testing 50 randomly selected data. Test data will be analyzed using the Rapidminer supporting application. The test results produced an accuracy of 83.96%.
Co-Authors Abdul Halim Anshor Agung Nugroho Agus Suwarno Aguswin, Ahmad Aldi Ramadhan Amali, Amali Ananto Tri Sasongko Andre Ardiansyah Andriani Andriani Andriani Andriani Anisah Purnamasari Aprila Hardi, Resty Arief Nur Hidayat ARIF SUSILO Aris Iskianto Aris Iskianto2 Arwan Sulaeman, Asep Asep Muhidin Asep Muhidin Baharudin, Arya Rifaldi Budi Rahardjo, Sugeng Candra Naya Dewi Sekar Arum Dian Riki Pangestu Dicky Winanda Santoso Edi Tri Triwibowo Edi Tri Wibowo Edora Edora Edy Widodo Edy Widodo Eka Nur Arifin Eko Putra, Fibi Elkin Rilvani Endah Yaodah Kodratillah Ermanto Ermanto Ermanto Fauzi Ahmad Muda febriyanti febriyanti Herdiyan, Serly Humam Fathurrahman Ikhsan Romli Irfan, Yusuf Kodratillah, Endah Yaodah Makmun Effendi, M. Mamat Casmat Maryani Manik Maulana, Futuh Muhamad Fatchan Muhammad Faisal Muhammad Fikri Fauzan muhidin, asep Muhtajuddin Danny Naya, Candra Nindi Tya Mayangwulan Nugroho, Agung Nurhali Saepudin Nurhali Saepudin Oktavianti, Risma Nadia Otib Subagja Pratama, Suria Puput Riyanti Purwanto Purwanto Putri Riandani, Andini Retno Fitri Astuti Retno Purwani Setyaningrum Rifa'i, Anggi Muhammad Romli S. Sunge, Aswan Selviana, Vina Setyawan, Wisnu Sifa Fauziah Sifa Fauziah, Sifa Siswandi , Arif Siswandi, Arif Siti Rahayu Sulaeman, Asep Arwan Sunge , Aswan S. Supriyanto, Asep Suratman Suratman Syahlan Sugiarto Tedi, Nanang Triwibowo, Edi Turmud Zy, Ahmad Valentin*, M Ryan Bagus Wachid Hasyim, Wachid Widiyatmoko, Arif Tri Wiyanto Wiyanto Wiyanto Yolanda Alviana