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Journal : Journal of Computer Science Artificial Intelligence and Communications

Sentiment Analysis of Social Media Towards Public Services Using Naive Bayes and Text Mining Rusmin Saragih; Mardiah; Deni Apriadi
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 2 (2024): November 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i2.18

Abstract

The rapid development of information and communication technology has driven the increased use of social media as a means of interaction between the public and service providers. Social media has become a platform for the public to express their opinions on the quality of services they receive, whether in the form of praise, suggestions, or complaints. Therefore, sentiment analysis of social media data can be a strategic tool in evaluating the performance of public services. This research aims to analyze public sentiment towards public services by utilizing text mining techniques and the Naive Bayes Classifier algorithm. The data used was collected from social media platforms such as Twitter and Facebook, followed by a text preprocessing stage that included tokenizing, stopword removal, and stemming. Subsequently, the data was analyzed to classify sentiment into positive, negative, and neutral categories. The test results show that the Naive Bayes algorithm is capable of classifying data with a satisfactory level of accuracy, making it an efficient method for monitoring public perception in real-time. This research contributes to supporting decision-making by government agencies regarding the improvement of public service quality based on publicly available feedback from social media
Analysis of the Effectiveness of Implementing a Queue Algorithm-Based Leadership Scheduling Information System in Government Agencies Mardiah; Nuranisah; Nainggolan, Theodora MV
Journal of Computer Science, Artificial Intelligence and Communications Vol 2 No 2 (2025): November 2025
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v2i2.61

Abstract

This study analyzes the effectiveness of implementing a leadership scheduling information system that utilizes queue algorithms in government agencies. The main objective is to evaluate how the integration of algorithm-based scheduling systems improves efficiency, accuracy, and transparency in managing executive-level appointments and meetings. The research adopts a mixed-method approach, combining quantitative analysis through system performance metrics with qualitative feedback from end-users, including administrative staff and decision-makers. Findings indicate a significant improvement in scheduling efficiency, with reduced conflicts, optimized time slots, and better coordination between departments. Furthermore, the system minimizes manual intervention, thus decreasing administrative errors and enhancing data integrity. The queue algorithm enables a first-come-first-served mechanism that ensures fairness while allowing for priority-based modifications in urgent cases. The implementation also receives positive responses in terms of user satisfaction and perceived usefulness. However, challenges such as user adaptation and technical limitations were identified, suggesting a need for continuous training and system updates. Overall, the integration of a queue algorithm-based scheduling system proves to be an effective solution for improving leadership-level administrative processes in government institutions.
Co-Authors A. Jasmine Haya Aqilah Patrianur Abd. Gafur Ade Budi Setiawan Adi Saputra Agustina, Yulianti Ahmad Ahmaludin Aini Ramadila Aji Jumiono Akbar, M. Ali Aminullah Aminullah, Aminullah Amir, Saiful Andria Andrian Andriana Anggraini, Bela Adinda Anisa Demi Narwanja Anshari, Muhammad Fatih Apriani, Yasri Ari Orizal Asnaniar, Wa Ode Sri Astuti, Lenny Ayu Mutiara Basmanelly Batubara, Kartika Sri Dewi Cut Salsabila Meutiasari Delfitriani Deli Sarnidawati Demonius Sarumaha Deni Apriadi Dessy Suswitha desy wulandari Devi Anisa Dewi Rury Arindari Dian Syahputri Dwi Syaravicena Eka Pandu Cynthia, Eka Pandu Eka Putra EKA YULI HANDAYANI Eliska, Arshyla Erly Krisnanik Evi Kristina Faizin Ridho Fedra Muchtar Ferdi Riza Fiddini Alham Fitria Almahliza Furqan Khalidy Gilang Dwi Fahri Harahap Hadi Siswoyo Handayani, Sri Hasnawati Hendry . Heppi Sasmita Herlina Lia Novianti Ian Alfian Imanuel Zega indah Indra Putra, Edi Susrianto Intan Kusumaningrum Irhamuddin Siregar Kamila, Alya Hasna Khairun Nisa Khairuniza, Nabila Khairunnisa Khalidy, Furqan Kusumawardhani, Damar Labris Shandi Lestari, Armelia Ayunda Lestari, Refa Cahya Leti Purnama Sari LIA AMALIA lia amalia Lidiyani, Nurfitri Lily Marleni Martina Napratilora Maulita, Wike Mawar Mega Yutamy Mina Marlina Muhaimin Adelio Sachi Muhammad Aqil Rusli Muhammad Iqbal Muhammad Khaibar Putra Adithia Muhammad Noor Hasan Siregar Mulya, Sahnur Nafisah Nurulrahmatiah Nainggolan, Theodora MV NANA ALDRIANA Napratilora, Martina Noli Novidahlia Nova Adi Kurniawan Nuranisah Nurliana NURUL HIDAYAH Opie Aulia Fadilah Pepayosa, Enca Pertiwi, Sri Rejeki Retna Qhisthina Atikah Rahman, Afif Rahmawati Ramli Rahmawati, Siti Irma Rahmi Fitria Rahmita Ramadhan, Muhamad Fauzi Ratna Puspita, Neneng Rini Mastuti Ristina Rosauli Harianja Rizki Ananda Rizki, Cindy Atika Rosdiana Rusmin Saragih, Rusmin Saeed, Alabbas Hussein Safitri Putri Derajat Saiful Amir Samsualam, Samsualam Sanggul Maharani Yessa Sariwana Sarumaha, Demonius Shinta Sahara, Arini Siahaan, Sekar Griselda Nadine Silpia, Mega Sintiya Halisya Sintiya Halisya Pebriani Siregar, Friska Anggi Sri Erdawati Sri Jayanthi Sri Wulandari Suci Nurlida Sapitri Suciwaty, Dian Sunarti supristiwendi supristiwendi Syamsiah Nasution Syamsul Rizal Tarmizi, M Tiara Amanda Lestari Tirtawati, Desi Titi Rohmayanti Trimelati, Dinda Army Uli, Tresia Shinta Veithzal Rivai Zainal Viska Annisa Sabrini Yeni Roslita Yudistira Afconneri Yuliana Hutasuhut Yuyun Bewelli Fahmi Zahara, Arini Shinta Zega, Imanuel Zuhana Zunita, Nia