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All Journal International Journal of Electrical and Computer Engineering JURNAL MEDIA INFORMATIKA BUDIDARMA JTAM (Jurnal Teori dan Aplikasi Matematika) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan INTECOMS: Journal of Information Technology and Computer Science Journal of Education and Instruction (JOEAI) JSiI (Jurnal Sistem Informasi) JURNAL PENDIDIKAN TAMBUSAI JOURNAL OF SCIENCE AND SOCIAL RESEARCH JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JISICOM (Journal of Information System, Infomatics and Computing) Journal of Information System, Applied, Management, Accounting and Research JURNAL TEKNOLOGI INFORMASI Jurnal Ekonomi Manajemen Jurnal Pendidikan dan Konseling Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Sains dan Teknologi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) SENADA : Semangat Nasional Dalam MengabdI Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Sosial dan Teknologi International Journal Software Engineering and Computer Science (IJSECS) KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Jurnal Tren Bisnis Global Malcom: Indonesian Journal of Machine Learning and Computer Science Publikasi Pengabdian Masyarakat Komputer dan Teknologi (PUNDIMASKOT) Journal of Artificial Intelligence and Digital Business CKI On Spot Kohesi: Jurnal Sains dan Teknologi SENADA : Semangat Nasional Dalam Mengabdi Jurnal Indonesia : Manajemen Informatika dan Komunikasi Repeater: Publikasi Teknik Informatika dan Jaringan International Journal of Applied Mathematics and Computing. International Journal of Information Engineering and Science International Journal of Mechanical, Electrical and Civil Engineering Journal of Engineering, Electrical and Informatics
Arinal, Veri
STIKOM Cipta Karya Informatika Jakarta, Indonesia
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Data Mining Classification in The New Student Admission Process Using The K-Nearest Neighbors Method : Case Study: Yapmi Boarding School Veri Arinal; Tri Wahyudi; Mesra Betty Yel; Nurul Khoiriyah
International Journal of Applied Mathematics and Computing Vol. 1 No. 4 (2024): October: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i4.111

Abstract

The new student admission process is an important activity in educational institutions to ensure that prospective students meet the established admission criteria. However, the selection process is often conducted manually, making it less efficient and prone to subjective assessments. This study aims to implement a data mining classification approach using the K-Nearest Neighbors (K-NN) method to support decision-making in the new student admission process at Yapmi Boarding School. The research utilizes historical admission data consisting of academic scores, interview results, and other admission criteria as classification attributes. The K-NN algorithm was applied to classify prospective students into accepted and rejected categories based on the similarity of their characteristics to previously evaluated applicants. The research methodology includes data collection, preprocessing, classification modeling, and performance evaluation using accuracy metrics. The results demonstrate that the K-NN method is capable of classifying prospective students effectively and can assist admission committees in making more objective and accurate decisions. The implementation of this model contributes to improving the efficiency, consistency, and reliability of the student admission process at Yapmi Boarding School. Therefore, the K-NN algorithm can be considered a viable alternative for supporting educational admission decision systems.
Sentiment Analysis of the Trending Topic #Indonesiagelap on X Using a Naive Bayes Algorithm Based on Particle Swarm Optimization Untung Surapati; Veri Arinal; Tri Wahyudi; Ahmad Fauzan
International Journal of Applied Mathematics and Computing Vol. 2 No. 2 (2025): April: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i2.127

Abstract

The rise of social media has created a digital public sphere that enables users to express their opinions on social and political issues openly and in real-time. One of the most discussed topics on social media platform X is the trending hashtag #IndonesiaGelap, which reflects public concern and criticism regarding various governmental and societal conditions. This study aims to conduct sentiment analysis on tweets containing the hashtag to determine the overall sentiment trend among users. The method employed in this research is the Naive Bayes classification algorithm, known for its simplicity and effectiveness in text classification. To enhance the model’s performance, Particle Swarm Optimization (PSO) is applied to optimize feature selection and parameter tuning. The dataset consists of public tweets collected via the Twitter API, followed by preprocessing, feature extraction using TF-IDF, and sentiment classification into three categories: positive, negative, and neutral. The results indicate that the integration of PSO significantly improves the classification accuracy of the Naive Bayes model compared to the baseline. The majority of tweets related to #IndonesiaGelap exhibit a negative sentiment, indicating widespread public dissatisfaction and criticism. This research is expected to contribute to a better understanding of public perception and serve as valuable input for stakeholders in addressing social issues in the digital age.
Design of a Financial Saving Challenge to Enhance Saving Interest Using the Reinforcement Learning Method Veri Arinal; Nandang Sutisna; Nova Dahliyanti; Dinda Raudhatul Jannah
International Journal of Applied Mathematics and Computing Vol. 2 No. 1 (2025): January: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i1.247

Abstract

This study aims to develop a financial saving application to improve the saving habits of students, particularly in Islamic boarding schools, through an adaptive challenge approach. The system integrates a mobile iOS application with a backend service and Large Language Model (LLM) processing via Ollama. Transaction data entered by users is processed by the backend to generate contextual and personalized saving challenges, applying Reinforcement Learning concepts in an adaptive and data-driven manner. The research adopts a descriptive quantitative method using surveys and system testing with 50 respondents. Results indicate that the application functions as designed, with no significant bugs detected. User evaluation shows high satisfaction, with an average score of 4.3 out of 5, covering ease of use, interface design, and increased awareness of saving. The combination of gamification, reward systems, and adaptive personalization successfully motivates users to save regularly. This system demonstrates the potential of integrating AI-driven personalization to strengthen financial literacy and healthy financial habits among students in a fun and interactive way.methods, and a summary of the results. The abstract should end with a comment about the significance of the results or conclusions brief.
Co-Authors Adella Fitriany Cahyana Agus Tanti Rahayu Ahluna, Faza Ahmad Fauzan Ahmad Ramdani Ahmad Tarwanto Akbar, Yuma Akbarulloh, Feri Akmal Yaqien Ali Akbar Ali Akbar Andriyana Fajar Angel, Gadies Anggi Ramadhan Anisa Puji Ikawati Anita Rosiana Arribatullah, Arribatullah Artha Patricia Atik Budi Paryanti Azizi, Doni Betty Yel, Mesra Bobby Arvian James Buulolo, Rupawan Calvin Bill Christian Gunawan Citra Pricylia Ananda Mulya Dadang Iskandar Mulyana` Dava Septya Arroufu Dede Sarikah Dessyanti Ryantina Dhita Aidilla Dicky Saputra Dinda Raudhatul Jannah Dirgantoro, Bagus Dita Safira Dita Yuliana Dita Yuliana Doni Azizi Edi Nurhadi Edwin Sentosa Fajar, Andriyana Fauzan Azima Fa’aso Lase Febri Yoga Harjanto Feri Akbarulloh Fikryadi, Fikryadi Fiktor Kurnia Fiky Alan Nuari Fileni Zalukhu I Komang Dewa Ananda Putra Ilham Wahyudi Indah Rosmalina Josua Pangaribuan Kiki Setiawan Kurniawan Irfan Nauval M. Rohyan Zidan M.Rafli Fadillah M.Taufik Maulida, Aulia Melani, Melani Afsari Melli Puspita S Miftahul Ulum Miftahul Ulum Miswanto, Miswanto Mohammad Farhan Muhammad Ikhsan Hakim Muhammad Joko Umbaran Kharis Bahrudin Mulya, Citra Pricylia Ananda Nandang Sutisna Nauval, Kurniawan Irfan Nayoan, Vallen Ezra Piter Niarti Agustiani Nova Dahliyanti Nova Esterina Silitonga Novi Septiani Nuary Inaldi Simarmata Nuary Inaldi Simarmata Nugroho, Adityo Purwo Nur Arif Khairudin Nurul Khoiriyah Nurwijayanti Paryanti, Atik Budi Patricia, Artha Prabowo, Renno Sandi Prabowo, Reno Sandi Prakoso Angga I Purnomo, Bening Sari Puspita, Melli Putra, Adaffi Aditya Putra, Adhy Hantar Putri Nugraheni Utami Putri, Seftiana Eka Radikto Rahayu, Agus Tanti Ramadhan, M. Anggi Raudhan, Muhammad Nurur Refi Nabillah Royadi Reza Setiawan Reza Setiawan Reza Wanandi Riko Afriandika Rindy Julianda Rizky Adawiyah Rodhiyah Rodhiyah Romadan, Diva Putra Ronny Budi Santoso Rusmarhadi, Irma Ryantina, Dessyanti Safira, Dita Saidah, Andi Sarimole, Francis Matheus Sarimole, Frencis Matheos Satria Wira Yudha Septiyana Bila Setiawan, Kiki Setya Putra Adenugraha Shakila Shila Wati Shindy Apriyani Siti Nurhaliza Siti Raysyah Stepanus Stepanus Sugeng Sugeng Sugiyono Sugiyono Sugiyono Sugiyono Sugiyono Sugiyono Sutisna Sutisna Sutisna Sutisna Sutisna Sutisna Tri Wahyudi Tundo, Tundo Untung Surapati Wandi Sanip Wardana, Shabrina Sukma Yuliya Putri P Yunita T Lubis