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All Journal Jurnal Media Infotama International Journal of Artificial Intelligence Research JurTI (JURNAL TEKNOLOGI INFORMASI) Jurnal Sistem Komputer dan Informatika (JSON) GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Indonesian Journal of Engineering Research Jurnal Dehasen Untuk Negeri Jurnal Media Computer Science Jurnal Komputer, Informasi dan Teknologi
Rizka Tri Alinse
UNIVERSITAS DEHASEN BENGKULU
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Other

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Penerapan Kecerdasan Buatan Untuk Deteksi Trafik Jaringan Tidak Wajar Berbasis Phyton Jurusan Teknik Jaringan Komputer Jusuf Wahyudi; Ahmad Asyhari; Rizka Tri Alinse; Wahyu Hidayat; Kharien Eka Putri
Jurnal Dehasen Untuk Negeri Vol 3 No 2 (2024): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jdun.v3i2.11099

Abstract

This community service activity is motivated by the gap in students’ understanding of information technology developments, particularly in network security and artificial intelligence. The purpose of this activity is to provide education on the application of artificial intelligence to detect abnormal network traffic and to enhance students’ readiness in facing technological advancements. The method used is interactive socialization and education through presentations, discussions, and question-and-answer sessions. The activity was conducted through preparation, implementation, and evaluation stages. The results indicate an improvement in students’ knowledge and understanding of network technology and artificial intelligence. In addition, participants showed high enthusiasm during the activity, as reflected in active participation and numerous questions raised. This activity also had a positive impact on increasing students’ motivation to learn more about information technology. Therefore, this program contributes to reducing the digital gap and improving students’ competencies to better prepare them for challenges in the technological era.
The Use of Apriori Method in Forecasting the Number of New Students Lena Elfianty; Jhoanne Fredricka; Rizka Tri Alinse
International Journal of Artificial Intelligence Research Vol 8, No 1 (2024): June 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1709

Abstract

The development of information technology has significantly influenced many sectors, including education. Higher education institutions are required to manage and analyze data effectively in order to support decision-making processes. One of the challenges faced by universities is predicting the number of new students each academic year. The uncertainty in the number of applicants can affect academic planning, facility preparation, and marketing strategies carried out by the institution. This study aims to apply the Apriori method to analyze new student admission data in order to discover patterns and relationships within the data that can be used as a basis for forecasting the number of new students in the following academic year. The research method used includes data collection through observation, interviews, and literature study. The data used in this study are historical data of new student registrations from previous years.The analysis process is carried out using the Apriori algorithm to identify frequent itemsets and association rules based on support and confidence values. The results of the study indicate that the Apriori method is capable of identifying patterns and relationships among variables in the new student registration process. The information generated from this analysis can assist universities in developing more effective strategies for student recruitment and admission planning. By implementing a data mining approach using the Apriori method, educational institutions are expected to utilize their existing data to generate valuable information that supports strategic decision making and improves forecasting accuracy for new student admissions
Co-Authors Agung Laksono Ridwan Ahmad Asyhari Arius Satoni Kurniawansyah Asnawati Asnawati Dewi Murniati Dewi Suranti Dzaki Muhammad Alwan Felic Valentino Feri Hari Utami Fredricka, Jhoanne Herlina Latipa Sari Jusuf Wahyudi Khairil Khairil Kharien Eka Putri Lena Elfianty Leni Ekasari Lola Eris Monika M. Afif Alfuadi Maryaningsih Maryaningsih Muhammad Anugrah Nadia Elisa Suhardi Rahma Safitrah Riki Irawansyah Rina Julita Sahlino Sahlino Sallaby, Achmad Fikri Sapri Sapri Siswanto Siswanto Venny Novita Sari Wahyu Hidayat Yupianti, Yupianti