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All Journal SMATIKA InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Information System for Educators and Professionals : Journal of Information System Information Management For Educators And Professionals (IMBI) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Informasi dan Komputer Jurnal Manajemen Informatika dan Sistem Informasi JURSIMA (Jurnal Sistem Informasi dan Manajemen) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Experimental Student Experiences JURSIMA Jurnal Nasional Teknik Industri, Sistem Informasi dan Teknik Informatika Journal of Computation Science And Artificial Intelligence EDUNOMIC : JURNAL ILMIAH PENDIDIKAN EKONOMI FAKULTAS KEGURUAN DAN ILMU PENDIDIKAN
Odi Nurdiawan
Unknown Affiliation
Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Social Sciences Other

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Implementation of Data Mining to Predict Graduation of SMK Al Huda Kedungwungu Students Using the Naïve Bayes Classifier Algorithm Odi Nurdiawan
Experimental Student Experiences Vol. 2 No. 2 (2023): April
Publisher : LPPM Institut Studi Islam Sunan Doe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58330/ese.v1i4.202

Abstract

The purpose of prediction is to become decision makers and make policies. Understanding the uncertainties and risks that may arise can be considered when making plans. By making these predictions, planners and decision makers will be able to consider other alternatives, so they can take advantage of student graduation data. The algorithm that will be used is the Naive Bayes Classifier Algorithm which is a simple probability classification method based on the application of Bayes' theorem with the assumption that explanatory variables are independent, clues and supporting data in predicting student graduation, namely student behavior, school exams, grades. In practice, the application of the Naive Bayes method applies data train to produce the probability of each criterion for different classes, so that the probability value of these criteria can be optimized to determine predictions of student graduation quickly and efficiently based on the classification carried out using the Naive Bayes method, then from the results of testing with the Naive Bayes method the results obtained an accuracy value of 76 .25%, so this result has very good accuracy. That way this method can be applied in predicting student graduation.
VISUAL SEMIOTIC ANALYSIS OF GAMIFICATION ELEMENTS IN DUOLINGO GERMAN Afifah, Azah; Odi Nurdiawan; Arif Rinaldi Dikananda
Journal of Computation Science and Artificial Intelligence (JCSAI) Vol. 3 No. 1 (2026): Journal of Computation Science and Artificial Intelligence (JCSAI)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/jcsai.v3i1.24

Abstract

The advancement of digital technology has accelerated the growth of Mobile Assisted Language Learning (MALL), with Duolingo as one of the most popular gamified language-learning applications. This study analyzes the visual semiotics of gamification elements in the Duolingo German interface (versions 2022–2025). A descriptive qualitative approach with a case study design is employed. Data consist of screenshots of gamification elements (XP, streak, badges, leaderboard, mascot, and feedback animations) and related literature, analyzed using Roland Barthes’ semiotics, the Shannon and Weaver communication model, and Self Determination Theory within a sociocultural framework. The findings show that visual gamification elements construct the myth of an ideal learner who is always productive, consistent, and competitive. These elements have a dual motivational effect: they can both strengthen and undermine the needs for competence, autonomy, and relatedness, depending on users’ cultural context and meaning-making. The study enriches visual semiotics and gamified language learning research and offers UI/UX recommendations for developers and educators to design more humanistic and meaningful learning experiences. Abstrak Kemajuan teknologi digital telah mempercepat pertumbuhan Pembelajaran Bahasa Berbantuan Seluler (Mobile Assisted Language Learning/MALL), dengan Duolingo sebagai salah satu aplikasi pembelajaran bahasa berbasis gamifikasi yang paling populer. Studi ini menganalisis semiotika visual elemen gamifikasi dalam antarmuka Duolingo Jerman (versi 2022–2025). Pendekatan kualitatif deskriptif dengan desain studi kasus digunakan. Data terdiri dari tangkapan layar elemen gamifikasi (XP, streak, lencana, papan peringkat, maskot, dan animasi umpan balik) dan literatur terkait, yang dianalisis menggunakan semiotika Roland Barthes, model komunikasi Shannon dan Weaver, dan Teori Penentuan Diri dalam kerangka sosiokultural. Temuan menunjukkan bahwa elemen gamifikasi visual membangun mitos tentang pembelajar ideal yang selalu produktif, konsisten, dan kompetitif. Elemen-elemen ini memiliki efek motivasi ganda: mereka dapat memperkuat dan melemahkan kebutuhan akan kompetensi, otonomi, dan keterkaitan, tergantung pada konteks budaya dan pemahaman makna pengguna. Studi ini memperkaya semiotika visual dan penelitian pembelajaran bahasa yang digamifikasi, serta menawarkan rekomendasi UI/UX bagi pengembang dan pendidik untuk merancang pengalaman belajar yang lebih humanistik dan bermakna.
Comparative Analysis of Serverless Container Service Performance Between Google Cloud Run and AWS App Runner in Cross-Cloud Architecture Muhammad Adithya Pratama; Odi Nurdiawan; Arif Rinaldi Dikananda; Denni Pratama; Dian Ade Kurnia
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1919

Abstract

Research on the performance of serverless container services is becoming increasingly important as the need for modern distributed and cross-cloud architectures grows. This study analyzes the performance of two leading serverless services, Google Cloud Run and AWS App Runner, in a cross-cloud architecture scenario. Testing was conducted using identical parameters, including container configuration, region, memory, vCPU, and concurrency. Performance testing included p95 latency, throughput, and error rate metrics using loads of up to 1000 virtual users. The results showed that Google Cloud Run provided more stable performance with p95 latency of 47–71 ms, throughput of 436–438 RPS, and 0% error rate. In contrast, AWS App Runner showed p95 latency of 490–651 ms with throughput variation of 388–410 RPS and an error rate of 2–4.41%. The difference in performance was due to autoscaling mechanisms, cross-cloud communication overhead, and resource contention. This study provides empirical evidence for selecting the optimal serverless service for distributed architectures.
Co-Authors Ade Irma Purnamasari Ade Rizki Rinaldi Afifah, Azah agus bahtiar Ahmad Bahrum Maula Rahman Ananda Rafly Aria Pratama Arif Nur Hakim Arif Rinaldi Dikananda Budi Saputra Chaerudin, Chaerudin Cindyk Irawanto Dadang Sudrajat Denni Pratama Dian Ade Kurnia Dicky Miftakhul Rizki Dwi Teguh Afandi Dyana Fitri Ega Salsa Nugraha Eka Wisnu Ramadhona Fadhil M Basysyar Fadhil M.Basysyar Fidya Arie Pratama Gifthera Dwilestari Iman Nurrohmat Irfan Ali Irvan Himawan Jayawarsa, A.A. Ketut Liyanda Pangestu Melawati Melawati Muhamad Sulaeman Muhammad Adithya Pratama Mulyawan Mulyawan nur syarief abdullah Rini Astuti Ruli Herdiana Saeful Anwar Shofian Yunus Siti Aisyah Syafi'i Syafi'i Syarif Hidayat, Deden Teguh Abdi Mangun Tio Prasetiya Tio Prasetya