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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Sistem informasi dan informatika (SIMIKA) Best Journal (Biology Education, Sains and Technology) International Journal of Global Operations Research DECODE: Jurnal Pendidikan Teknologi Informasi Journal of Informatics and Communication Technology (JICT) Journal of Informatics and Communication Technology (JICT) Engineering: Journal of Mechatronics and Education
Maulana, Muhamad Riyan
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Transportation Other

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GOJEK DATA ANALYSIS THROUGH TEXT MINING USING SUPPORT VECTOR MACHINE (SVM) AND K-NEAREST NEIGHBOR (KNN) Hasanah, Siti Hadijah; Maulana, Muhamad Riyan; Nurdiana, Dian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp889-902

Abstract

The main focus of this research is to apply and test the effectiveness of SVM and KNN methods in Gojek data text analysis. This research will examine how the two methods can classify user comments and feedback and identify data sentiment analysis at the same time practically help Gojek understand user needs and improve service quality. The data obtained through scrapping is categorized into positive and negative sentiment. Data is taken from Gojek application user reviews throughout the year 2022 with a total of 1148 sentiment data with a percentage of 80% training data and 20% testing data. Evaluation of model performance using Confusion Matrix and AUC-ROC Curve shows that SVM is more effective than KNN, with accuracy on training data of 92.55% for SVM and 81.71% for KNN, as well as accuracy on testing data of 82.40% for SVM and 77,09% for KNN.
Generative artificial intelligence as an evaluator and feedback tool in distance learning: a case study on law implementation Nurdiana, Dian; Maulana, Muhamad Riyan; Hasanah, Siti Hadijah; Chairunnisa, Madiha Dzakiyyah; Komuna, Avelyn Pingkan; Rif'an, Muhammad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp2490-2505

Abstract

The development of generative artificial intelligence (GAI) has impacted various fields, including higher education. This research examines the use of GAI as an evaluator and feedback provider in distance legal education. This study tested five GAI models: ChatGPT, Perplexity, Gemini, Bing, and You, using a sample of 20 students and evaluations from legal experts. Descriptive statistical analysis and non-parametric tests, including Wilcoxon, intraclass correlation coefficient (ICC), Kappa, and Kendall's W, were used to assess accuracy, feedback quality, and usability. The results showed that ChatGPT was the most effective GAI, with the highest mean scores of 4.22 from experts and 4.12 from students, followed by Gemini with scores of 4.15 and 4.07. In terms of binary judgement accuracy, Gemini scored 80%, ChatGPT 60%, while Perplexity, Bing, and You had lower scores. Statistical analysis showed moderate agreement (ICC=0.439) and low alignment (Kappa=-0.058) between the GAIs and expert evaluations, with a Kendall's W value of 0.576 indicating moderate consistency in judgements. These findings emphasize the importance of selecting effective GAIs such as ChatGPT and Gemini to improve academic evaluation and learning in legal education, and pave the way for further innovations in the use of AI.
Development of E-learning Based Mechatronics Learning Module for Distance Education Maulana, Muhamad Riyan
Engineering: Journal of Mechatronics and Education Vol. 1 No. 2 (2024): Engineering: Journal of Mechatronics and Education
Publisher : Yayasan Insan Mulia Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59923/mechatronics.v1i2.181

Abstract

In the growing context of distance education, e-learning modules for mechatronics offer great potential to increase learning flexibility and effectiveness, but face challenges related to concept understanding, student motivation, and technical constraints. This study aims to evaluate the effectiveness of mechatronics-based e-learning modules in improving students' understanding of mechatronics concepts and to identify challenges and areas of improvement needed. Using a qualitative approach, the study involved in-depth interviews with 20 students over a four-month period as well as focus group discussions and document analysis. The data obtained was analysed thematically to reveal students' views and experiences. The findings show that e-learning modules that integrate multimedia elements such as animations and interactive simulations significantly improve students' understanding and motivate them through interactive elements. However, technical constraints such as unstable internet connection and device compatibility issues, as well as the need for additional support in self-directed learning, hindered the learning experience. Student feedback indicated the need for improvements to the module navigation and user guide. In conclusion, the e-learning module was effective in improving student understanding and motivation, but requires technical improvements and additional support to optimise its benefits in distance education.
Design of Web-Based Attendance Application Information System at SDN Walantaka 3 Karpan, Ibnu; Maulana, Muhamad Riyan
Engineering: Journal of Mechatronics and Education Vol. 1 No. 2 (2024): Engineering: Journal of Mechatronics and Education
Publisher : Yayasan Insan Mulia Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59923/mechatronics.v1i2.224

Abstract

Advances in information technology have resulted in significant transformations in various sectors, including in improving the efficiency and accuracy of data management in educational institutions. SDN Walantaka 3 still uses a manual attendance system, which often faces efficiency and accuracy problems in managing teacher attendance. This research aims to develop a web-based attendance application to overcome the limitations of the manual system and facilitate the management of attendance data. The method used in this research uses the waterfall software development model. The indicators used include the development process, system validation, application feasibility, and evaluation of its effectiveness. The developed system includes various features, including a login page, an intuitive dashboard, teacher master data, and an integrated attendance module. Testing of the application showed positive results, with the system successfully improving efficiency, accuracy, and minimising the potential for human error in recording attendance. The app also provides real-time access to attendance data, allowing the school to conduct better and more structured monitoring and reporting. Overall, the implementation of this application improves the effectiveness of attendance management at SDN Walantaka 3 and provides a sustainable solution for school administration needs.
Uji Usability dan User Experience Website Sistem Informasi Akademik Universitas Terbuka (SIA UT) Berdasarkan Perspektif Mahasiswa Menggunakan Metode USE Questionnaire dan Cognitive Walkthrough Maulana, Muhamad Riyan; Utama, Moh. Rizky Putra Aji; Nurdiana, Dian
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 4 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Efektivitas dan efisiensi website Sistem Informasi Akademik Universitas Terbuka (SIA UT) dalam mempermudah komunikasi dan penyampaian informasi antara universitas dan mahasiswa menjadi sangat krusial untuk dibahas mengingat fakta bahwa mahasiswa UT tersebar di seluruh Indonesia dan mengikuti pembelajaran jarak jauh. Tujuan dari penelitian ini adalah melakukan pengujian yang terukur untuk mengetahui tingkat usabilitas dan pengalaman pengguna serta memperoleh rekomendasi perbaikan bagi sistem apabila ditinjau dari pandangan mahasiswa UT. Metode penelitian yang digunakan untuk mengukur Usability menggunakan USE Questionnnaire dengan parameter pengukuran Usefulnesss, Ease of Use, Ease of Learning, dan Satisfaction. Sedangan metode yang digunakan untuk mengukur User Experience menggunakan Cognitive Walkthrough  (CW) yaitu metode yang digunakan untuk menganalisis User Experience dengan model kognitif. Pengujian Usability menggunakan Google Form yang dibagikan kepada 50 mahasiswa dari berbagai jurusan dan UPBJJ-UT. Sedangkan pengujian User Experience dilakukan dengan skenario tugas secara langsung di UPBJJ-UT Serang dan Semarang kepada 10 mahasiswa. Hasil penelitian ini menunjukkan bahwa nilai rata-rata kumulatif (mean) dari faktor Usefulnesss sebesar 4,35 yang dikategorikan ke dalam rentang penilaian “Baik”. Sementara nilai mean faktor Ease of Use adalah 4,07 masuk dalam rentang “Baik”. Indikator penilaian Satisfaction memperoleh skor mean sebesar 4,11 yang juga masuk dalam rentang kategori “Baik”. Pengujian usabilitas menggunakan metode CW memberikan rekomendasi perbaikan yang dapat menjadi dasar bagi UT untuk terus memperbaiki dan mengembangkan website SIA UT agar lebih memenuhi kebutuhan dan ekspektasi mahasiswa, terutama yang mengikuti sistem belajar jarak jauh.
Co-Authors Amastini, Fitria Aprijani, Dwi Astuti Chairunnisa, Madiha Dzakiyyah Hasanah, Siti Hadijah Heny Kurniawati Karpan, Ibnu Komuna, Avelyn Pingkan Nurdiana, Dian Ridwan, Muhammad Yovie Rif'an, Muhammad Risnawati, Imbuk Saputro, Fajar Agus Utama, Moh. Rizky Putra Aji