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All Journal Informatika Jurnal Ipteks Terapan : research of applied science and education
Putri Sakinah
Informatika, Universitas Adzkia
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CHATBOT IMPLEMENTATION TO SUPPORT MOBILE LEARNING DURING NCOVID19 PANDEMIC Putri Sakinah; Yaya Heryadi
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 14 No. 3 (2020): Re Publish Issue
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (296.874 KB) | DOI: 10.22216/jit.v14i3.102

Abstract

This paper presents the results of chatbot implementation to support mobile learning in higher education. Thegoal of the chatbot implementation in this study, among others, is to address high interest of higher educationin Indonesia toward online learning support mainly during the resent NCOVID19 pandemic in which most oflearning process are implemented using online learning mode. The proposed chatbot prototype has been testedin the University of Andalas, Sumatera, Indonesia. The chatbot is designed using standard softwareengineering method and implemented using Android-based mobile application flatform. Respondents for thechatbot evaluation are chosen based on purposive random sampling among students of Department ofSociology as sampling population. The data collecting is implemented using survey method with selfadministered questionnaires. The overall evaluation results showed that the designed and implementation hasmet the students’ expectation. Interestingly most of the respondents showed their interest to use the chatbot
CHATBOT IMPLEMENTATION TO SUPPORT MOBILE LEARNING DURING NCOVID19 PANDEMIC Putri Sakinah; Yaya Heryadi
Jurnal Ipteks Terapan Vol. 14 No. 3 (2020): Re Publish Issue
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (296.874 KB) | DOI: 10.22216/jit.v14i3.102

Abstract

This paper presents the results of chatbot implementation to support mobile learning in higher education. Thegoal of the chatbot implementation in this study, among others, is to address high interest of higher educationin Indonesia toward online learning support mainly during the resent NCOVID19 pandemic in which most oflearning process are implemented using online learning mode. The proposed chatbot prototype has been testedin the University of Andalas, Sumatera, Indonesia. The chatbot is designed using standard softwareengineering method and implemented using Android-based mobile application flatform. Respondents for thechatbot evaluation are chosen based on purposive random sampling among students of Department ofSociology as sampling population. The data collecting is implemented using survey method with selfadministered questionnaires. The overall evaluation results showed that the designed and implementation hasmet the students’ expectation. Interestingly most of the respondents showed their interest to use the chatbot
Integrasi Model Pembelajaran Mesin dalam Game Menggunakan Gerakan Tangan Yomei Hendra; Putri Sakinah; Fajar Maulana; Kiki Hariani Manurung
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6826

Abstract

This study develops a Tetris game controlled through hand gestures using a machine learning model. The primary objective of this research is to create an interactive and responsive gaming experience by utilizing hand gesture detection as the main control mechanism. A hand gesture dataset was collected from videos segmented into individual frames, which were then analyzed using MediaPipe to detect and label gestures. The machine learning model employs a Convolutional Neural Network (CNN) trained to recognize hand gesture patterns and translate them into commands within the game. After implementation, an evaluation was conducted by distributing questionnaires to 18 Informatics students at Adzkia University to assess the system's comfort and responsiveness. The questionnaire results showed a high satisfaction level, with an average score of 84.56, covering evaluations of control ease, gesture detection accuracy, and system responsiveness. The average score for ease of use reached 85, indicating that the majority of users found the gesture-based controls comfortable. This study demonstrates that applying machine learning models in gesture-based control games can provide a more interactive and responsive experience, with potential applications in other interactive technologies.
Co-Authors Fajar Maulana Hendra, Yomei Kiki Hariani Manurung Yaya Heryadi