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All Journal CogITo Smart Journal Servitium Smart Journal
Semmy Wellem Taju
Universitas Klabat
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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Journal : CogITo Smart Journal

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Bahasa Indonesia Bahasa Inggris Elshadai Gracia Carolina Rampengan Rampengan; Semmy Wellem Taju; Venisa Tewu
CogITo Smart Journal Vol. 9 No. 1 (2023): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v9i1.469.181-192

Abstract

Klabat University provides residential facilities for students, better known as a dormitory. Information services regarding dormitories and reservation rooms at Klabat University are still managed manually between the dormitory and students. Some problems occur when students want to find information and/or reserve a room at the same time. From the problems that have been observed, researchers have designed a Chatbot to facilitate the students to find for information as well as reserve dormitory rooms. The development method used in this research is the prototyping model. To design a chatbot by implementing two-way communication, researchers implemented Natural Language Processing technique with a Machine Learning approach. The result of this research is a new Chatbot widget as a virtual assistant for information services and reservation rooms in the dormitory at Klabat University
Implementing QR code and Geolocation Technologies for the Student Attendance System Semmy Wellem Taju; Yonatan Putra Mamahit; Jeremy Andrew Pongantung
CogITo Smart Journal Vol. 10 No. 1 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i1.636.642-653

Abstract

Attendance is one of the important factors in supporting lecture activities that can be used to see how well the performance of student attendance in class. Traditional attendance systems used in various educational institutions often cause problems. This research aims to develop an innovative and efficient student attendance system to help the process of taking attendance by utilizing QR-Code and geo-location technologies at Klabat University. The research method employed for this development is the Prototyping Model, which involves iterative development and refinement processes. The system is designed as a web-based application and a mobile application, developed using PHP as the programming language, MySQL as the database management system, Bootstrap 5 as the CSS and JavaScript framework for creating responsive websites, Apache as the web server and Ubuntu 22.04 as the operating system for the server. QR-Code technology is proposed as a medium for recording and verifying student attendance, while Geo-Location technology is used to verify the presence of students in the right lecture venue. The results of this research are expected to make a positive contribution to Klabat University in terms of recording student attendance.
Research Project Topic Recommender System Using Generative Language Model Debby Erce Sondakh, S.Kom, M.T, Ph.D; Semmy Wellem Taju; Jian Kezia Tesalonica Yuune; Anjelita Ferensca Kaminang; Syalom Gabriela Wagey
CogITo Smart Journal Vol. 10 No. 1 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i1.678.654-666

Abstract

Education has become a driver of a person's continuous innovation to improve their quality. Currently, the use of artificial intelligence determines progress in education. In this research, artificial intelligence technology was applied to develop a web-based recommendation system to help students at the Faculty of Computer Science, Klabat University, choose appropriate research topics for their final assignments. To provide personalized and contextually relevant suggestions, the recommendation system leverages deep learning and generative language models, specifically GPT-3. The Rapid Application Development process model is employed to develop the system. Its key components include semantic search, rapid engineering, and an advanced vector database for effective data management and retrieval. The functions provided by the system include user account registration, login, input of major subject grades and research preferences, and personalized recommendation results. Some additional features such as profile management, previous recommendation history, and password reset options are also provided. All these functions have been tested using the black box method.
Co-Authors Anjelita Ferensca Kaminang Elshadai Gracia Carolina Rampengan Rampengan Jeremy Andrew Pongantung Jian Kezia Tesalonica Yuune Marchel Timothy Tombeng Reymon Rotikan Rolly Junius Lontaan Sondakh, Debby Erce Stenly Richard Pungus Syalom Gabriela Wagey Venisa Tewu Yonatan Putra Mamahit