Arif Marsal
Universitas Islam Negeri Sultan Syarif Kasim Riau

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Implementation of the internet of things on smart posters using near field communication technology in the tourism sector Muhammad Luthfi Hamzah; Astri Ayu Purwati; Sutoyo Sutoyo; Arif Marsal; Sarbani Sarbani; Nazaruddin Nazaruddin
Computer Science and Information Technologies Vol 3, No 3: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v3i3.p194-202

Abstract

Tourism promotion in Pekanbaru is one step in increasing the number of tourists visiting Pekanbaru City. Through tourism promotion, tourists will find out where the locations are in Pekanbaru and information related to these tourist objects. This research aims to design a tourism promotion system using near-field communication (NFC) smart posters using smartphones in the city of Pekanbaru and apply NFC technology to Android smartphones in the city of Pekanbaru. Promote tourism in the city of Pekanbaru. They were testing this application with the System Usability Score, which had a good score of 74.30. This study shows that the planning and modeling of the smart poster system using NFC technology makes it easier to identify important information for every tourism activity in Pekanbaru. The results of this study are the design and product of an intelligent poster using NFC on an Android smartphone that can help users achieve information so that it is more effective and efficient.
USABILITY EVALUATION ON THE NEW STUDENT ADMISSIONS SYSTEM USING THE HEURISTIC EVALUATION METHOD nurhaliza azzini; Idria Maita; Tengku Khairil Ahsyar; Fitriani Muttakin; Siti Monalisa; Arif Marsal
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 2 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i2.4099

Abstract

The Dumai College of Technology (STT) has implemented a New Student Admission System for prospective students to register online. Based on the results of interviews with the SPMB manager, during its implementation there has never been a usability evaluation. So that the SPMB manager does not know what user needs or problems experienced by system users are. Therefore, researchers conducted usability research. The purpose of this study is to measure the success rate of the New Student Admission System by using the Heuristic Evaluation method so that it can provide recommendations to the manager of the New Student Admission System for future system improvements to meet user needs. The results of the research questionnaire there are 93 data respondents who use SPMB. Based on the results of the usability evaluation on the STT Dumai New Student Admission System, it was found that the total percentage of respondents was found to be 65.2% which can be said that the SPMB STT Dumai was "Good", while the results of the total percentage of respondents were not found, namely 34.8% which can be said to be "Not Good" for the SPMB STT Dumai. ” for system users. From the usability results found 4 statements that get the lowest percentage value which means it is not successful and needs to be improved. The results of the recommendations obtained in the SPMB can be used as an illustration for improvement.
Pendekatan Machine Learning: Analisis Sentimen Masyarakat Terhadap Kendaraan Listrik Pada Sosial Media X Gathot Hanyokro Kusuma; Inggih Permana; Febi Nur Salisah; M. Afdal; Muhammad Jazman; Arif Marsal
JUSIFO : Jurnal Sistem Informasi Vol 9 No 2 (2023): JUSIFO (Jurnal Sistem Informasi) | December 2023
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v9i2.21354

Abstract

Environmental issues and the depletion of fossil fuels continue to escalate as the number of fossil fuel-based vehicle users increases in Indonesia. Electric vehicles emerge as one of the potential alternative solutions to address current environmental challenges, given their eco-friendly nature and lack of pollution emissions. Sentiment analysis is conducted to understand public responses, both supportive and opposing, towards electric vehicles. This research aims to analyze the sentiment of X-social media users regarding electric vehicles using machine learning techniques. The research stages include data collection, data selection, preprocessing, and classification using Naïve Bayes Classifier (NBC), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) algorithms. The test results show that on a balanced dataset using ROS, SVM performs the best with accuracy = 68.7%, precision = 77.9%, and recall = 68.4%. Meanwhile, NBC yields an accuracy of 60.3%, precision of 61.3%, and recall of 60.3%, while KNN has an accuracy of 53.9%, precision of 54%, and recall of 53.9%.