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All Journal Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Jurnal Ilmiah Universitas Batanghari Jambi INTECOMS: Journal of Information Technology and Computer Science Jurnal Sistem Cerdas Jurnal Sistem Informasi Kaputama (JSIK) Jurnal Teknik Informatika (JUTIF) Journal of Informatics, Electrical and Electronics Engineering Indonesian Journal of Dedication and Educations The Indonesian Journal of Computer Science INOVTEK Polbeng - Seri Informatika
M. Afdal
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Journal : INOVTEK Polbeng - Seri Informatika

 1 
Analysis of User Satisfaction of SAINS Pahlawan Tuanku Tambusai University Using the EUCS Method Raihan Alfarisy; Idria Maita; Tengku Khairil Ahsyar; M. Afdal
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/n7ene473

Abstract

  Abstract - Smart Academic Integrated System (SAINS) is an information system used to improve the quality and facilitate students, lecturers and staff in carrying out lecture activities at Universitas Pahlawan Tuanku Tambusai. Nevertheless, certain challenges persist, as revealed through interviews and observations with the Head of Student Affairs and Active Students. These include insufficient details regarding the KRS filling schedule and lecture information (content), an unappealing SAINS appearance (format), an inaccessible forgotten password menu (case of use), and a lengthy login process (timeliness). In order to gauge how happy SCIENCE users are with the system, this study used the End User Computing Satisfaction (EUCS) approach and polled 97 people. The results showed that three variables had a positive effect, namely accuracy, format and ease of use, and two variables had a negative effect, namely content and timeliness. The variables that have a positive influence have T-statistic values ​​of 2.804, 2.414, and 3.528, while the variables that have a negative influence have T-Statistic values ​​of 0.576, and 0.326. Research recommendations can add information about the KRS filling schedule and lectures on the SAINS system homepage, as well as increase the speed of access to the SAINS system by users.
Sentiment Analysis of Gojek, Grab, Maxim Applications Using Support Vector Machine Algorithm Iqrom, Muhammad; M. Afdal; Rice Novita; Medyantiwi Rahmawita; Tengku Khairil Ahsyar
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/52fycr56

Abstract

This research analyzes user sentiment towards three major online transportation applications in Indonesia—Gojek, Grab, and Maxim using the \SVM algorithm. The analysis results indicate that Maxim has the highest positive sentiment rate (42.45%) compared to Grab (32.83%) and Gojek (20.21%). Maxim's advantages lie in its competitive pricing and driver professionalism. However, Gojek recorded the best performance in sentiment classification with an accuracy of 94%, followed by Maxim (90%) and Grab (87%). The evaluation based on five main variables (general sentiment, drivers, services, applications, and pricing/costs) reveals the strengths of each application in different categories. Maxim excels in general sentiment and driver satisfaction, Grab dominates in pricing/cost, and Gojek stands out in the application category. Wordcloud visualization reveals frequently mentioned words such as "driver," "application," and "order," reflecting users' primary concerns and experiences. This research provides valuable insights for online transportation service providers to improve service quality, although it has limitations in exploring external factors such as user demographics and marketing strategies, as well as relying on a single algorithm without comparison. The choice of the SVM algorithm is based on its ability to handle well-structured data and provide high accuracy in classification. SVM is effective in finding the optimal hyperplane that clearly separates data classes, making it suitable for sentiment analysis involving multiple variables.
Co-Authors Anggi Widya Atma Nugraha Annisa Nadaa Shabrina Aprilian, Rahil Imainul Arifin, Abdullah Azani, Nilam Wahdiaz Dhiya U Syamsi Jamali Fachroerrozi Hoesni, Fachroerrozi Febi Nur Salisah Febi Yanto Fitriani Muttakin Ichsan Ahmad Gunawan Idria Maita Inggih Permana Inggih Permana Iqrom, Muhammad Jahtera Manalu Julia Julia Medyantiwi Rahmawita Muhammad Irsyad Muhammad Jazman Mustakim Nabiilah, Nabiilah Raihan Alfarisy Rice Novita Rice Novita Rice Novita Sepri, Domi Siti Monalisa SUMIYATI SUMIYATI Suryadi Suryadi Syahrul Hijaji Tengku Khairil Ahsyar Tsulis Amirudin Zahri Windy Amelia Putri Zarnelly