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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Informatika Kaputama (JIK) Jurnal Informasi dan Teknologi Vocatech : Vocational Education and Technology Journal JTIK (Jurnal Teknik Informatika Kaputama) JOURNAL OF INFORMATICS AND COMPUTER SCIENCE G-Tech : Jurnal Teknologi Terapan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Pengabdian kepada Masyarakat Nusantara JINAV: Journal of Information and Visualization International Journal of Engineering, Science and Information Technology MALLOMO: Journal of Community Service Journal of Renewable Energy, Electrical, and Computer Engineering Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Pengabdian Masyarakat Bangsa MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Informatika: Jurnal Pengembangan IT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS)
Yesy Afrillia
Universitas Malikussaleh
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Machine Learning Algorithms Comparison for Gender Identification Aldo januansyah. H; Muhammad Fikry; Yesy Afrillia
Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Vol. 4 (2024): Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MI
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/micoms.v4i.885

Abstract

Abstract. In this study, we presents a comprehensive analysis of gender identification methods utilising eight distinct classification models: K-Nearest Neighbors (KNN), Naive Bayes, Decision Tree, Random Forest, Logistic Regression, XGBoost, Support Vector Machine (SVM), and Neural Network. Gender identification is a critical task with significant applications in marketing, social analysis, and security systems, necessitating the exploration of various methodologies to achieve optimal performance. The dataset employed in this research underwent normalisation using the Min-Max scaling technique, which enhances the performance of classification models by ensuring that all features contribute equally, particularly when the data exhibits varying ranges of values. The results reveal that the K-Nearest Neighbors (KNN) model significantly outperformed the other models, achieving an impressive accuracy of 0.9758 with a support of 951, underscoring the effectiveness of the KNN algorithm in gender identification tasks and establishing it as a reliable choice for applications requiring high accuracy. Furthermore, the study emphasises the critical importance of selecting appropriate models in machine learning tasks and the substantial impact of data normalisation on model performance. Overall, this research provides valuable insights into the KNN algorithm, demonstrating its ease of implementation and exceptional effectiveness in achieving high precision in gender identification tasks, with implications for future research and practical applications across various fields. Keywords : classification models; data normalisation; gender identification; K-Nearest Neighbours; machine learning.
Quality Analysis of Web-Based Visitor Management System (DATENG) Using Cypress Testing and Task-Based Usability Testing Methods Based on ISO 9241-11 (Case Study of PT Perta Arun Gas) Rizky Putra Fhonna; Yesy Afrillia; Ilham Sahputra; Sayed Fachrurrazi; Faiz Fadhilla
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.27052

Abstract

Manual management of visitor data in the company environment has the potential to cause various problems, such as time inefficiency, the risk of data loss, and the occurrence of physical queues during certain operational hours. These conditions can hinder the smooth running of operational activities and reduce the quality of service to guests. Therefore, a web-based visitor management system called DATENG was developed which aims to support the process of recording, scheduling, and verifying visits in an integrated and structured manner. This research activity focuses on testing and evaluating the quality of the DATENG system to ensure that the system can function properly and is easy to use by users. The method used consists of two main approaches, namely functionality testing and usability evaluation. Functionality testing is carried out using the Cypress Testing method with an end-to-end testing approach to verify that all system features are running according to the needs that have been set. Furthermore, usability evaluation is carried out using a task-based testing method based on the ISO 9241-11 standard, which includes measuring aspects of effectiveness, efficiency, and satisfaction. The test results show that all the key features of the DATENG system can function properly without significant functional errors being found. Usability evaluations show that users are able to complete each task with a high success rate, relatively efficient turnaround time, and a good level of user satisfaction. Based on these results, it can be concluded that the DATENG system has good system quality and is able to support the visitor management process effectively, efficiently, and provide a positive user experience in accordance with the company's operational context.
Co-Authors Abadi, Sabani Abdul Hadi Abil Khairi Adek, Rizal Tjut Aldo januansyah. H Ananda Faridhatul Ulva Andreansyah, Sabda Annas, Muhammad Aqmal, Jamalul Arif, Abdul Halim Arif, M. Arif Saputra Arifa, Cut Hilma Asmi, Nurul Annisa Asrianda Asrianda Asrifan, Andi Aswandi, Sakti Ayu Indah Lestari Berutu, Indah Fachlira Bustami Bustami Dahlan Abdullah Dasril Dasril David Sarana Deassy Siska Dewi, Tursina Dika, Farhan Dinanti, Intan Putri EDI YUSUF, EDI eva darnila, eva darnila Fadlisyah Fadlisyah Fadlisyah Faiz Fadhilla Fajar, Kasihan Muhammad Fakhruddin Ahmad Nasution Fatika, Dian Fidyati, Fidyati Fikria, Putri Fuadi, Wahyu Hafidh Rafif, Teuku Muhammad Harahap, Ilham Taruna Herman Fithra Hidayat, Amam Taufiq ilham - sahputra Ilsa Hidayat Jamalul Aqmal Julianansa, Ririn Kautsar, Al Khairuni Khairuni Lidya Rosnita Mahesa Reglisalo Maida, Eka Muhammad Fikry Muhammad Muhammad Muhammad Yusuf Mukhlis Mukhlis Mukti Qamal Munirul Ula Muzaffar Rigayatsyah Muzaffar Rigayatsyah NELI SUSANTI, NELI Nurdin Nurdin Nurqamarina Rahma, Mutiara Rahmawati, Rahmawati Rini Meiyanti Risawandi, Risawandi Riza, Saiful Rizal Rizal Rizal S.Si., M.IT, Rizal Rizky Putra Fhonna Rozzi Kesuma Dinata Safriand, Safriand Sayed Fachrurrazi Selian, Riko Ardiansyah Siregar, Winda Ramadhani Sofyan Sofyan Suci Ramadani Sujacka Retno Teuku M. Arief Afwan Uliana, Lisa Ulva Ilyatin Veri Ilhadi Wahyu Fuadi Wahyu Fuadi Wardana, Ade Bagus Widari, Liz Ayu Yanti, Winda Zara Yunizar Zuhra, Elviza Zulfan