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All Journal Jurnal Teknologi dan Manajemen Informatika POROS TEKNIK Antivirus : Jurnal Ilmiah Teknik Informatika Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Advanced in Information and Industrial Technology (JAIIT) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) JAREE (Journal on Advanced Research in Electrical Engineering) J-Intech (Journal of Information and Technology) PELS (Procedia of Engineering and Life Science) Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Innovative: Journal Of Social Science Research Science Contribution to Society Journal JOSAR (Journal of Students Academic Research) Jurnal Informatika Polinema (JIP)
Yuana, Haris
Universitas Islam Balitar
Religion Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Design of a Website-Based Goods Inventory Information System at the Grocery Store Aldo Nicholas; Haris Yuana; Rahmat, Mohammad Faried
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.632

Abstract

This research aims to design and build a website-based inventory information system at the Dewi Grocery Store. The problem currently faced by stores is that capturing and managing inventory data is still manual, causing problems such as difficulty monitoring stock, recording errors and making old reports. The research method used is Agile Methods, consisting of requirements, design, implementation, verification and maintenance. System design using Laravel, Visual Studio Code, MySQL, XAMPP, Draw.io, and Whimsical. The research result is a website-based inventory information system application that can help the Dewi Grocery Store manage inventory data effectively and efficiently. The sales inventory system is functional and user-friendly, making it a valuable tool for Dewi Grocery Store to effectively manage sales inventory and provide accurate reports. The application has category management features, item data, sales, and report creation, as well as prediction features to help shop owners make decisions. The results of black box, expert, and user testing show the application is worthy of use with scores of 94%, 76%, and 83 %, respectively.
Sentiment Analysis On Evos Esports Team Instagram Social Media Using Convolutional Neural Network (CNN) Zen, Mohammad Amir Fatkhi; Yuana, Haris; Mawaddah, Udkhiati
JOSAR (Journal of Students Academic Research) Vol 10 No 2 (2025): September
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/4xw3mn98

Abstract

The rapid growth of the esports industry in Indonesia presents unique challenges for professional teams such as EVOS Esports, particularly in strengthening fan engagement and loyalty in the digital era. This study aims to analyze fan sentiment toward the official Instagram posts of EVOS Esports using a deep learning approach with a Convolutional Neural Network (CNN). The research process involved data collection through web scraping, followed by preprocessing stages such as cleaning, case transformation, normalization, tokenization, stopword removal, and stemming. The dataset was then labeled, split into training and testing sets (90:10), and used for CNN model training and evaluation through a confusion matrix. The results demonstrate that the CNN model successfully classified comments into three sentiment categories—positive, negative, and neutral—with an accuracy of 92%. The model also achieved a precision of 0.92, recall of 0.92, and an F1-score of 0.92, indicating very good classification performance. Sentiment distribution analysis of 11,305 comments showed that neutral sentiment dominated (47.24%), followed by positive (30.12%) and negative (22.64%). These findings provide valuable insights into fan perceptions of esports team performance on social media. For future research, expanding the sentiment lexicon with terms commonly used in online communities is recommended to further enhance classification accuracy.
Co-Authors Adfiansyah, Farkhan Adhiyasa Khoirul Muttaqiin Afandi, Kautsar Aldo Nicholas Alwan Fauzaan Anugerah Utama, Jaka Ari Bintari, Dinny Asromah Al Alawiyah Awwalin, Beta Nurul Bayu Lokananta, Ricko Chulkamdi , M. Taofik Chulkamdi, Mukh Taofik Dimas Fanny Hebrasianto Permadi Dwi Fasnuari, Happy Andrian Dwi Puspitasari, Wahyu Eka Febri Anggara, Wahyu Eko Saputro, Wahyu Fani Putra, Nicky Febrinita, Filda Hartami Santi, Indyah Herliztyo, Deva Khasani, Abil Kholila, Ni'ma Kirom, Sabitul Kuncoro Timur, Bimo Kurnia Paranita Kartika Kurnia Paranita Kartika Riyanti Lestanti, Sri M. Taofik Chulkamdi, M. Taofik M.Taufiq Sauma Hendy Mawaddah, Udkhiati Mukh Taofik Chulkamdi Muttaqiin, Adhiyasa Khoirul Nizam, Muhammad Nizam Nur Budiman, Saiful Nur Hidayat Nur, Akbar Nurul Fitrah Rahmat, Mohammad Faried Rizaldy Gunawan Rochim, Bahrur Saiful Nur Budiman Saiful Nur Budiman Sholikhatul Kasanah, Eka Subeqi, Muhammad Surachmad, Bayu Taofik Chulkamdi, Mukh Udkhiati Mawaddah Ulya, Ulya Darotin Wahyu Dwi Puspitasari wahyu woro lestari Wicaksono, Eko Teguh Widya Andhika, Fibri Wulansari, Zunita Yusuf Pramono Yuswandari Zain Zakaria, Robby Zen, Mohammad Amir Fatkhi Zukhomsin, Devid Zunita Wulansari Zunita Wulansari