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All Journal Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Journal of Computer Science and Informatics Engineering
Harun, Rusni
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Computer Science & IT Control & Systems Engineering

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Application of Monitoring Handy Talkie Usage as Support For Security Operation Based Android At Polda Gorontalo Harun, Rusni; Manurapon, Reynaldi; D. Paemo, Nuranissa; Ismail, Abdul Rahman
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1183

Abstract

Information Technology is developing rapidly and it has a significant impact on various aspects of life, including the government sector. The process of data collection that used Microsoft Excel software and paper filing have drawbacks such as difficult data collection, data loss due to natural factors, and it was difficulty in determining the condition of HTs. The purpose of this reseacrh was to designed an application of innovative monitoring HTs for security based Android. This application utilizes Android technology and HT devices to improve the effectiveness and coordination of security within the Information and Communication Technology Division of Regional Police in Gorontalo. The methodology of research used was Research and Development (R&D). The application was created using Java programming using Android Studio, PHP, and HTML. It allows Polda personnel to log in, view HT types and stock, borrow and return devices, and upload transaction receipts. The database used was MySQL. The modeling used Unified Modeling Language. This system utilizes whitebox and blackbox testing. As a sample, researchers tested the HT Borrowing flowchart, obtaining a region (R) value of 3, an Independent Path value of 3, and a Cyclometric Complexity (CC) value of 3. Test scenarios, including login, menu, HT type, and history displays, were successful, demonstrating that the system correctly authenticates users, manages HT data accurately, displays complete information, manages returns and validation appropriately, and handles usage securely
Analisis Ulasan E-commerce Menggunakan Fine Grained Sentiment Analysist dan Convolutional Neural Network Harun, Rusni; Razak, Mashur; Jalil, Abdul
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 11 No 2 (2025): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v11i2.3529

Abstract

Beragam ulasan dan komentar dari konsumen Aplikasi e-Commerce seringkali ditinggalkan pada kolom komentar merupakan pengalaman mereka saat mengadakan transaksi jual beli pada platform e-commerce dari yang sangat positif hingga sangat negatif dapat memberikan informasi berharga tentang kepuasan atau ketidakpuasan pelanggan. Ulasan seringkali di tulis dalam bahasa alami yang tidak terstruktur sehingga sulit dianalisis secara manual karena dalam skala besar. Penelitian ini dilakukan untuk menganalisis ulasan pada aplikasi e-commerce platform Bukalapak dan Tokopedia menggunakan metode Fine Grained Sentiment Analysis dan Convolutional Neural Network dengan 1000 dataset yang di scrawling dari google play store menggunakan google colab sebagai toolsnya. Penelitian ini bertujuan untuk memberikan informasi bagi perusahaan dari analisis sentimen yang diperoleh sehingga dapat merespons dengan cepat terhadap umpan balik pelanggan, dan kemudian bisa meningkatkan kualitas layanan, dan mengoptimalkan pengalaman belanja secara online. Penelitian ini menggunakan 5 kelas sentimen yaitu : sangat positif, positif, sangat negatif, negatif dan netral. Dari hasil eksperimen yang telah dilakukan hasil akurasi yang diperoleh dari aplikasi e commerce Tokopedia dengan epoch 10, 20, 40, 60, 80, 100 adalah 62.50 %, 59.26 %, 57.58 %, 48.39%, 51.85%, 65.62%, pada aplikasi Bukalapak adalah 62.50 %, 55.17 %, 62.86 %, 50.00%, 75.00%, 51.72%.
Co-Authors Abdul jalil D. Paemo, Nuranissa Ismail, Abdul Rahman Manurapon, Reynaldi Mashur Razak