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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknologi Informasi dan Ilmu Komputer POSITIF Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sisfokom (Sistem Informasi dan Komputer) METIK JURNAL Vocatech : Vocational Education and Technology Journal JOURNAL OF INFORMATICS AND COMPUTER SCIENCE JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Tika JURNAL ILMIAH GLOBAL EDUCATION Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Minfo Polgan (JMP) TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Terapan and Sains 4.0 Jurnal Bangun Abdimas Variasi : Majalah Ilmiah Universitas Almuslim MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Journal of Advanced Computer Knowledge and Algorithms Journal Serambi Engineering (JSE) Jurnal Elektro dan Teknologi Informasi Bulletin of Engineering Science, Technology and Industry Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Zara Yunizar
Universitas Malikussaleh
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)

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Spammer Detection On Computer Networks Using Gaussian Naïve Bayes Classifier And K-Medoids As Acquisition Training Data OK Muhammad Majid Maulana Majid; Rizal Tjut Adek; Zara Yunizar
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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This research focuses on the implementation of the Gaussian Naïve Bayes algorithm for spammer detection in computer networks, leveraging K-Medoids clustering for training data acquisition. The increasing number of internet users, combined with the challenges of detecting spam activity on a network, has made manual detection ineffective. This study addresses the need for automated spam detection using machine learning algorithms. The Gaussian Naïve Bayes algorithm was chosen for its simplicity and effectiveness in handling continuous data, making it suitable for classifying network traffic as either normal or spammer. To acquire labeled training data, K-Medoids clustering was employed, offering robustness against outliers, which traditional clustering algorithms like K-Means often struggle with. The research involved collecting traffic data from a Mikrotik Routerboard at various intervals, followed by data preprocessing to remove irrelevant or null features. After preprocessing, the data was clustered using K-Medoids into two groups: spammer and normal. The Gaussian Naïve Bayes classifier was then applied to the clustered data, producing a model with high accuracy, precision, recall, and F1-score. Specifically, the model achieved 99.71% accuracy, 100% precision, 99.71% recall, and a 99.85% F1-score, indicating a well-balanced performance in spam detection. The results demonstrate that the Gaussian Naïve Bayes algorithm, combined with K-Medoids clustering, is effective for detecting spammers in computer networks. Future research could explore higher-layer network traffic and broader datasets, utilizing different routers for a more comprehensive evaluation. This approach provides a reliable solution for network administrators seeking to improve network security by detecting and mitigating spam activity.
Implementation of the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) Algorithm for Rice Price Prediction Ezra Sasqia Syahna; Zara Yunizar; Zahratul Fitri
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstrak Studi ini mengimplementasikan model Seasonal Autoregressive Integrated Moving Average with Exogenous variables (SARIMAX) untuk memprediksi harga beras ( gabah ) berdasarkan data historis dari tahun 2020 hingga 2024. Dengan memanfaatkan data yang diperoleh dari Investing.com, penelitian ini mengintegrasikan variabel eksternal utama seperti suhu, harga pupuk, dan tingkat produksi untuk meningkatkan akurasi prediksi. Metodologi ini terdiri dari langkah-langkah sistematis, termasuk pengumpulan data, pemrosesan, dan evaluasi model, dengan menggunakan metrik seperti Mean Squared Error (MSE), Root Mean Squared Error (RMSE), dan Mean Absolute Percentage Error (MAPE) untuk menilai kinerja. Temuan tersebut mengungkapkan korelasi yang kuat antara harga pasar yang diprediksi dan aktual, khususnya dalam kategori harga penutupan, yang mencapai MAPE sebesar 1,354%. Metrik evaluasi selanjutnya mengonfirmasi kekokohan model, dengan harga penutupan menunjukkan MSE terendah sebesar 299.629,64 dan RMSE sebesar 547,38. Meskipun kategori harga tertinggi menunjukkan MAPE yang sedikit lebih tinggi, yaitu 2,007%, semua kategori tetap berada di bawah ambang batas yang dapat diterima, yaitu 2%, yang menunjukkan akurasi prediksi yang memuaskan. Sebagai kesimpulan, model SARIMAX menunjukkan efektivitas yang signifikan dalam peramalan harga beras, yang memberikan wawasan berharga bagi para pemangku kepentingan di pasar pertanian. Implementasi dalam aplikasi web memfasilitasi prediksi secara real-time, yang mendukung pengambilan keputusan yang tepat, dan meningkatkan strategi pasar. Kata kunci : SARIMAX; harga beras; model prediksi; MAPE; pasar pertanian; analisis deret waktu.
Implementation of Horspool Algorithm on Book Search Application in Malikussaleh University Library Based on Mobile Android Gilang Wahyu Ramadhan Gilang; Zara Yunizar; Sujacka Retno
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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The development of information technology encourages innovation in library management systems, one of which is an efficient book search system. This thesis examines the application of the Horspool method in library book search applications to improve search speed and accuracy. The Horspool method is a pattern matching algorithm designed to speed up the text search process by utilizing a sliding table, which significantly reduces the number of comparisons required in pattern search. The developed application allows users to search for books based on title, author, or other keywords with fast and relevant results. An evaluation was conducted by comparing the search time between the Horspool method and the traditional search method. The evaluation results show that the Horspool method offers significant performance improvement, with faster search time and high accuracy.
Development of Portable IoT-Based Fish Pond to Enhance Freshwater Aquaculture Efficiency Rifkial Iqwal; M Ishlah Buana Angkasa; Nazwa Aulia; Subhan Hartanto; Tejas Shinde; Muhammad Fikry; Zara Yunizar
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This paper presents the development of iPooL, a portable Internet of Things (IoT)-based fish pond system designed to optimize freshwater fish farming, particularly in resource-constrained and urban environments. By integrating real-time monitoring of essential water parameters—such as pH, temperature, dissolved oxygen, and ammonia levels—iPooL ensures that optimal environmental conditions are maintained for fish health and growth. The system employs IoT sensors connected to an ESP32 microcontroller, which processes and transmits data to a cloud platform, enabling farmers to receive real-time alerts and manage their ponds via a mobile app. Field trials demonstrated that the iPooL system reduces fish mortality by 20% and improves fish growth rates by maintaining stable water conditions. Additionally, the automation of feeding schedules and water management reduces operational costs, particularly in labor and feed, resulting in a 30% increase in profitability. With an estimated return on investment (ROI) within one year, iPooL offers a cost-effective solution for both small- and medium-scale fish farmers. The system also promotes environmental sustainability by optimizing water usage and reducing the need for chemical additives. Its portability allows fish farming in non-traditional environments, such as urban rooftops, contributing to decentralized food production and reducing the environmental impact of transporting fish to urban markets. iPooL’s scalability, combined with future integration of artificial intelligence and renewable energy sources, positions it as a transformative tool for the aquaculture industry, supporting both economic development and sustainable farming practices.
Co-Authors ,, Iqbal ,, Maulidasari ,, Zulaifani ., Yulisma Agil, Helvina Aidilof, Hafizh Al Kautsar Aidilof, Hafizh Al-Kautsar Aisah, Sri Purwani Amelia, Ulva Aminsyah, Ansharulhaq Arief Fazillah Arif H., Nanda Nan Arnawan Hasibuan Asran Asran Bariah, Hairul Bustami Bustami Cindy Rahayu Dahlan Abdullah Devi, Salma Dhyra Gibran Alinda Dr M Rajeswari Elma Fitria Ananda ERNAWITA ERNAWITA Ersa, Nanda Savira Eva Darnila Ezra Sasqia Syahna Fadlisyah Fadlisyah Fajri, Riyadhul Fajri, Ryadhul Fajriana, Fajriana Fardiansyah, T. Fasdarsyah Fasdarsyah Fatimah Zuhra Fatimah Zuhra Fatimah Zuhra Fuadi, Wahyu Gilang Wahyu Ramadhan Gilang Hafidh Rafif, Teuku Muhammad Harahap, Ilham Taruna Hasan, Phadlin HENDRA ZULKIFLI Irshad Ahmad Reshi Johan, T. M. Kartika Kartika Kurnia Amanda, Destiara Lidya Rosnita M Ishlah Buana Angkasa M. Fauzan M.Cs, Iqbal, Maghfirah Maghfirah Maha, Dedi Torang P Mahara, Sabda Mahendra Febriliansyah Maizuar Maizuar Maryana Maryana, Maryana Maulana Helmi, Fathan Maulana, O.K.Muhammad Majid Melizar Meutia Rahmi Misbahul Jannah Muhammad Daud Muhammad Fikry Muhammad Ikhwani Muhammad Muhammad Muharni Muharni Mukhlis Mukhlis Mukhlis Mulaesyi, Syibbran Munar, Munar Munirul Ula Mursyidah Mursyidah MUTHMAINNAH Muthmainnah Muthmainnah Nazwa Aulia NinaUlfauza NinaUlfauza Nunsina, Nunsina Nur Mauliza Nura Usrina Nurdin Nurdin Nuryawan, Nuryawan OK Muhammad Majid Maulana Majid Putri, Riska Yolanda Ramadhana Juseva Ridha, Ridha Rifkial Iqwal Rini Meiyanti Ritonga, Huan Margana Rizal S.Si., M.IT, Rizal Rizal Tjut Adek Rizki Suwanda Rizky Almunadiansyah Rizky Putra Fhonna Rizky, Rahmat Rizkya, Dini Dara Rozzi Kesuma Dinata Rusnani Rusnani Rusniati Rusniati Ruwaida Ruwaida Safwandi Safwandi Said Fadlan Anshari Savira Ersa, Nanda Siregar, Winda Ramadhani Sriana, Anis Subhan Hartanto Suci Fitriani, Suci Sujacka Retno Syintia, Icut Tarigan, Tasya Amelia Taufiq Taufiq Tejas Shinde Tjut Adek, Rizal Wahyu Fuadi Yanti, Winda Yesy Afrillia Zahratul Fitri Zalfie Ardian Zulsuhendra, Edi