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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) International Conference on Engineering and Technology Development (ICETD) DINAMIKA DOTCOM Jurnal EECCIS Jurnal Teknologi Informasi dan Ilmu Komputer AGRIVITA, Journal of Agricultural Science International Journal of Advances in Intelligent Informatics JOIV : International Journal on Informatics Visualization Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Journal of Robotics and Control (JRC)
Heru Nurwarsito
Universitas Brawijaya Malang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mechanical Engineering

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Imputation of missing microclimate data of coffee-pine agroforestry with machine learning Nurwarsito, Heru; Suprayogo, Didik; Sakti, Setyawan Purnomo; Prayogo, Cahyo; Yudistira, Novanto; Fauzi, Muhammad Rifqi; Oakley, Simon; Mahmudy, Wayan Firdaus
International Journal of Advances in Intelligent Informatics Vol 10, No 1 (2024): February 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v10i1.1439

Abstract

This research presents a comprehensive analysis of various imputation methods for addressing missing microclimate data in the context of coffee-pine agroforestry land in UB Forest. Utilizing Big data and Machine learning methods, the research evaluates the effectiveness of imputation missing microclimate data with Interpolation, Shifted Interpolation, K-Nearest Neighbors (KNN), and Linear Regression methods across multiple time frames - 6 hours, daily, weekly, and monthly. The performance of these methods is meticulously assessed using four key evaluation metrics Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results indicate that Linear Regression consistently outperforms other methods across all time frames, demonstrating the lowest error rates in terms of MAE, MSE, RMSE, and MAPE. This finding underscores the robustness and precision of Linear Regression in handling the variability inherent in microclimate data within agroforestry systems. The research highlights the critical role of accurate data imputation in agroforestry research and points towards the potential of machine learning techniques in advancing environmental data analysis. The insights gained from this research contribute significantly to the field of environmental science, offering a reliable methodological approach for enhancing the accuracy of microclimate models in agroforestry, thereby facilitating informed decision-making for sustainable ecosystem management.
Rancang Bangun Sistem Administrasi Akademik Berbasis Multimedia Pada Multicliente E-Kiosk Di Lingkungan Program Teknologi Informasi Dan Ilmu Komputer Nurwarsito, Heru; Rusdianto, Denny Sagita; Prasetio, Barlian Henryranu
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 1 No 1: April 2014
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (695.175 KB) | DOI: 10.25126/jtiik.201411105

Abstract

Abstrak E-Kiosk adalah suatu sistem vending machine informasi bagi publik yang dapat diakses kapanpun pada umumnya tersedia di tempat-tempat publik. Secara umum e-Kiosk terdiri dari tiga kategori besar :Information Kiosk, Transaction Kiosk, dan Multimedia Kiosk. E-Kiosk dalam perkembangannya telah menjadi suatu fasilitas akses publik yang interaktif (self-service), terhubung dalam suatu sistem jaringan infonnasi terpusat dalam LAN (Local Area Network), Intranet, bahkan Internet. Dengan terhubungnya e-Kiosk dalam jaringan, maka diperlukan aplikasi berbasis web yang dapat melayani fungsie-Kiosk selama 24 jam oleh suatu server. Hal ini mutlak diperlukan mengingat fungsi utama e-Kiosk yang selalu standby dan selalu diakses oleh publik kapanpun dan dimanapun.Selain itu, juga diperlukan suatu manajemen trafik jaringan e-Kiosk tersebut agar dapat memberikan layanan yang memuaskan kepada publik. Pada Penelitian ini akan dilakukan rancang bangun server jaringan e-Kiosk (Multi Client e-Kiosk) yang dapat melakukan fungsi memberikan informasi dan akses administrasi akademik di lingkungan PTIIK kepada civitas akademik. Kata kunci: Kiosk, sistem informasi akademik Abstract E-Kiosk is a vending machine system for public information that can be accessed anytime in general available in public places. In general, e-Kiosk consists of three major categories: Information Kiosk, Transaction Kiosk, and Multimedia Kiosk. E-Kiosk in its development has become an interactive public access facilities (self-service), connected in a network system, The information centralized within a LAN (Local Area Network), Intranet, and even Internet. By e-Kiosk interlinked in a network, it is necessary to web-based applications that can serve fungsie-Kiosk for 24 hours by a server. It is absolutely necessary given the major functions of e-Kiosk is always standby and always accessible to the public whenever and wherever. It also required a traffic management e-Kiosk networking order to provide a satisfactory service to the public. This research will be conducted on the design of e-Kiosk network server (Multi Client e-Kiosk) that can perform the function of providing information and access to the academic administration, PTIIK and the academic community. Keywords: Kiosk, sistem informasi akademik
Implementasi Sistem Pendeteksi Serangan Denial of Service Slow Read Menggunakan Algoritma Random Forest Pada Suricata Simarmata, Gilbert Jonathan; Data, Mahendra; Nurwarsito, Heru
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 9 No 11 (2025): November 2025
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Serangan Slow Read merupakan salah satu varian dari Denial of Service (DoS) yang sulit dideteksi karena meniru pola lalu lintas normal dengan cara mempertahankan koneksi HTTP secara perlahan. Intrusion Detection System (IDS) seperti Suricata yang berbasis signature memiliki keterbatasan dalam mengenali pola serangan ini. Penelitian ini mengusulkan integrasi algoritma machine learning Random Forest ke dalam Suricata untuk meningkatkan kemampuan deteksi serangan Slow Read secara real-time. Dataset dibentuk melalui simulasi trafik normal dan serangan menggunakan JMeter dan SlowHTTPTest dalam lingkungan terkendali. Data dari log Suricata diproses melalui tahap pelabelan ulang, balancing, dan pemilihan fitur utama. Model Random Forest dilatih dengan data seimbang dan diuji menggunakan matrik evaluasi seperti accuracy, precision, recall, dan F1-score. Hasil evaluasi menunjukkan kemampuan klasifikasi dengan akurasi sebesar 0.94, precision 0.95, recall 0.94, dan F1-score 0.94. Sistem yang diintegrasikan ke dalam Suricata mampu mendeteksi trafik normal dengan akurasi 99.7% dan trafik serangan dengan akurasi 95.68%. Hasil ini menunjukkan bahwa pendekatan antara signature-based dan machine learning dapat meningkatkan kemampuan dalam mendeteksi serangan Slow Read.
Co-Authors Adaby, Resnu Wahyu Adhi Kurniawan Aidi Rahman Aji Prasetya Wibawa Alfrienza Tighfaraka Alifibioneri Ananda Adiyatma Putra Andy Wiranto Aprino, Dani Ardia Regita Pramesti ari kusyanti Armansyah Armansyah Arshad, Mohammad Syafwan Aryadna Nareindra Atiqo Tuzumah Baharum, Zirawani Barlian Henryranu P Barlian Henryranu Prasetio Bekti Widyaningsih Bintang Mada Suharsono Bisma Arie Yaqudsa Bisma Prasetya Cahyo Prayogo, Cahyo Cindy Zefira Afiani Denny Sagita Rusdianto Denny Sagita Rusdianto Desman Desman Devano Mirza Nugroho Didik Suprayogo Dwiki Ansarullah Ervani Sofyana Putra Fathul Hakim Fauzi, Muhammad Rifqi Fedro Jordie T. H. Simangunsong Fegi Eriyani Ferdi Cezano Santosa Fernanda Yerisha Hartinah Ridwan Firlhi Kurniawan Firstian Satya Yulihardi Fitra, Ahmad Ali Yuddin Galeh Prehandayana Getdra Saragih Sumbayak Guntur Wahyu Pamungkas Hairulnizam Mahdin, Hairulnizam Hassan, Azman Herdian Zend Komara I Putu Krisna Yoga Tanaya Imam Cholissodin Imam Cholissodin Kamri, Khairol Anuar Kasyful Amron Kharisma Fadillah Kuni Yustika Dewi M. Fatkur Rohman Made Widya Anjani Mahendra Data Mahendra Data Maulana Yoga Wiyananta Mirsha Akbar Muhamad Alfarisi Muhamad Romdoni Rachman Wijaya Muhammad Arhangga Satriawan Muhammad Isman Suga Muhammad Rizqi Fauzi Naufal Hilmi Ni Luh Irma Arini Niar Ariati Novanto Yudistira Nurul Azmi Nurul Hidayat Oakley, Simon Pradana, Kevin Dion Andre Pramukantoro, Eko Sakti Priyambadha, Bayu Purnomo Budi Santoso Purnomo Budi Santoso Putra, Mahdiaffan Dwi Putu Gede Sayoga Rakhmadhany Primananda Reynaldi Firman Tersianto Reza Andria Siregar Ricky Yohanes Ridwan Eko Prasetyo Rifqi Raditya Wibowo Rifqi Zumadilla Pratama Rika Yunitarini Riksa Suta Adji Riski Manta Simanjorang Rizal Fahturrizqi Salman Al Farizi Sandya Ratna Maruti Sarah Atemalem Octaviana Toruan Satrio Trimada Tarigan Seisarrina, Maulidya Larasaty Setyawan P. Sakti Setyawan Purnomo Sakti Shofura Naufal Rifiera Simarmata, Gilbert Jonathan Sindy Alvionita Su-Cheng Haw Sukron Alfa Dani Setiawan Tesa Putri Cendani Tyo Enos Revan Gultom Velient Vinandha Verio Brika Sejahtera Wayan Firdaus Mahmudy Widhi Yahya Wijaya Kurniawan Winda Silviana Yuli Wahyuni