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All Journal International Journal of Electrical and Computer Engineering Perfecting a Video Game with Game Metrics Jurnal EECCIS Journal of Enviromental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Network Engineering Research Operation [NERO] Jurnal Teknik Mesin dan Mekatronika (Journal of Mechanical Engineering and Mechatronics)
Achmad Basuki
Faculty Of Computer Science, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mechanical Engineering Transportation

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Pengendalian Kemacetan Jaringan Melalui Per-Flow Multipath Routing Fransiska Sisilia Mukti; Achmad Basuki; Onny Setyawati
Jurnal EECCIS Vol 12, No 1 (2018)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (506.801 KB)

Abstract

Kemacetan terjadi ketika jumlah paket yang ditransmisikan melalui jaringan telah mendekati kapasitas penanganan paket jaringan. Hal ini menjadi faktor utama untuk diketahui lebih dini, guna menghindari adanya kegagalan dalam proses routing. Sebagian besar protokol routing yang digunakan saat ini   menggunakan algoritma yang menghasilkan jalur tunggal saja, tanpa memperhatikan permintaan trafik yang bersifat fluktuatif. Penggunaan jalur tunggal dapat menyebabkan terjadinya kemacetan yang berdampak kepada pemborosan sumber daya. Penelitian ini bertujuan untuk melakukan pengendalian kemacetan jaringan dengan mengkombinasikan mekanisme multipath routing dan congestion control pada protokol routing OSPF. Hasil pengujian menunjukkan keunggulan sistem dalam tiga aspek, yaitu kestabilan nilai throughput (100%) sehingga tidak ada packet loss, pengiriman data 50% lebih cepat, dan utilisasi jaringan yang lebih baik.
Identifying Citronella Plants From UAV Imagery Using Support Vector Machine Candra Dewi; Achmad Basuki
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.7450

Abstract

High-resolution imagery taken from Unmanned Aerial Vehicle (UAV) is now often used as an alternative in monitoring the agronomic plants compared to satellite imagery. This paper presents a method to identify Citronella among other plants based on UAV imagery. The method utilizes Support Vector Machine (SVM) to classify Citronella among other plants according to the extraction of texture feature. The implementation of the method was evaluated using two group of datasets: 1) consists of Citronella, Kaffir Lime, other green plants, vacant soil, and buildings, and 2) consists of Citronella and paddy rice plants. The evaluation results show that the proposed method can identify Citronella on the first group of datasets with an accuracy 94.23% and Kappa value 88.48%, whereas on the second group of datasets with an accuracy 100% and Kappa value 100%.
Optimasi Flow Entries Untuk Mencegah Flow Table Overflow Pada Server Load Balancing Berbasis Software Defined Networking Agung Wahyu Setio Budi; Achmad Basuki
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (855.301 KB)

Abstract

Software Defined Networking (SDN) is new paradigm in computer network management to replace a complex conventional network into the flexible and efficient network by separating the control plane and data plane.This concept lead the control plane define each of flow to be written into data plane. However, the space in the flow table is limited resource, requires careful management to prevent flow table overflow. This research discusses a flow entries management to prevent flow table overflow in SDN by proposing two mechanism of flow removal, that is flow expiry and flow modification. The flow expiry remove an expired flow based on its time, meanwhile the flow modification will be triggered whenever the flow tablespace is nearly full. The implementation of our proposal carried out on a stateless server load-balancing application on SDN. The evaluation results show that the system is able to prevent flow table overflow. Before implements our proposal, 53% of total packet did not get response from server. After implements our proposal, 100% of total packet can accommodate by flow table and get a service from server. In addition, the reuse of flow entries can reduce the value of network latency.
Desain dan Implementasi In-Network Caching Pada Content Centric Networking Menggunakan CCN-Lite Dengan Simulator OMNeT++ Ibrahim Ibrahim; Achmad Basuki; Eko Sakti Pramukantoro
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (380.131 KB)

Abstract

Content Centric Networking (CCN) is a proposed architecture for addressing current Internet issues in terms of data distribution. The CCN is content-centric based, where the data search is performed using the name of the content, not the content host. CCN also has a different caching mechanism than caching in general called in-network caching. This study aims to find out how the performance of in-network caching on CCN by design and implementation using CCN-Lite in OMNeT ++ environment. The parameters tested were delivery latency and cache hit ratio (CHR). The result of the simulation is done, the smallest delivery latency is 10.69 ms. This value is obtained from the caching process, when compared with the latency of delivery without caching that is equal to 32.45 ms. It proves that with the caching, the latency gets lower. The highest CHR obtained in the CCNTLV protocol file is 0.54 or 54%, when compared with the CCNB file protocol of 0.45 or 45%. This proves that the higher the value of CHR the better the content is served.
KLASIFIKASI PENYAKIT MATA KATARAK BERDASARKAN KELAINAN PATOLOGIS DENGAN MENGGUNAKAN ALGORITMA LEARNING VECTOR QUANTIZATION Hariyanto, Rudi; Basuki, Achmad; Hasanah, Rini Nur
Network Engineering Research Operation [NERO] Vol 2, No 3 (2016): NERO
Publisher : Universitas Trunojoyo Madura

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Abstract

Katarak merupakan salah satu jenis kerusakan mata yang menyebabkan lensa mata berselaput, rabun yang bervariasi sesuai tingkatannya hingga menjadi kebutaan. Penyakit katarak ini menggerogoti mata secara perlahan, sedikit demi sedikit tanpa rasa sakit yang dialami pasien tetapi jika penanganannya terlambat maka mengakibatkan kebutaan permanen. Ketepatan penentuan jenis dan letak katarak secara dini sangat penting untuk mencegah dampak keparahan katarak yang lebih parah. Prosedur utama diagnosis katarak (Gold Standart Prosedur) dilakukan menggunakan Computed Tomography ( CT ) scan dan Magnetic Resonance Imaging (MRI). Alternatif diagnosis dapat dilakukan melalui pemeriksaan fisik, pemeriksaan laboratorium, riwayat penyakit, serta informasi lain yang terkait. Tujuan penulisan ini menyajikan hasil kajian mengenai implementasi metode Learning Vector Quantization (LVQ) untuk memudahkan klasifikasi penentuan jenis penyakit katarak serta tingkat keparahannya. Hasil penelitian menunjukkan bahwa penggunaan metode LVQ memberikan tingkat akurasi penentuan sebesar (99%) serta durasi waktu pelatihan (training) sampel sebesar (0,06 detik).Kata Kunci: Katarak, Klasifikasi, Learning Vector Quantization
Home Appliance Control with Publish Subscribe in Social Media Sabriansyah Rizqika Akbar; Eko Setiawan; Achmad Basuki
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 2: June 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i2.1309

Abstract

 Nowadays, Internet social media has enriched the way people to communicate and interact each other. Will it be possible for people to interact with their home appliances around? This paper proposes a new approach in smart home system that made possible for people to remotely interact with their appliances using social media networks. In this paper, we present a smart home prototype system that leverages Twitter’s Application Program Interface (API) to remotely control home appliances over the Internet. Experiment results showed that the system immediately responds to remote commands sent over a social media account to control home appliances. The system responds the command in 3672.96 ms. Publish-subscribe method work better in mass announcement communication system. Home system could notice all householders in less than 6 s independenly from number of householder. Our proposed method gives alternative solution to build reliable, fast and simple control method.
Analisis Performansi Raspberry-Pi/Aptus Box Sebagai Portable Server MOOCS Basuki, Achmad; Akbar, Sabriansyah Rizkika; Setyawan, Raden Arief
Jurnal EECCIS Vol 12, No 2 (2018)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.558 KB)

Abstract

Dewasa ini pemanfaatan e-learning sebagai sarana pembelajaran telah sangat massif. Berkembangnya internet memberikan berbagai alternatif sarana pembelajaran bagi setiap orang. Namun sayangnya kemudahan ini tidak dapat dinikmati oleh masyarakat di area terpencil yang tidak memiliki akses internet. Salah satu cara agar masyarakat tersebut tetap dapat menikmati pembelajaran melalui e-learning adalah menggunakan portable server. Penelitian ini mencoba menganalisa penggunaan Raspberry Pi, sebuah minicomputer, sebagai portable server untuk e-learning.
Metode Deteksi Intrusi Menggunakan Algoritme Extreme Learning Machine dengan Correlation-based Feature Selection Sulandri Sulandri; Achmad Basuki; Fitra Abdurrachman Bachtiar
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8, No 1: Februari 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.0813358

Abstract

Deteksi intrusi pada jaringan komputer merupakan kegiatan yang sangat penting dilakukan untuk menjaga keamanan data dan informasi. Deteksi intrusi merupakan proses monitor traffic pada sebuah jaringan untuk mendeteksi adanya pola data yang dianggap mencurigakan, yang memungkinkan terjadinya serangan jaringan. Penelitian ini melakukan analisis pada traffic jaringan untuk mengetahui apakah paket tersebut mengandung intrusi atau merupakan paket normal. Data traffic yang digunakan untuk deteksi intrusi pada penelitian ini diambil dari dataset KDD Cup. Metode yang digunakan untuk melakukan deteksi intrusi dengan cara klasifikasi yaitu dengan menggunakan metode Extreme Learning Machine (ELM). Namun, dengan menggunakan metode ELM saja tidak mampu untuk menghasilkan akurasi yang baik maka, pada metode ELM perlu ditambahkan metode seleksi fitur Correlation-Based Feature Selection (CFS) untuk meningkatkan hasil akurasi dan waktu komputasi. Hasil penelitian yang dilakukan dengan menggunakan metode ELM menunjukkan tingkat akurasi mencapai 81,97% dengan waktu komputasi 3,39 detik. Setelah ditambahkan metode seleksi fitur CFS pada ELM tingkat akurasi meningkat secara signifikan menjadi 98,00% dengan waktu komputasi 2,32 detik. AbstractIntrusion detection of computer networks is a very important activity carried out to maintain data and information security. Intrusion detection is the process of monitoring traffic on a network to detect any data patterns that are considered suspicious, which allows network attacks. This research analyzes the network traffic to find out whether the packet contains intrusion or is a normal packet. Traffic data used for intrusion detection in this study were taken from the KDD Cup dataset. The method used to do intrusion detection by classification is using the Extreme Learning Machine (ELM) method. However, using the ELM method alone is not able to produce good accuracy, so the ELM method needs to be added to the Correlation-Based Feature Selection (CFS) feature selection method to improve the accuracy and computational time. The results of the research conducted using the ELM method showed an accuracy rate of 81.97% with a computation time of 3.39 seconds. After adding the CFS feature selection method to ELM the accuracy level increased significantly to 98.00% with a computing time of 2.32 seconds.
The Extended Dijkstra’s-based Load Balancing for OpenFlow Network Widhi Yahya; Achmad Basuki; Jehn Ruey Jiang
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 2: April 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (443.569 KB) | DOI: 10.11591/ijece.v5i2.pp289-296

Abstract

This paper proposes load-balancing algorithm on the basis of the Extended Dijkstra’s shortest path algorithm for Software Defined Networking (SDN). The Extended Dijkstra’s algorithm considers not only the edge weights, but also the node weights to find the nearest server for a requesting client. The proposed algorithm also considers the link load in order to avoid congestion. We use Pyretic to implement the proposed algorithm and compare it with related ones under the Abilene network topology with the Mininet emulation tool. As shown by the comparisons, the proposed algorithm outperforms the others in term of the network end-to-end latency, throughput and response time at the expense of a little heavier computation load and more memory usage on the SDN controller.
KLASIFIKASI PENYAKIT MATA KATARAK BERDASARKAN KELAINAN PATOLOGIS DENGAN MENGGUNAKAN ALGORITMA LEARNING VECTOR QUANTIZATION Rudi Hariyanto; Achmad Basuki; Rini Nur Hasanah
Network Engineering Research Operation Vol 2, No 3 (2016): NERO
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (655.322 KB) | DOI: 10.21107/nero.v2i3.63

Abstract

Co-Authors Adhitya Bhawiyuga Adhitya Bhawiyuga Adhitya Bhawiyuga Aditya Chamim Pratama Agung Wahyu Setio Budi Akbar, Sabriansyah Rizkika Akhmad Mukhtarom Al Aziiz Burhanudin Faidzin Labay Amalia Miftakhul Jannah Andi Yudiko Leonardo Solin Angger Abdul Razak Ariefanda Junediansyah Bayu Sutawijaya Budi Darma Setiawan Cahyo Karya Basuki Candra Dewi Candra Dewi Dahnial Syauqy Dany Primanita Kartikasari Deron Liang Eko Laksono Eko Sakti Pramukantoro Eko Setiawan Eko Setiawan Eldyto Puspa Laksana Endah Octaviana Nasution Fabiansyah Raam Pontoh Fahmi Alfareza Faisal Akhmadi Fandisya Rahman Farid Jauhari Faris Surya Akbar Fariz Andri Bakhtiar Fathan Abdurrahman Shani Amarta Putra Fitra Abdurrachman Bachtiar Fitra Abdurrachman Bachtiar Fitra Bachtiar Fransiska Sisilia Mukti Friska Anggia Nurlita Sari Hans Romario Sitorus Hariyanto, Rudi Hasanah, Rini Nur Hawwin Purnama Akbar Ibrahim Ibrahim Imron Sazali Ismawati Nurjannah Ismiarta Aknuranda Jehn Ruey Jiang Jodi Prayoga Wahyudwi Jonathan Rovelano Huwae Kasyful Amron Kasyful Amron Kevin Jonathan Harnanta Khabban Sayyidi Razin Surya Khafidzun Fadli La Ode Muh. Fadlun Akbar Laisa Ryry Pudja Mentari Lutfi Fanani Maskur Purwiadi Maystya Tri Handono Moh Wildan Habibi Moh. Wildan Habibi Mohammad Zulfikar Muhamad Miftahur Ridhoilah Muhamad Rizka Maulana Muhammad Aswin Muhammad Aziz Muslim, ST., MT., Ph.D Muhammad Khairullah Harto Muhammad Naufal Dzakie Muhammad Rafi Fauzan Fathin Muhammad Syaifuddin Zuhri Muharrom Abdillah Onny Setyawati Panca Mudjirahardjo Panser Brigade Muhammad Primantara Hari Trisnawan Primantara Hari Trisnawan Putri Rizqia Hardein Putu Bagus Arya Raden Arief Setyawan Raden Arief Setyawan, Raden Arief Rakhmadhany Primananda Rasidy Cakra Pratama Refri Rifwan Daharmi Reza Andria Siregar Rifki Karim Ramadhan Rini Nur Hasanah Rini Nur Hasanah Rizky Jelang Romadhondaru Rudi Hariyanto Rudi Hariyanto Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Shafira Aulia Indrarto Sulandri Sulandri Uis Yudha Tri Wirawan Wayan Firdaus Mahmudy Wayan Firdaus Mahmudy Widhi Yahya Widhi Yahya yuliana diah pristanti Zaky Abdussalam Zeddin Arief Zefanya Hermanta