Garuda - Garba Rujukan Digital

p-Index From 2019 - 2024

6.043

P-Index

This Author published in this journals

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

Author-ID : 2501340

Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mechanical Engineering Transportation

Published : 69 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4 5

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

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

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

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)

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.

Bus Arrival Prediction – to Ensure Users not to Miss the Bus Lutfi Fanani; Achmad Basuki; Deron Liang
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 2: April 2015
Publisher : Institute of Advanced Engineering and Science

Predicting arrival times of buses is a key challenge in the context of building intelligent public transportation systems. The bus arrival time is the primary information for providing passengers with an accurate information system that can reduce passenger waiting times. In this paper, we used the normal distribution method to the random of travel times data in a bus line number 243 in Taipei area. In developing the models, data were collected from Taipei Bus Company. A normal distribution method used for predicting the bus arrival time in bus stop to ensure users not to miss the bus, and compare the result with the existing application. The result of our experiment showed that our proposed method has a better prediction than existing application, with the probability user not to miss the bus in peak time is 93% and in normal time is 85%, greater than from the existing application with the 65% probability in peak time, and 70% in normal time.

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

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.

Design of Pervasive Discovery, Service and Control for Smart Home Appliances: An Integration of Raspberry Pi, UPnP Protocols and Xbee Sabriansyah Rizqika Akbar; Maystya Tri Handono; Achmad Basuki
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science

Pervasive technology is an important feature in smart home appliances control. With pervasive technology, the user is able to discover and control every device and each service without initialization configuration and setup. Since single-board computer often used in smart home appliances, combining pervasive technology and microcomputer/single-board computer will be important to be applied and make a possibility to create a smart home system based on the requirement of it users that will be beneficial for the smart home users and the developers. This paper proposed a design of pervasive discovery, service, and control system for smart home appliances by integrating Raspberry Pi, UPnP protocols, and Xbee that able to control an RGB LED services such as switching, dimming, change color and read a temperature sensor as an example in smart home appliances. This paper enriched the raspberry Pi GPIO function to be able to control via TCP/IP network with UPnP protocol and receive information from a temperature sensor node via Xbee communication. Service control time is measured with UPnP round trip time by subtracting HTTP response arrival with HTTP request time. GPIO processing time measured at the application level by counting a timer that starts before GPIO process and ended after GPIO successfully executed.

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

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%.

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

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.

An Effective Chromosome Representation on Proportional Tuition Fees Assessment Using NSGA-II Farid Jauhari; Wayan Firdaus Mahmudy; Achmad Basuki
Journal of Information Technology and Computer Science Vol. 4 No. 3: Desember 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Proportional tuition fees assessment is an optimization process to find a compromise point between student willingness to pay and institution income. Using a genetic algorithm to find optimal solutions requires effective chromosome representations, parameters, and operator genetic to obtain efficient search. This paper proposes a new chromosome representation and also finding efficient genetic parameters to solve the proportional tuition fees assessment problem. The results of applying the new chromosome representation are compared with another chromosome representation in the previous study. The evaluations show that the proposed chromosome representation obtains better results than the other in both execution time required and the quality of the solutions.

Website Visitors Forecasting using Recurrent Neural Network Method Putu Bagus Arya; Wayan Firdaus Mahmudy; Achmad Basuki
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. The number of visitors and content accessed by users on a site shows the performance of the site. Therefore, forecasting needs to be done to find out how many users a website will come. This study applies the Long Short Term Memory method which is a development of the Recurrent Neural Network method. Long Short Term Memory has the advantage that there is an architecture of remembering and forgetting the output to be processed back into the input. In addition, the ability of another Long Short Term Memory is to be able to maintain errors that occur when doing backpropagation so that it does not allow errors to increase. The comparison method used in this study is Backpropagation. Neural Network method that is often used in various fields. The testing using new visitor data and first time visitors from 2018 to 2019 with vulnerable time per month. The computational experiment prove that the Long Short Term Memory produces better result in term of the mean square error (MSE) comparable to those achieved by Backpropagation Neural Network method.

Internet of Things (IoT) Cloud Platform Using MQTT End-to-Cloud Architecture Fariz Andri Bakhtiar; Moh. Wildan Habibi; Adhitya Bhawiyuga; Achmad Basuki
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

IoT devices are constrained in computation and storage, therefore cannot store all long-term obtained data or perform complex computations. Shifting those jobs to cloud platform are feasible, yet rising heterogeneity and security issues. This study proposes an IoT cloud platform to facilitate communication among heterogeneous devices and the cloud while ensuring devicesâ€™ validity. It uses publish/subscribe paradigm with an end-to-cloud architecture and HTTP-based auth server. The proposed system has successfully addressed heterogeneity and security issues. Performance tests conclude that the fewer publishers publish data simultaneously, the smaller the delay. Moreover, the system performs better at up to 250 publishers as the average delay is under 1000 ms, compared to 500 publishers that has average delay above 1000 ms. On its scalability, in 250-concurrent-publishers experiment, the system affords 191 publishers responded in under one second with 100% success rate. In 500-concurrent-publishers one, 187 responded in under one second with 99% rate.

Co-Authors 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 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 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 Pramukantoro, Eko Sakti Primantara Hari Trisnawan Putri Rizqia Hardein Putu Bagus Arya Raden Arief Setyawan 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 Widhi Yahya Widhi Yahya yuliana diah pristanti Zaky Abdussalam Zeddin Arief Zefanya Hermanta

Title

Found 69 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 69 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 69 Documents
Search