Articles
<![CDATA[Distributed rule execution mechanism in smart home system ]]>
<![CDATA[Agung Setia Budi]]>;
<![CDATA[Hurriyatul Fitriyah]]>;
<![CDATA[Eko Setiawan]]>;
<![CDATA[Rakhmadhany Primananda]]>;
<![CDATA[Rizal Maulana]]>
<![CDATA[ International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijece.v12i4.pp4439-4448
<![CDATA[Smart home systems become an interesting topics in the last few years. Many researchers have been studied some features. Most of smart home system use a centralized architecture know as centralized smart home system (CSHS). The centralizedmechanism is easy to manage and to configure. However, in fault-tolerant systemparadigm it produces a problem. The entire system will fail, if the master station fails.Another problem of CSHS is centralized mechanism gives more data-flow. This condition makes the system has a greater delay time. To solve the problem, we proposea distributed rule execution mechanism (DREM). Compared to the centralized mechanism, the DREM allows a device to provide its service without any commands fromthe master station. In this mechanism, since the information does not need to go tothe master station, the data-flow and the delay-time can be decreased. The experimentresults show that the DREM is able to mask the failure in the master station by directlytransmit the data from trigger device to service device. This mechanism makes the services provision without master station possible. The mathematical analysis also shows that the delay time of the service provision of the DREM is less than the delay time ofCSHS.]]>
<![CDATA[Segway Line Tracer Using Proportional-Integral-Derivative Controllers ]]>
<![CDATA[Wijaya Kurniawan]]>;
<![CDATA[Mochammad Hannats Hanafi Ichsan]]>;
<![CDATA[Eko Setiawan]]>
<![CDATA[ TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016 ]]>
Publisher : <![CDATA[Universitas Ahmad Dahlan ]]>
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DOI: 10.12928/telkomnika.v14i2.3156
<![CDATA[Intelligent control, sensors and hardware integration are expected to generate an efficient transportation system and and minimum effort, to carry goods from one location to another location. Line tracer used by robot to transport follow the path, it has a system that uses a light sensor to read the color from a line that represent the path to make specific direction. Segway is two wheeled transportation item that have an efficient energy used. Nowadays line tracer can only work if it has three or more wheels and segway can only work with riders. This research segway designed by lego robot, PID (Proportional, Integral, Derivative) control used to control an input from gyroscope sensor in form of elevation angle of the earth. The control system are expected to control two wheeled Segway to reach steady state rapidly. So the Segway would run without involving human or without rider.]]>
<![CDATA[Semi-Adaptive Control Systems on Self-Balancing Robot using Artificial Neural Networks ]]>
<![CDATA[Eko Setiawan]]>;
<![CDATA[Dahnial Syauqy]]>
<![CDATA[ INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 5 No 2 (2021): August 2021 ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/intensif.v5i2.15296
<![CDATA[A self-balancing type of robot works on the principle of maintaining the balance of the load's position to remains in the center. As a consequence of this principle, the driver can go forward reverse the vehicle by leaning in a particular direction. One of the factors affecting the control model is the weight of the driver. A control system that has been designed will not be able to balance the system if the driver using the vehicle exceeds or less than the predetermined weight value. The main objective of the study is to develop a semi-adaptive control system by implementing an Artificial Neural Network (ANN) algorithm that can estimate the driver's weight and use this information to reset the gain used in the control system. The experimental results show that the Artificial Neural Network can be used to estimate the weight of the driver's body by using 50-ms-duration of tilt sensor data to categorize into three defined classes that have been set. The ANN algorithm provides a high accuracy given by the results of the confusion matrix and the precision calculations, which show 99%.]]>
<![CDATA[Implementasi Logika Fuzzy Pada Sistem Berbasis Field Programmable Gate Array (FPGA) ]]>
<![CDATA[Mochammad Hannats Hanafi Ichsan]]>;
<![CDATA[Eko Setiawan]]>;
<![CDATA[Mochamad Afief Hamidi]]>
<![CDATA[ Jurnal Teknologi Informasi dan Ilmu Komputer Vol 3 No 1: Maret 2016 ]]>
Publisher : <![CDATA[Fakultas Ilmu Komputer, Universitas Brawijaya ]]>
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DOI: 10.25126/jtiik.201631166
<![CDATA[Penggunaan perangkat mikrokontroller dewasa ini semakin banyak dipergunakan seperti arduino, atmega, FPGA dan lain sebagainya. Salah satu perangkat tersebut adalah FPGA (Field Programmable Gate Array). Bahasa yang digunakan pada FPGA adalah VHDL atau VHSIC (Very High Speed Integrated Circuit Hardware Description Language) merupakan salah satu jenis bahasa yang digunakan untuk mendeskripsikan fungsi rangkaian digital. Pada penelitian ini akan dijelaskan tentang implementasi tentang dasar Logika Fuzzy pada VHDL. Sehingga memiliki keuntungan jika dilakukan implementasi ini akan didapatkan rancang bangun logika fuzzy yang memungkinkan untuk diimplementasikan dengan cepat pada perangkat seperti Xilinx, Synosis dan lain sebagainya. Pada penelitian ini berhasil diimplementasikan, proses pengujian dilakukan dengan membandingkan perhitungan matematis dengan hasil keluaran sistem yang didapatkan akurasi sebesar 80%. Akan tetapi proses waktu eksekusi total untuk semua proses dalam Logika Fuzzy sebesar 145 ns.]]>
<![CDATA[Identifikasi Malicious Host dalam Local Area Network Menggunakan Teknik Graph Clustering dan Filtering ]]>
<![CDATA[Khafidzun Fadli]]>;
<![CDATA[Achmad Basuki]]>;
<![CDATA[Eko Setiawan]]>
<![CDATA[ Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 3: Juni 2020 ]]>
Publisher : <![CDATA[Fakultas Ilmu Komputer, Universitas Brawijaya ]]>
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DOI: 10.25126/jtiik.2020733339
<![CDATA[Keamanan pada Local Area Network (LAN) sekarang ini adalah masalah serius yang harus diperhatikan. Penyebab LAN menjadi tidak aman dikarenakan teknologi firewall tidak mampu melindungi host (komputer) dalam LAN dari penyebaran malware. Penyebaran malware yang terdapat dalam LAN dilakukan oleh host di dalam LAN yang disebut sebagai malicious host. Tindakan untuk mengurangi penyebaran malware dalam LAN dapat dilakukan dengan mengidentifikasi malicious host. Penelitian ini mengusulkan metode identifikasi malicious host berdasarkan aktivitas ARP request dengan menggunakan teknik graph clustering-filtering. Teknik graph clustering-filtering merupakan langkah-langkah pengelompokan serta penyaringan node dan edge berdasarkan parameter dari graph seperti weight edge, out-degree node dan weight out-degree node yang bertujuan untuk mengidentifikasi malicious host. Berdasarkan parameter dari graph seperti out-degree node dan weight out-degree node, penghitungan persentase aktivitas host dapat dilakukan untuk menunjukkan seberapa besar tingkat aktivitas host dalam melakukan broadcast ARP request, sehingga hasil penghitungan persentase aktivitas host dapat menentukan host yang diidentifikasi sebagai malicious host. Hasil penerapan teknik graph clustering-filtering terhadap 511 node dan 4144 edge didapatkan melalui pengamatan dan pengambilan data selama 3 jam dalam LAN kampus dapat divisualisasikan menjadi hanya 22 node dan 328 edge. Hasil penghitungan berdasarkan persentase jumlah aktivitas host menunjukkan 22 node menjadi 6 node yang diperkirakan sebagai malicious host. Dengan demikian, visualisasi graph menggunakan teknik graph clustering-filtering dan persentase aktivitas host dapat mengidentifikasi jumlah host yang dicurigai sebagai malicious host.AbstractLocal Area Network (LAN) security is a serious problem to consider. The cause of LAN becomes insecure because firewall technology is not able to protect the host (computer) in LAN from spreading malware. The spread of malware contained within a LAN is carried out by hosts in the LAN which are referred to as malicious hosts. Actions to reduce the spread of malware in the LAN can be done by identifying malicious hosts. This paper proposes a method of identifying malicious hosts based on ARP request activities using graph clustering-filtering techniques. Graph clustering-filtering techniques are steps of grouping and filtering nodes and edges based on graph parameters such as weight edges, out-degree nodes and weight out-degree nodes that aim to identify malicious hosts. Based on parameters from the graph such as out-degree node and weight out-degree node, the calculation of the percentage of host activity can be done to show how much the level of host activity in broadcasting an ARP request, so that the result of calculating the percentage of host activity can determine a host that is categorized as a malicious host. The results of graph visualization using graph clustering-filtering technique can display fewer nodes and edges, from 511 nodes and 4144 edges to 22 nodes and 328 edges observed and collected in a LAN within 3 hour in the campus LAN. The results of the calculation of the percentage of host activity show hosts from 22 nodes become only 6 nodes which are suspected as malicious hosts. Overall, graph visualization with graph clustering-filtering techniques and the percentage of host activity can find a number of hosts identified as malicious hosts.]]>
<![CDATA[Klasifikasi Tingkat Dehidrasi Berdasarkan Kondisi Urine, Denyut Jantung dan Laju Pernapasan ]]>
<![CDATA[Rizal Maulana]]>;
<![CDATA[Muhammad Rheza Caesardi]]>;
<![CDATA[Eko Setiawan]]>
<![CDATA[ Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 2: April 2021 ]]>
Publisher : <![CDATA[Fakultas Ilmu Komputer, Universitas Brawijaya ]]>
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DOI: 10.25126/jtiik.2021824379
<![CDATA[Dehidrasi merupakan suatu kondisi ketika tubuh kekurangan cairan. Secara umum terdapat tiga tingkatan dehidrasi, yaitu dehidrasi ringan, sedang dan berat. Tingkatan dehidrasi berat sangat berbahaya bagi penderitanya, bahkan dapat mengakibatkan kematian. Untuk mencegah terjadinya tingkatan dehidrasi yang berbahaya, maka diperlukan pendeteksian secara dini agar penderita dehidrasi segera mendapatkan penanganan yang cepat dan tepat. Terdapat beberapa parameter yang dapat digunakan untuk mendeteksi dehidrasi, diantaranya warna dan kadar ammonia pada urine, denyut jantung dan laju pernapasan. Pada penelitian ini, dirancang sebuah sistem klasifikasi tingkatan dehidrasi berdasarkan empat parameter tersebut dengan menggunakan metode klasifikasi k-nearest neighbor. Sistem yang dirancang mampu memberikan kemudahan untuk melakukan pemeriksaan secara mandiri dan mendapatkan hasil klasifikasi tingkat dehidrasi secara real-time. Dataset yang digunakan dalam penelitian ini berjumlah 75 data yang didapatkan dari pasien diare yang menjalani perawatan di Rumah Sakit. Data tersebut sudah memiliki tingkatan dehidrasi berdasarkan diagnosis dari dokter. Dari hasil pengujian yang telah dilakukan, metode k-nearest neighbor memiliki tingkat akurasi terbaik pada penggunaan nilai k=5 dan k=7 dengan nilai akurasi sebesar 96%. Abstract Dehydration is a condition when the body lacks of fluids, caused by the amount of fluid released by the body is greater than the fluids that enters the body. Dehydration is divided into three levels, mild, moderate and severe. Severe dehydration is very dangerous and can even lead to death in patients. To prevent dangerous levels of dehydration, early detection is needed to provide fast and precise treatment to patients. There are several parameters that can be used to detect dehydration, such as color and ammonia levels in urine, heart rate and respiratory rate. This paper designed a system to classify dehydration levels based on these four parameters using k-nearest neighbor classification method. The system is designed to be easy to use independently and provides real-time classification results. There are 75 datasets used in this paper, obtained from diarrhea patients in a hospital in Malang. Each data already has a label in the form of dehydration level based on the doctor’s diagnosis. From the test result, k-nearest neighbor has the best classification accuracy at k=5 and k=7 with the accuracy of 96%.]]>
<![CDATA[Peningkatan Utilisasi Jaringan Distributed Storage System Menggunakan Kombinasi Server dan Link Load Balancing ]]>
<![CDATA[Hawwin Purnama Akbar]]>;
<![CDATA[Achmad Basuki]]>;
<![CDATA[Eko Setiawan]]>
<![CDATA[ Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 3: Juni 2021 ]]>
Publisher : <![CDATA[Fakultas Ilmu Komputer, Universitas Brawijaya ]]>
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DOI: 10.25126/jtiik.2021834294
<![CDATA[Distributed Storage System (DSS) memiliki sejumlah perangkat server penyimpanan yang terhubung dengan banyak perangkat switch untuk meningkatkan utilisasi jaringan. DSS harus memperhatikan keseimbangan beban pada sisi server penyimpanan dan trafik data pada semua jalur yang terhubung. Jika beban pada sisi server penyimpanan dan trafik data tidak seimbang, maka dapat menyebabkan bottleneck network yang menurunkan utilisasi jaringan. Kombinasi server dan link load balancing adalah solusi yang tepat untuk menyeimbangkan beban pada sisi server penyimpanan dan trafik data. Penelitian ini mengusulkan metode kombinasi algoritme least connection sebagai metode server-load balancing dan algoritme global first fit sebagai metode link load balancing. Algoritme global first fit merupakan salah satu dari algoritme load balancing hedera yang bertujuan untuk menyeimbangkan trafik data berukuran besar (10% dari bandwidth), sehingga terhindar dari permasalahan bottleneck network. Algoritme least connection merupakan salah satu algoritme server load balancing yang menggunakan jumlah total koneksi dari server untuk menentukan prioritas server. Hasil evaluasi kombinasi metode tersebut didapatkan peningkatan pada rata-rata throughput sebesar 77,9% dibanding hasil metode Equal Cost Multi Path (ECMP) dan Round robin (RR). Peningkatan pada rata-rata penggunaan bandwidth sebesar 65,2% dibanding hasil metode ECMP dan RR. Hasil Penggunaan CPU dan memory pada server di metode kombinasi ini juga terjadi penurunan beban CPU sebesar 34,29% dan penurunan beban penggunaan memory sebesar 9,8% dibanding metode ECMP dan RR. Dari hasil evaluasi, penerapan metode kombinasi metode server dan link load balancing berhasil meningkatkan utilisasi jaringan dan juga mengurangi beban server. AbstractDistributed Storage System (DSS) has a number of storage server devices that are connected to multiple switch devices to increase network utilization. DSS must pay attention to the balance of the load on the storage server side and data traffic on all connected lines. If the load on the storage server side and data traffic is not balanced, it can cause a network bottleneck that reduces network utilization. The combination of server and link-load balancing is the right solution to balance the load on the server side of storage and data traffic. This study proposes a combination of the least connection algorithm as a server-load balancing method and the global first fit algorithm as a link-load balancing method. The global first fit algorithm is one of Hedera's load balancing algorithms which aims to balance large data traffic (10% of bandwidth), so as to avoid network bottleneck problems. Least connection algorithm is one of the server balancing algorithms that uses the total number of connections from the server to determine server priority. The results of the evaluation of the combination of these methods showed an increase in the average throughput of 77.9% compared to the results of the Equal Cost Multi Path (ECMP) and Round robin (RR) methods. The increase in the average bandwidth usage is 65.2% compared to the results of the ECMP and RR methods. The results of CPU and memory usage on the server in this combination method also decreased CPU load by 34.29% and a decrease in memory usage load by 9.8% compared to the ECMP and RR methods. From the evaluation results, the application of a combination of the server method and the link load balancing method has succeeded in increasing network utilization and also reducing server load.]]>
<![CDATA[Controlling the Nutrition Water Level in the Non-Circulating Hydroponics based on the Top Projected Canopy Area ]]>
<![CDATA[Hurriyatul Fitriyah]]>;
<![CDATA[Agung Setia Budi]]>;
<![CDATA[Rizal Maulana]]>;
<![CDATA[Eko Setiawan]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 2 (2022): April ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.70556
<![CDATA[Deep Water Culture Hydroponics is suitable for a large-scale plantation as it does not require turn-on the electric pump constantly. Nevertheless, this method needs an electric aerator to give Oxygen to the roots. Kratky’s and Dry Hydroponics are the two methods that suggest an air gap between the raft and the nutrient water level. The gap gives Oxygen to the roots without an aeration pump. Controlling the nutrient water level is required to give a good distance of air gap for Precision Agriculture. The root length estimation used to be done manually by opening the raft, but this research promotes automatic and non-contact estimation using the camera. The images are used to predict the root length based on the Top Projected Canopy Area (TPCA) using various Regression Methods. The test shows that the TPCA gives a high correlation toward the Root Length (>0.9). To control the nutrient water level, this research compares If-Else and the Linear Regression. The error between the actual level that is measured using an Ultrasonic sensor and the setpoint is fed to an Arduino Uno to control the duration of an inlet pump and the outlet pump. The If-Else and the Linear Regression method show good results.]]>
<![CDATA[Interpretasi Paham Radikalisme Pascabom di Surabaya dalam Perspektif Historis ]]>
<![CDATA[Eko Setiawan]]>
<![CDATA[ SANGKéP: Jurnal Kajian Sosial Keagamaan Vol. 2 No. 2 (2019): Radikalisme, Kritik Teori Sosiologi dan Wacana Politik di Indonesia ]]>
Publisher : <![CDATA[Asosiasi Sosiologi Agama Indonesia (ASAGI) ]]>
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DOI: 10.20414/sangkep.v2i2.629
<![CDATA[The humanitarian tragedy through a series of bombings carried out by one family, such as a willingness to be disguised for their actions as not to seek an attention, and the use of children in the acts of terrorism tosacrifice all family members, this has never happened in any part of the world which have swallowed recent casualties and property losses occurred in Surabaya, became a highlight for all Indonesian people and the world as well. The growth of radicalism eventually shows the face of violence in Indonesia, this terrorism movement is intended as a form of resistance, in carrying out its actions solely as a jihad to uphold the truth they believe in. The basis and purpose of their foundation is religion, but the religion which is narrowly understood and packaged in such a way becomes a radical ideology of resistance. It does not mean that terrorist activists of jihad are lack of education, some of them are smart people but they are frustrated by the socio-political hegemony of secularhedonic culture. Terror is still one of the ways to express radicalism, aterror which is motivated by religious ideology and dissatisfaction, is very dangerous due to an excessive individual fanaticism and willingness to sacrifice oneself in achieving the goals.]]>
<![CDATA[Evaluasi Topik Tersembunyi Berdasarkan Aspect Extraction menggunakan Pengembangan Latent Dirichlet Allocation ]]>
<![CDATA[Dinda Adimanggala]]>;
<![CDATA[Fitra Abdurrachman Bachtiar]]>;
<![CDATA[Eko Setiawan]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v5i3.3075
<![CDATA[Recently, Sentiment Analysis is used for expression detection of products or services. Sentiment Analysis is one category type with a level of aspect focused on extracting product aspects. One of the common methods used for aspect extraction is Latent Dirichlet Allocation (LDA) using random topic identification, but this method has not been able to find an acceptable topic with some aspects having been found. Undeterminable topics are referred to as the hidden topics. This study purpose is to evaluate and compare the suitability of identifying hidden topics between human and computer evaluation. The study is also focused on aspect extraction using a variety of LDA innovations. The data used in this study used case studies on e-Commerce. Data were processed using feature selection and grouped using LDA development. Then the data results are processed using Latent Topic Identification based on subjective and objective evaluations. The identification of hidden topic results was evaluated using several semantic and lexicon tests. The evaluation results indicate the comparison of two hidden topic identification assessment values is quite relevant with the average difference in value reaching 6%. As a result, computer calculations assist humans in determining topics if each topic has a low coherence value.]]>
