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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Sosiologi USK (Media Pemikiran & Aplikasi) SANGKEP: Jurnal Kajian Sosial Keagamaan Habitus: Jurnal Pendidikan Sosiologi dan Antropologi Equalita: Jurnal Studi Gender dan Anak Journal of Gender and Social Inclusion in Muslim Societies Jurnal Ilmu Sosial dan Ilmu Politik Malikussaleh (JSPM) Hasanuddin Journal of Sociology (HJS). Yinyang: Jurnal Studi Islam Gender dan Anak Jurnal Sosiologi Dialektika Sosial Jurnal Riset sosial humaniora, dan Pendidikan (Soshumdik) Jurnal Ilmu Sosial dan Ilmu Politik
Eko Setiawan
Fakultas Ilmu Komputer, Universitas Brawijaya
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing Social Sciences Other

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Deteksi Pergerakan Bola Mata untuk Pemilihan Empat Menu Menggunakan Metode Facial Landmark dengan Ekstraksi Fitur LBP dan Klasifikasi K-NN Rhaka Gemilang Sentosa; Fitri Utaminingrum; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 4 (2020): April 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The more sophisticated technology makes all electronic devices can be made through joysticks, remote controls, and so on. This is a challenge for stroke sufferers because it limits them to move the member must make it able to rotate the device. Then the menu selection system needs to be made on the display that is able to make a sound to facilitate sufferers in communicating. Stroke sufferers have limitations to move members but can still move the two balls. This research was made to overcome their limitations by using the K-Nearest Neighbor classification method to classify the value of features resulting from ball motion detection using digital image processing with the face landmark method to convert eye areas and using the LBP method to extract features in the eye area. This system produces an accuracy of 100% and in dim lighting produces an accuracy of 60%, 20%, 100%, and 100% for moving the eyeball forward, right, left, and up. 100% accuracy results. The results of computational time are 399.7 ms, 398.4 ms, 398.4 ms, 396.8 ms for moving the eyeball forward, right, left, and up.
Sistem Klasifikasi Kualitas Daging Ayam menggunakan Metode K-Nearest Neighbors berbasis Arduino Zamaliq Zamaliq; Fitri Utaminingrum; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 5 (2020): Mei 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Chicken meat is one of the most abundant sources of animal protein consumed by the community. Chicken meat consumption needs will always increase due to several factors, namely, the price of chicken meat that is relatively affordable compared to beef, has good nutritional quality, and is easily processed into various types of cuisine. Chicken meat sellers in the market or on the side of the road sometimes their sales results are not fully sold in the hands of consumers for various economic reasons, storability and ignorance of the public using hazardous additives and preservatives may be done some examples of abuse on food products is the use of synthetic preservatives for example formalin and borax. In overcoming this problem the determination of the classification of tiren chicken meat, rotten chicken, and formalin chicken, then the right method is needed to do the classification. K-NN method can work independently on each object features to be classified. In this system, several components are used: Arduino Mega Mini microcontroller to process data and perform calculations, the TGS2602 sensor is useful for detecting aroma in chicken meat, the accuracy of the error generated by 3.42% is placed in a container, the Ph BNC Electrode sensor Probes with an accuracy error level of 25.89% are useful to measure acid base levels in chicken meat. For classification using the K-NN presentation method the accuracy was found to be 80.95%.
Sistem Pengukur Kesegaran Daging Sapi menggunakan Metode K-Nearest Neighbor (K-NN) dengan Fitur Penambahan Data Latih berbasis EEPROM Jeffry Atur Firdaus; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 5 (2020): Mei 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beef is one of the food products that is in demand by the people of Indonesia because it has high nutritional value. 70% air, 20% protein, 9% fat and 1% ash. The freshness of beef affects the quality of beef. Simple characteristics of beef that is still fresh is the color of fresh red meat, soft flesh fiber and yellow fat. The quality loss in beef can be marked by changes in color, taste and smell. This is caused by the development of microorganisms in beef. Eating beef contaminated by microorganisms can cause food poisoning and other health problems. In this research, a system can classify beef quality using the K-Nearest Neighbor algorithm and Arduino nano EEPROM. This system uses beef RGB color input using TCS3200 sensor, gas quality to measure the intensity of NH3/ammonia gas using the MQ135 sensor and push-button as a medium of user interaction with the system. Further sample data is classified using K-Nearest Neighbor on Arduino Nano using training data stored on EEPROM. The results of the classification of "fresh" "medium" or "rotten" grade beef will be shown on the LCD. In addition, data on the EEPROM can also be added and removed for system development through a menu on the LCD. The average computation time obtained in the system to classify beef quality is 117ms and the classification system with 81 training data on 27 test data obtains an accuracy of up to 85%.
Perancangan Algoritma Jaringan Saraf Tiruan Backpropagation untuk Navigasi Robot Beroda Mohammad Riski Aprilianto; Gembong Edhi Setyawan; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 5 (2020): Mei 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Wheeled robot is a robot that moves using wheels under certain conditions so that a good navigation system is needed. Whether or not the robot navigation system is influenced by the software system and the algorithm that is running. Over time, artificial neural network algorithm is much in demand and developed because it has good flexibility to the nonlinear environment. Therefore, in this study a backpropagation artificial neural network algorithm is designed for navigation of wheeled robots. Artificial neural networks have advantages, among others, the level of accuracy is better than pattern recognition algorithms such as fuzzy and KNN. Besides artificial neural networks also have good flexibility in solving problems with multidimensional classes. Backpropagation artificial neural network is a supervised neural network in which there is a network training. In network training there are several factors that influence, including hidden layers, momentum, and learning rate. In addition to good training, robot speed regulation also needs to be considered so that the robot has good stability in its environment. Based on the time and error values ​​in the network training, the number of hidden layer nodes of 5 has the best results on input and output of 4 nodes. Whereas in the PWM motor 150 value setting obtained a fairly good movement stability for the wheeled robot used.
Desain Datapath Arsitektur Komputer MIC-1 8 bit Menggunakan IC74XX Seprianto Ray Roganda Sianipar; Mochammad Hannats Hanafi Ichsan; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The architecture of the MIC-1 8 bits is one of the simplest computer architecture in which there are registers such as the program counter, a memory buffer register, register A, register B, an external input and integrated logic unit. The register collection was used as a datapath for the execution of instructions. Intergrated circuit 74XX (IC74XX) is an intergrated circuit (IC) series used to implementation simple logical series. IC74XX, in one set of IC74XX, there are several varieties of gates that can perform a variety of functions involving AND, OR, NOT, adder, and multiplexer. On a series of datapath computer architecture MIC-1 8 bits uses switches and IC74051. The switch function is as a data input entered by the user by hand and IC74051 to process datapath data that is used as a b bus input. Arihmetic logic unit (ALU) using IC74LS32, IC74LS04, IC74LS08, IC74LS08, and IC74LS251N in the arithmetic and logic process. Datapath and arithmetic logic unit (ALU) use 5-volt power as resources and LED as output. With functional testing results it obtained according to manual calculations in multiplexer datapath operation and was reduced to non-functional testing part.
Rancang Bangun Sistem Monitoring dan Klasifikasi Lingkungan Hidup Larva Lalat Tentara Hitam (Hermetia Illucens) dengan Metode K-Nearest Neighbor (K-NN) Amri Yahya; Rizal Maulana; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The process of biodegradation is the activity of using a microorganism to carry out the process of handling waste quickly. Microorganisms that can handle waste efficiently are black larvae. Environmental quality of larvae supports the process of biodiversity. The environmental quality monitoring system uses several sensors and a microcontroller which is packaged in the form of a monitoring and classification system. Classification of the k-NN method produces three classes namely "Optimal", "Medium", and "Bad" with input of some environmental quality of larvae. Internet of Things (IoT) is used to send monitoring and classification system data results to an Android application. The results of the k-NN classification test showed 91.3%. Computational time testing gets time with an average of 4275ms on a system. Testing the sending of data from the system to Firebase and Firebase to the Android application results that 100% of data is sent according to the monitoring and classification system data.
Pengoptimalan Lampu Lalu Lintas menggunakan Metode Naive Bayes Classifier Ivan Kasogi; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Congestion is one of the main problems for big cities in Indonesia. This is influenced by the growth number of vehicles in Indonesia that are not matched by road growth. So, congestion cannot be avoided. In addition to these factors, the static traffic system in Indonesia contributes as a cause of congestion. at a traffic junction, sometimes a segment must wait for waiting time, while in other segments that intersect have no queue. So in this research of traffic light optimization system was designed using the naive bayes classifier method which was simulated using the SUMO Simulator Software and will communicated with Arduino through serial communication. In this research the density or length of the queue and each section will be used as input system that will be processed with training datas. The output system is the duration of traffic light that adjust by density in each sections. From the tests carried out, the suitability of naive bayes classifier with training datas reaches 100%. The Arduino and SUMO Simulator suitability tests reached 100% and the traffic light system optimization test using the naive bayes classifier produces a percentage of 86,66% better than the traffic system without naive bayes classifier of 15 times the side carried out.
Perancangan Dan Implementasi Sistem Pola Berjalan Pada Robot Hexapod Menggunakan Metode Inverse Kinematic Abdullah Asy Syakur; Rizal Maulana; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

There are many types of robot as a helper device, such as legged robot. This legged robot has the ability to crawl and walk even on a terrain which can't be reach by other vehicle. There are many contest of firefighter robot for legged robot. Six legged robot (hexapod) is the most often to use in robot competition because of it's walk stability is better than any other legged robot. This research using hexapod which each leg has 3 DOF of servo. The walking gait of hexapod are calculated using inverse kinematic to generate the motion angle of servo on each DOF. Each DOF on this hexapod are build from Dynamixel AX-12 servo, and Arduino as the processor of the inverse kinematic calculation. Input of inverse kinematic based on coordinate of “end-of-effector”. The generated angles are sent to each servo in motion data format, so the end of effector can move to the expected position. There are 4 step in one cycle walk of a leg, the position of each step are calculated with inverse kinematic. The accuracy test shows that the end of effector has 3.51 % of mean error. The accuracy test of straight-walk-accuracy test shows that hexapod has 7.14 % of mean deviation error on average speed 17,27 cm/second. While the side walk test result has 3.76 % of deviation error on speed 14.27 cm/second
Implementasi Prototype Kapal sebagai Sistem Monitoring Kualitas Air menggunakan Algoritme Naive Bayes Axel Elcana Duncan; Rizal Maulana; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 7 (2020): Juli 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Living things really need water as a source of life. Lots of people use water in the waters for various things. Water quality standards using three characteristics, physics, chemistry, and biology are prerequisites for water quality. Through its very important role for all living things, it is very much needed an embedded system that is equipped with an algorithm for monitoring water quality, given the complexity, and conventionality of existing methods for measuring water quality. A ship prototype system using Arduino Nano, WEMOS D1 Mini, Genuine Analog pH Meter sensor, DS18B20 sensor, Turbidity sensor, JSN-SR04T sensor, L298N motor driver, and 6V DC motor can help from existing problems. This system is in the form of a ship so that it can carry out comprehensive monitoring. This system also uses the Naive Bayes algorithm in classifying through features such as pH, temperature, turbidity, and depth as inputs. Good, medium, and bad results will be the class will be output. In getting these results, this system uses as many as 40 training data and 20 test data. The average error reading of the Genuine Analog pH Meter sensor from 10 tests is 8,233%. The average error of DS18B20 sensor readings from 10 tests is 0.859%. Turbidity sensors have a linear graph, the more turbid the water the smaller the voltage value. The average error of sensor reading JSN-SR04T from 10 times the test is 2.492%. The accuracy of sending data from 10 tests is 100%. The accuracy of the classification using the Naive Bayes algorithm is 90%. The average computational time performed by the system from 10 tests is 3.7055 ms. The accuracy rate on the drive system from 3 times of testing is 100%.
Navigasi Robot Beroda menggunakan Algoritma SVM (Support Vector Mechines) Nengah Affan Riadi; Gembong Edhi Setyawan; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 7 (2020): Juli 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Wheeled robots need a navigation ability to operate properly. One of the navigation implementations of the wheeled robot is that the wheeled robot can help the SAR (Search and Rescue) team find victims. Wheeled robots need a navigation algorithm to do the job. This research will use one type of navigation algorithm, the SVM (Support Vector Machines) algorithm. In addition, the wheeled robot also requires a sensor and actuator that can support the performance of the wheeled robot. This research will use an Ultrasonic Sensor which is used to detect obstacles around the robot wheel and DC motor as the propulsion of the wheeled robot. The results of the tests conducted in this study, obtained the best PWM (Pulse Width Mudulation) motor value that will be used for operating robots is 150, Ultrasonic Sensors and DC Motors have a pretty good functionality and can be used in robots with wheels well, and accuracy SVM algorithm output that compares with the actual output is 87.5%.
Co-Authors A. Ashar Ashari Abdul Muiz Anggit Budiyantoyo Abdullah Asy Syakur Adhly Hasbi Fadhlillah Adji Kuncoro Bhangun Agung Setia Budi Ahmad Mustafa Kamal Amri Yahya Andika Bhayangkara Andre Adikusuma Arya Rizky Imansyah Harahap Axel Elcana Duncan Bagas Gerry Caesario Bagus Sawung Timur Barlian Henryranu Prasetio Billy Gusparentaqi Dahnial Syauqy Dias Alfan Nur Ilham Dimas Dwi Saputra Dinda Adimanggala Dionisius Marcello Divito Duwi Hariyanto Farras Nabil Fatchullah Wahid Afifi Fitra Abdurrachman Bachtiar Fitriyah, Hurriyatul Gembong Edhi Setyawan Hani Firdhausyah Haryanto Sihombing Hurriyatul Firtiyah Irfan Harlim Ivan Kasogi Jeffry Atur Firdaus Lia Safitri Lucky Pamboro Luqmanul Halim Zain Lutfi Anang Makruf M. Khanif Ashar Mahesha Bayu Paksi Mochammad Hannats Hanafi Ichsan Mochammad Zava Abbiyansyah Mohammad Riski Aprilianto Muhamad Delta Rudi Priyanto Muhammad Bilal Muhammad Junifadhil Caesariano Muhammad Kholash Fadhilah Muhammad Rheza Caesardi Muhammad Rifqi Radifan Masruri Muhammad Taufiq Azra Haromain Nengah Affan Riadi Nikmatus Soleha Okky Nizka Pratama Othman Mirizi Batubara Pandy Aldrige Simanungkalit Priyo Prasetyo Putra Berlian Ageng Mukti Putri Harviana Rahmat Yusuf Afandi Rakhmadhany Primananda Reza Budi Pratikto Rhaka Gemilang Sentosa Riyad Febrian Rizal Maulana Rizky Widya Mahendra Ryan Anggito Priono Sabriansyah Rizqika Akbar Selina Kusmiawati Seprianto Ray Roganda Sianipar Septiyo Budi Perkasa Syaafi’ Nurwahyono Sustami Tan Varian Kashira Tedy Kurniawan Utaminingrum, Fitri Vedric Amos Sinaga Widasari, Edita Rosana Wijaya Kurniawan Yanottama Oktabrian Yoga Sugma Pradana Yosia Nindra Kristiantya Zamaliq Zamaliq