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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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Sistem Deteksi Kematangan Buah Mangga berdasarkan kandungan Gas NH3, C2H5OH dan VOCs menggunakan metode K-Nearest Neighbor (K-NN) Luqmanul Halim Zain; Eko Setiawan; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Mango is a fruit from a tropical climate besides having an interesting taste characteristic, mangoes have various nutritional content and a distinctive aroma. Mango (Mangifera indica L.) has more than 270 aroma of volatile compounds in different mango varieties (Shibamoto, T. et al, 1990). One of the problems in mango production is the classification process for whether mangoes are ripe. In the case of ripe mangoes, sometimes there are mangoes that have a fairly ripe color but still taste sour, and vice versa. Because of that we need a system that can determine the level of maturity of mangoes based on aroma. In this study, a system was designed to detect ripeness in mangoes based on aroma using the K-Nearest Neighbor method. In the process of classifying the sample data, Arduino nano is used as data processing. The training data is taken from mangoes with different ripeness levels, after that the tested mangoes will be detected their gas content with TGS2602, MQ135 and MQ5 sensors, after data has been obtained it will be processed by the K-Nearest Neigbour method. The classification results of the mango ripeness level will be displayed on the LCD screen along with the sensor readings. In system testing, the results classification accuracy with 15 test data, the highest accuracy reached 86.6% at K = 3 compared to the values of K = 5.7 and 9.
Rekayasa Sistem Lampu Lalu Lintas berdasarkan Kepadatan Dua Persimpangan menggunakan Naive Bayes dan Komunikasi Soket Abdul Muiz Anggit Budiyantoyo; Eko Setiawan; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 11 (2021): November 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Congestion is a serious problem in this world. In Indonesia, congestion is a problem that always occurs every year. Congestion is caused by several factors, one of the causes of congestion is the ineffective and less optimal traffic light system that exists today. The current traffic light system often causes vehicles to accumulate in one of the sections that have a high level of vehicle density because the traffic lights on that section do not get the duration of the green light in accordance with the density of vehicles on that section. In addition to being caused by a high level of vehicle density, congestion in a segment is also caused by vehicles stopping on an active segment (green light) because they are waiting for a connecting link to a nearby intersection that is experiencing congestion so that vehicles cannot pass through the connecting segment. The system built by the author aims to optimize the current traffic light system to be more effective by providing a green light duration by considering the state of the density of vehicles on the section and also the density of vehicles on the section that connects the intersection with the surrounding intersection. This system uses a Raspberry Pi 4, TL LED light, and a Sumo Simulator running on a laptop. Roads and intersections are built and simulated using the Sumo Simulator. Naive Bayes is used to classify the Induction Loop Sensor data contained in the Sumo Simulator and predict the density level classes that exist on a road segment. The Raspberry Pi 4 will receive class prediction data that has been processed from a laptop using Socket Programming and will adjust the TL LED Light according to the data received. Tests are carried out on each segment that has been optimized using the system with an average accuracy of 91.66%. testing was also carried out using 3 different Route Trips with an average simulation result of 407 steps faster than the usual traffic light system. This system has an average execution time of 0.6057408571 seconds.
Sistem Kendali Pitch, Roll dan Ketinggian Quadcopter dengan Isyarat Tangan menggunakan Kalman Filter Muhammad Junifadhil Caesariano; Eko Setiawan; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

UAV (Unmanned Aerial Vehicle) is an aircraft that can be controlled remotely either by humans or programmed automatically. UAV control requires a joystick controller. However, the use of a joystick as a UAV controller requires special skills in its use. Therefore, the author created a hand position-based controller that is easier to understand by people who are not familiar with the use of joysticks. However, the sensor readings are often inaccurate, therefore the Kalman Filter is used as a solution to reduce the inaccuracy. The test results show that the use of kalman filter increases the accuracy of sensor readings by using the calculation of the Root Mean Square Error. Based on testing the suitability of control using hand gestures on the movement of the UAV, the accuracy rate of control success is 85% for pitch and roll movements and 70% control success for altitude control
Sistem Pengendali Kualitas Air untuk Budidaya Ikan Guppy berdasarkan Suhu dan Derajat Keasaman Air menggunakan Metode KNN (K-Nearest Neighbor) Rizky Widya Mahendra; Eko Setiawan; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia, which is an archipelagic country, is home to various types of fish, from edible fish to ornamental fish used to beautify a room. One of the most popular aquarium fish today is the guppy fish, so it's understandable that there are more and more guppy fish fans. Of course, currently guppy fish farming is a promising field of activity for current cultivators because of its high selling value. However, keeping guppy fish is not easy, because the quality of the water used in the guppy fish habitat must be maintained, otherwise the water quality will cause the fish to get sick. This condition can be caused because there are some cultivators who do not carry out routine maintenance for guppies. The most common mistakes are incorrect selection of the aquarium location which causes significant changes in water temperature, as well as improper water management which causes changes in water pH that are too high. So we need an automatic system that can control the condition of the water. By using the KNN (KNearest Neighbor) method, the accuracy value of K is obtained, the K value using K=3, K=5, and K=11 gets an accuracy value of 95%, while the K value using K=7 and K=9 accuracy of 100%, after KNN gets the results of the detection, these results will be useful for regulating the action of the actuator. The use of the system affects the development of guppies, for aquariums that use the system the growth of fish is faster than the aquarium that does not use the system..
Implementasi Wearable Device pada Monitoring Suhu Tubuh, Denyut Jantung dan Saturasi Oksigen dalam Darah menggunakan Low Power Mode Mahesha Bayu Paksi; Rizal Maulana; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Health is measuring the human condition itself based on mental and physical conditions. Health conditions can be determined by measuring their vital signs, namely heart rate and body temperature. One of the most important organs for humans that will be fatal if exposed to disease is the lungs. The use of wearable devices to check these important organs will be easy. The use of wearable devices that are used in daily activities will not last long if they use battery power. For this reason, the system utilizes the low power method to save the power used. This sleep mode feature will be implemented in a system that can monitor the state of the human body through temperature, heart rate and blood oxygen levels. In the heart rate reading test, the percentage of error during normal conditions is 9.42% and during exercise is 5.99%. In the temperature reading test, the error percentage is 2.44%. Sleep mode on the system is able to reduce current by 22.29% from 34.36 mA to 26.7 mA.
Sistem Identifikasi Penyakit Gagal Ginjal melalui Bau Mulut, Warna Urine dan Tekanan Darah dengan Metode Support Vector Machine Lia Safitri; Rizal Maulana; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The human body has a pair of kidneys that are shaped like the seed of a pea. Although it has a shape that is not so big, the kidneys have some crucial function in the human body. One of the functions of the kidneys is detoxification, which is removing metaboic waste that will become toxic if not removed from the body. One of the diseases that can attack the kidneys is kidney failure. Kidney failure is a condition when the kidneys cannot perform their functions and work properly. Kidney health should not be underestimated, then we need a system that can identify kidney conditions as early as possible to anticipate kidney damage in the human body. In this study, there are three parameters used to determine whether the kidneys are in normal condition or have kidney failure. First. To calculate the level of ammonia gas from bad breath with the MQ-135 sensor. Second, to calculated the RGB value of urine color using TCS3200 sensor and thridly, to measure blood pressure using the MPX5700AP sensor. These three parameters were choosen because they can beidentified using sensors. The data processing system in this system uses Arduino Uno. In addition, the selected classification method is support vector machine (SVM). After testing 10 times on 20 input training data. The level of accuracy of the test that have been done is 80% and the average computation time required is around 37.10 second.
Simulasi Metode Dueling Double Deep Q-Learning pada Unmanned Aerial Vehicle untuk Menghindari Halangan Riyad Febrian; Eko Setiawan; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The ability to avoid obstacles is a subsystem of the navigation system that must be owned by an autonomous robot such as the Unmanned Aerial Vehicle (UAV). This ability governs the process of observing environmental data, making decisions and commands to control movement. Implementation of the avoiding obstacles with conventional methods tends to be static and unable to adapt. Therefore, Implementing this with an artificial intelligence (AI)-based systems will enhance the adaptivity. Reinforcement Learning (RL) is one of the AI or Machine Learning methods that has a characteristic in terms of direct learning in the environment. This study proposes an RL simulation analysis using the Dueling Double Deep Q-Learning (D3QN) method on the UAV to avoid obstacles. The simulation is run on the Airsim simulator and the UAV is a quadcopter. The perceptual configuration of the quadcopter is using a monocular camera, ultrasonic sensor and collision sensor. This study examines the comparative analysis of thresholds of 1 meter and 2 meters, batch sizes 32 and 128. The test results show that the thresholds of 2 meters and batch size 128 provide a more stable visualization plot and converge in less than 70 episode.
Adaptasi Pergerakan pada Robot Beroda terhadap Jalan Halang Rintang dengan Metode Fuzzy Billy Gusparentaqi; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 4 (2022): April 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In this study, the aim of this research is to design the adaptation of the movement of the wheeled robot using the fuzzy method. In this wheeled robot, there are 3 ultrasonic sensors input and 2 DC motor output. These inputs and outputs will be used as variables for the fuzzy method. This input variable consists of sensor (left), sensor (front) and sensor (right), each of which has 2 sets of membership functions, namely near and far. This output variable consists of a DC motor (right) and a DC motor (left), each of which has 2 sets of membership functions, namely slow and fast. The number of if-then rules in the fuzzy method used is 8 rules. The test was carried out as many as 3 experiments on the movement of the wheeled robot, namely moving straight, moving to turn right and moving to turn left. This test succeeded in proving that the fuzzy method can control the movement of the wheeled robot.
Simulasi Algoritme Hector SLAM untuk Pemetaan 2D pada Quadcopter berbasis ROS Selina Kusmiawati; Eko Setiawan; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 5 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Quadcopter is an Unmanned Aerial Vehicle (UAV) that is deployed to operate in areas that are not maximally accessible by Unmanned Ground Vehicles (UGV) in geographic structures that have been distorted due to natural disasters. Quadcopter requires the ability to recognize the surrounding environment by using a map. A map is a set of features that describe the environment such as walls, obstacles, landmarks, etc. Maps are relatively easy to make in a static environment, but in a disaster-damaged environment, maps will be more difficult to create because the environment has changed. The solution to this problem is that the quadcopter must be able to build its own environmental map. To build a map, a mapping process is needed that can be done using Simultaneous Localization and Mapping (SLAM). Hector SLAM is one of the SLAM algorithms which works based on scan matching technique and without odometer. Simulations were carried out to test the 2D mapping results from the Hector SLAM algorithm. The mapping was carried out with a LiDAR sensor embedded in the quadcopter and tested in 3 different environments. Simulations were carried out with 3D Gazebo and Rviz simulators based on Robot Operating System (ROS). There are 36 test scenarios carried out with the best map accuracy obtained with a Structural Similarity Index (SSIM) value of 0.78, Mean Squared Error (MSE) value of 5344.1, and Pixel Matching percentage of 89.59%.
Simulasi Algoritme Hector SLAM untuk Pemetaan 2D pada Quadcopter berbasis ROS Selina Kusmiawati; Eko Setiawan; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 5 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Quadcopter is an Unmanned Aerial Vehicle (UAV) that is deployed to operate in areas that are not maximally accessible by Unmanned Ground Vehicles (UGV) in geographic structures that have been distorted due to natural disasters. Quadcopter requires the ability to recognize the surrounding environment by using a map. A map is a set of features that describe the environment such as walls, obstacles, landmarks, etc. Maps are relatively easy to make in a static environment, but in a disaster-damaged environment, maps will be more difficult to create because the environment has changed. The solution to this problem is that the quadcopter must be able to build its own environmental map. To build a map, a mapping process is needed that can be done using Simultaneous Localization and Mapping (SLAM). Hector SLAM is one of the SLAM algorithms which works based on scan matching technique and without odometer. Simulations were carried out to test the 2D mapping results from the Hector SLAM algorithm. The mapping was carried out with a LiDAR sensor embedded in the quadcopter and tested in 3 different environments. Simulations were carried out with 3D Gazebo and Rviz simulators based on Robot Operating System (ROS). There are 36 test scenarios carried out with the best map accuracy obtained with a Structural Similarity Index (SSIM) value of 0.78, Mean Squared Error (MSE) value of 5344.1, and Pixel Matching percentage of 89.59%.
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