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All Journal Jurnal Ners Indonesia Komunikasi Fisika Indonesia Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Sinergi Jurnal Pengabdian UntukMu NegeRI JURNAL MEDIA INFORMATIKA BUDIDARMA IT JOURNAL RESEARCH AND DEVELOPMENT Prosiding Seminar Nasional Teknoka INOVTEK Polbeng - Seri Informatika JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) International Journal of Electrical, Energy and Power System Engineering (IJEEPSE) JINAV: Journal of Information and Visualization Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal PkM (Pengabdian kepada Masyarakat) Malcom: Indonesian Journal of Machine Learning and Computer Science SATIN - Sains dan Teknologi Informasi
Feri Candra
Universitas Riau
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Nursing Physics Public Health Social Sciences Veterinary

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Sistem Pengenalan Pola Karakter Huruf Korea Menggunakan Metode Principal Component Analysis Dan Jaringan Syaraf Tiruan - Back Propagation Delsavonita, Delsavonita; Candra, Feri
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 5 (2018): Edisi 2 Juli s/d Desember 2018
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Abstract

This paper describes about a recognition sistem for Korean characters into Latin form by using Principle Component Analysis Method and Artificial Intelligence - Back Propagation Approach. This sistem uses image of Korean characters as input data with 65x65 pixel of original image size and is processed by image preprocessing in the form of pixel size conversion into 15x15 pixel binary image. Every image is then extracted to produce an image feature. The features are processed first using Principle Component Analysis to reduce image feature before they enter classification stage by using Artificial Intelligence - Back Propagation Approach. This study uses 10 sample data of Korean vowel letters, obtained from 25 different font types and each font consists of normal and bold sample. Total data reaches 500 samples divided into 70 training data and 30 testing data. Architecture of this artificial intelligence uses 3 hidden layers . Each hidden layer consists of 20, 20 and 5 neurons, one output neuron. The result of this sistem research is obtained an accuracy of 95%.Keyword : Korean Letters a.k.a Hangul, Principle Components Analysis, Artificial Intelligence - Back Propagation
Perancangan Internet Supervisory Control dan Data Acquisition (I –Scada) Universitas Bung Hatta Dani, Febry Rachma; Candra, Feri; Soesilo, Eddy
Prosiding Seminar Nasional Teknoka Vol 3 (2018): Prosiding Seminar Nasional Teknoka ke - 3
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (850.176 KB) | DOI: 10.22236/teknoka.v3i0.2817

Abstract

I-SCADA merupakan suatu sistem pengendalian alat jarak jauh berbasis web atau menggunakan jaringan internet, dengan kemampuan memantau dan mengendalikan data-data dari alat yang dikendalikan. Teknologi I-SCADA memungkinkan mengontrol dan memonitoring secara langsung kondisi tersebut. Dalam sistem monitoring dan pengontrolan ini dilakukan pengukuran besaran listrik seperti arus, tegangan, daya dan faktor daya serta mengontrol unit-unit beban pada Universitas Bung Hatta Kampus Proklamator III ruangan A11 (IT ROOM). Adapun tujuan penelitian ini adalah untuk membuat alat pengontrol dan monitor energi listrik ruangan A11 (IT Room) Kampus Proklamator III Universitas Bung Hatta dari jarak jauh berbasis web. Alat yang dibuat terdiri dari komponen – komponen seperti sensor arus, sensor tegangan tegangan ,relay, Arduino Mega, Modul Ethernet Shield serta dilengkapi dengan fasilitas server web. Masing-masing komponen diuji sebelum dirangkai menjadi sebuah sistem. Dari hasil enam kali pengujian didapatkan error 0 % dan waktu komunikasi 1.16 detik- 1.30 detik.
Pengiriman Data Detak Jantung Menggunakan Teknik Kompresi Pada Raspberry PI Akbar, Nurhadi; Candra, Feri
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 6 (2019): Edisi 2 Juli s/d Desember 2019
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Abstract

Heart attack is one of the causes of high mortality, so a lot of research make a tool to monitor human heart activities. In this study, researchers use a Raspberry pi that is connected to the AD 8232 module. The AD 8232 module to detect heart signal, commonly called ECG signals. The AD 8232 module is connected with an ADC module to convert analog signals into digital signals that are connected to raspberry pi, then the ECG signal conduct a compression process. The compression process aims to minimize the byte of storage in the raspberry pi where as ECG signal measurements are carried out in real-time. To get the right and optimal compression method without destruct the ECG signal data, researchers compare two data compression methods. The two data compression will be used are the Huffman Code and Lempel Ziv Welch. The results of the comparison ratio of data before and after the compression process for are 43.96% huffman and 88.61% for lempel Ziv Welch.Key words: Raspberry Pi, EKG module, AD 8232 module, compression, Algoritma Huffman
Pemanfaatan Raspberry Pi 3 Pada Pembuatan Sistem Absensi Berbasis Pengenalan Wajah Komariah, Siti; Candra, Feri
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 6 (2019): Edisi 1 Januari s/d Juni 2019
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Abstract

Biometrics is an automatic method for recognizing someone based on physical characteristics or behavior, including Face Recognition. Generally used for identification and verification. Identification is the process of recognizing and matching of a it is person's biometric data in a database that contains a person's character record. Verification is the process of information determining whether someone is in accordance with his/her look. In this research, a biometric attendance system designed using a tool called Rasberry Pi 3 (Mini Computer) for taking user face images (photo grid) then planting is eigenface algorithms and artificial neural network. Rasberry Pi often abbreviated as Raspi is a single board computer whereas whereas the it’s size same as credit card that can be used to run official programs, computer games and media player for high resolution videos. The eigenface method is face recognition based on the Principal Component Analysis. On the eigenface method image is captured and stored in the database to become training data which compared to the sample data. ANN used because it has ability to learn from the data trained. With the design of this attendance system, it is expected to avoid negative things, for example, the loss of student attendance data because there are too many signatured papers in the attendence list for each subject. The results of testing face data used 3 hidden layers where the first layer has 32 neurons, the second layer has 18 neurons, and the third layer has 8 neurons, it concludes that the face recognition succed to recognize somebody’s face as his/her photograph is 100%.Keywords : Face Recognition, Raspberry Pi 3, Eigenface, Neural Network.
Implementasi Teknologi Augmented Reality Untuk Pembelajaran Sistem Ekskresi Manusia Berbasis Android Rezkiana, Nisa Tri; Candra, Feri
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 6 (2019): Edisi 1 Januari s/d Juni 2019
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Abstract

The development of communication and information technology grows rapidly at this time is very influential in changing people's lifestyle in various fields, such as education. In Academic Atmosphere, especially learning process in Senior High Schools level currently is using the 2013 Curriculum. By following the development of technology can be accepted by students, such as Power Point (PPT) and Three-dimensional (3D) animation that uses interactive mobile devices. One of learning media based on technology is Augmented Reality (AR) technology, this technology combines two-dimensional (2D) or 3D virtual objects into the real-world environment. Inside of it, there is an additional reality that can be applied in all senses, including hearing and senses. In Senior High School Level, one of the subjects is Biology, which a theory that reveals students must use higher understanding level to understand it. That theory is called excretory system in human lung. Implementing Technology Augmented Reality (AR), based on 3D android as the makes students be easyfier to understand hat theory.Keywords: Augmented Reality, Academic Atmosphere, Android, Biology, Excretion System.
Aplikasi Pengenalan Plat Nomor Kendaraan Mahasiswa Di Universitas Riau Noprizal, Noprizal; Candra, Feri
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 6 (2019): Edisi 2 Juli s/d Desember 2019
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Vehicle license plate recognition application has been found in shopping centers, university, and other agency buildings with various methods of recognition. Some examples of methods used such as digital image processing techniques, neural networks and so forth. This study makes an application for the introduction of license plates, especially for student vehicle license plates in the university area. This application is developed with Digital Image Processing Methods and Artificial Neural Networks.In this study, 900 training data are used, taken from 200 photo vehicle number plates, to train 36 characters that contain 26 alphabets and 10 decimal numbers. The training data is used to test 30 photos of vehicle license plates. Plate photos used as training and testing data are the Indonesian standard with black and white plates. Artificial Neural Network used to recognize vehicle license plate by using the BPNN method with parameters Epoch 1000, Hidden layer1 with node 60, Hidden layer2 with node 55, Goal 0.001.The final conclusion of this Study shows that the use of Artificial Neural Network BPNN method is very good, with the best testing accuracy obtained, namely 98% and 1.25 error.Keywords: Digital Image Processing, Artificial Neural Networks,BPNN, Vehicle License Plate
Sistem Pengenalan Motif Songket Melayu Menggunakan Ekstraksi Fitur Principal Component Analysisdan Gray Level Co-Occurence Matrix Dan Jaringan Saraf Tiruan Gressiva, Gressiva; Candra, Feri
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 5 (2018): Edisi 2 Juli s/d Desember 2018
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Abstract

Malay Songket Woven cloth Riau is one of the symbols of the weaving art from Riau Province. Riau songket Woven clothis woven by using golden silk yarn or cotton yarn. it has shaped motifs fromgold or silver yarn . Songket motifs system can be done with two ways uses Principal Component Analysis (PCA) andGray Level Co-Occurence Matrix(GLCM). this research comparesPrincipalComponent Analysis (PCA) andGray Level Co-Occurence Matrix(GLCM) features extraction by using Backpropagation Artificial Intelligence (AI) method with Matlab 2016b,to get the best featureextraction method for recognition songket motifs. This study uses five songket motifs that consist of, Pelita Flower, Bamboo Shoot Flower, Pistil Mangosteen, Sow Flower and Cloud Elbow, torecognize riau songket, 100 data are headed consisting of 60 Training Data and 40 Test Data. results of testing recognition system of songket motif with a combination of training parameters by using epoch 1000, and learning rate of 0.01 prodauce 82% Principal Component Analysis (PCA) and 92%Gray Level Co-Occurence Matrix(GLCM)Keywords: Woven cloth Riau, Principal Component Analysis (PCA) , Gray Level Co-Occurence Matrix(GLCM), Artificial intelligence (AI), Backpropagation Method
APLIKASI PENGENALAN PLAT NOMOR KENDARAAN DI UNIVERSITAS RIAU Noprizal; Feri Candra
JURNAL FASILKOM (teknologi inFormASi dan ILmu KOMputer) Vol 9 No 3 (2019): Jurnal Fasilkom
Publisher : Fakultas Ilmu Komputer, Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (472.513 KB) | DOI: 10.37859/jf.v9i3.1670

Abstract

Abstract Vehicle license plate recognition application has been found in shopping centers, university, and other agency buildings with various methods of recognition. Some examples of methods used such as digital image processing techniques, neural networks and so forth. This study makes an application for the introduction of license plates, especially for student vehicle license plates in the university area. This application is developed with Digital Image Processing Methods and Artificial Neural Networks. In this study, 900 training data are used, taken from 200 photo vehicle number plates, to train 36 characters that contain 26 alphabets and 10 decimal numbers. The training data is used to test 30 photos of vehicle license plates. Plate photos used as training and testing data are the Indonesian standard with black and white plates. Artificial Neural Network used to recognize vehicle license plate by using the Backpropagation method with parameters Epoch 1000, Hidden layer1 with node 60, Hidden layer2 with node 55, Goal 0.001. The final conclusion of this Study shows that the use of Artificial Neural Network Backpropagation method is very good, with the best testing accuracy obtained, namely 98% and 1.25 error. Keywords : digital image processing, artificial neural networks, vehicle license plate Abstrak Aplikasi pengenalan plat nomor kendaraan sudah banyak ditemukan di pusat perbelanjaan, universitas, dan gedung instansi dengan berbagai metode pengenalan. Beberapa contoh metode yang digunakan seperti teknik pengolahan citra digital, jaringan syaraf tiruan dan lain sebagainya. Disini penulis membuat sebuah aplikasi pengenalan plat nomor kendaraan khususnya untuk plat nomor kendaraan mahasiswa yang ada dilikungan Universitas Riau. Aplikasi ini dikembangkan dengan metode pengolahan citra digital dan jaringan syaraf tiruan. Pada penelitian ini, digunakan 700 data pelatihan yang diambil dari 200 foto plat nomor, untuk melatih 36 karakter. Data pelatihan tersebut kemudian digunakan untuk menguji 30 foto plat nomor kendaraan. Foto plat yang dijadikan untuk data pelatihan dan pengujian yaitu plat standar indonesia yang berwarna hitam dan putih. Jaringan syaraf tiruan yang digunakan untuk melakukan pengenalan yaitu dengan Metode Backpropagation dengan parameter Epoch 1000, Hidden layer1 dengan jumlah node 60, Hidden layer2 dengan jumlah node 55, Goal 0,001. Kesimpulan akhir dari penelitian ini yaitu menunjukan bahwa penggunaan Metode Backpropagation jaringan syaraf tiruan ini sangat bagus, dengan akurasi pengujian terbaik yang didapat yaitu 98% dengan eror 1,25. Kata kunci: pengolahan citra digital, jaringan syaraf tiruan, Backpropagation, plat nomor
Sistem Pendukung Keputusan Untuk Pendistribusian Beras Masyarakat Miskin Menggunakan Logika Fuzzy Sugeno Febiola, Dwi Suci; Candra, Feri
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 7 (2020): Edisi 2 Juli s/d Desember 2020
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Abstract

Poor people’s rice program or commonly known as Raskin is one of the government’s effort to reduce the burden of spending on the poor and as a social protection. To prevent mistakes in determining Raskin recipients and to avoid cheating by certain parties a system is needed. Decision support systems can overcome this problem, the system can support decision making Raskin recipients based on the criteria specified, so that the calculation is more accurate then the fuzzy logic implementation is used in decision making. The use of fuzzy logic in this system is based on the advantages of fuzzy logic, namely fuzzy logic tolerates incorrect data, fuzzy logic can model functions that are not linear, and fuzzy logic is based on natural language that is easy to understand. The fuzzy logic method used in this study is the Mamdani Method and Sugeno Method, which of the two methods will be compared to the best method by calculating the accuracy and error rate of the two methods. Keywords: Raskin, Decision support systems, Fuzzy logic, Recipient
Perancangan Sistem Pakar Untuk Mendiagnosa Penyakit Nyeri Perut Dengan Metode Teorema Bayes Berbasis Web Ningsih, Sri Purnama; Candra, Feri; Zulharman, Zulharman
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 8 (2021): Edisi 2 Juli s/d Desember 2021
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Abstract

People who still do not pay attention to a stomachache disorder, due to the busyness of their daily activities. With this, many people experience stomach pain at an already serious stage and even difficult to treat. Due to lack of attention to early symptoms. With this we need someone who is an expert in their field, namely an expert. So that the problems that occur can be resolved properly according to the correct handling procedure. Expert systems can help deal with problems that require expertise in certain fields. One of them is in the health sector, especially in handling abdominal pain. This expert system is very helpful in making decisions, from this expert system can collect and store knowledge by someone or several people from experts in a knowledge base and use a reasoning system resembling an expert in solving problems. This research will use the Bayes theorem method because it fits very well with the existing problems. To test the accuracy of the testing data obtained by experts with expert system output, the appropriate output results are obtained with an accuracy rate of 94.44%.Keywords: Stomach Pain Diseases, Expert System, Bayes Theorema
Co-Authors Adiya, M. Hasmil Ahmad Syahfrizal Akbar, Nurhadi Anand, Barri Anhar Anhar Antonius Rajagukguk Bayu Fharadila Chairun Nisa Chi-chi Salsa Amaza Dani, Febry Rachma Darwin Manurung Delsavonita, Delsavonita Desnelita, Yenny Dewi Nasien Dina Lovita Sari Dina Veranita Eddy Hamdani Faisal Karim Fathra Annis Nauli Fathur Rohman, Fathur Febiola, Dwi Suci Gressiva, Gressiva Herman Herman Hidayat, Ilham I. Yasri Indra Yasri JR Lessy Eka Putri Kurniawan Kurniawan Lukmannil Hakim Luthfi Afif Mailestari Wina Yance Minarni Minarni Minarni Shiddiq, Minarni Misrawati Misrawati Mohammad Fisal Rabin Monica Oktavianti Muhammad Rizki Radhelan Muhammad Sandy Prastyo Muhammad Syafii Muhammad Syafii Ningsih, Sri Purnama Noprizal Noprizal Noprizal, Noprizal Noveri Lysbetti Marpaung Nurhalim Dani Ali Rabil Kurniawan Rahmat Rizal Andhi RAHMAT WIBOWO Ramadhan Ramadhan Ramadhan Refli Erdinal Restuyoda, Raka Rezkiana, Nisa Tri Roby Esta Sunara Roni Sanjaya Saktioto Saktioto Salhazan Nasution Salhazan Nasution Salsabilla Azahra Putri Setiabudi, Muhamad Indra Sherkhing Angriawan Siswanto Siswanto Siti Komariah Siti Komariah Soesilo, Eddy Sri Wahyuni Suryani Suryani Syafiqoh, Nidya Nur T Yudi Hadiwandra T. Yudi Hadiwandra Warman Fatra Yanda Sepri Yanifal Yusnita Rahayu Zulharman Zulharman Zulharman Zulharman, Zulharman