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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Paradigma JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Ilmiah Media Sisfo The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Bulletin of Computer Science Research Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Informatika dan Rekayasa Komputer PROCEEDING OF INTERNATIONAL CONFERENCE ON BUSINESS MANAGEMENT AND ACCOUNTING Bulletin of Informatics and Data Science Jurnal Informatika: Jurnal Pengembangan IT The Indonesian Journal of Computer Science Scientific Journal of Informatics Jurnal Pengabdian Masyarakat Unama Jurnal Lentera Ilmiah Pengabdian Masyarakat
Yovi Pratama
Universitas Dinamika Bangsa
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Eksperimen Penerapan Sistem Traffic Counting dengan Algoritma YOLO (You Only Look Once) V.4. Yovi Pratama; Errissya Rasywir
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3309

Abstract

Traffic counting is the activity of counting traffic (vehicles) that pass on the road in a certain period. The purpose of traffic counting is to collect traffic data, determine traffic characteristics, determine vehicle composition and measure traffic performance. With the YOLO V.4 algorithm, changes in the position, size and volume of the detected object can be carried out in several tests. Although not all the results of using this algorithm are perfect on all data, the results tend to be good. This is related to the services provided in the form of a convolutional layer on YOLO reducing downsample or reducing image dimensions by using anchor boxes, this algorithm can also increase accuracy. The YOLO V.4 algorithm utilizes an image feature scanning model using the concepts of angles and directions mathematically. From the results of experiments carried out in this study, obtained detection results that have a fairly good accuracy in the results of separating frames from video data. Irregular transformations of position, dimension, composition and direction can still be captured as the same feature. YOLO's ability in feature engineering is an acknowledgment that has been successfully proven in this research.
Sistem Pakar Diagnosis Penyakit Tanaman Karet dengan Metode Fuzzy Mamdani Berbasis Web Hendrawan Hendrawan; Abdul Harris; Errissya Rasywir; Yovi Pratama
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2521

Abstract

Rubber plants can be attacked by various diseases originating from fungi, pests, animals and even cancer cells. A method that is able to diagnose rubber disease is needed so that it is hoped that it can help farmers detect symptoms early so that the productivity of rubber plantations can increase. This study developed an analysis of the results of the diagnosis of rubber plant disease using the Mamdany Fuzzy method. The choice of this method departs from the fuzzy mamdany research which states that the fuzzy mamdany method is able to resemble the workings of the human brain intuitively. With the implementation of the Expert System for Diagnosis of Disease in Rubber Plants with the Fuzzy Mamdani Algorithm, the work of diagnosing rubber plant diseases can be done more automatically. With 33 sympthon parameter data for rubber plant disease symptoms and 14 classes of rubber disease diagnosis tested using the Mamdany Fuzzy algorithm, the results obtained an accuracy of 81.74%, a value of 5-cross validation of 80.93% and a value of 10-cross validation of 82.30%. This shows that the application of the fuzzy mamdani algorithm produces good accuracy in diagnosing rubber plants.
Analisis Statistik Pemilihan Bidang Skripsi Menggunakan Ekspectation Maximization Yovi Pratama
Jurnal Ilmiah Media Sisfo Vol 11 No 1 (2017): JURNAL ILMIAH MEDIA SISFO
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (818.314 KB)

Abstract

Pada sebuah perguruan tinggi jurusan ilmu komputer, mahasiswa dituntut untuk menerapkan apa yang mereka pelajari ke dalam sebuah implementasi atau penerapan pada bidang tertentu baik dalam bentuk format pembelajaran, analisis maupun berbentuk aplikasi, program atau sistem komputer sebagai syarat lulus (skripsi). Namun dengan banyaknya bidang yang dipelajari membuat mahasiswa bingung menentukan bidang yang akan diambil. Berdasarkan hal tersebut peneliti melakukan perekomendasian bidang skripsi menggunakan algoritma Expectation Maximization Clustering. Cluster yang dihasilkan berasal dari data kelompok mata kuliah terkait penelitian yang diambil dari Computer Science Curriculla yang diterbitkan oleh ACM dan IEEE. Dari data mata kuliah yang terkait bidang penelitian, peneliti mencocokan mata kuliah dengan kode mata kuliah yang terdapat pada program studi Teknik Informatika. Hasil dari penelitian ini membuktikan bahwa rekomendasi bidang Skripsi dengan menggunakan Expectation Maximization Clustering mampu memberi nilai rekomendasi terendah mencapai nilai 1 % dan nilai tertinggi 100 % serta rata-rata 67 % dari jumlah mahasiswa sebanyak 11.167 orang.
Application of YOLO (You Only Look Once) V.4 with Preprocessing Image and Network Experiment Yovi Pratama; Errissya Rasywir; Akwan Sunoto; Irawan Irawan
The IJICS (International Journal of Informatics and Computer Science) Vol 5, No 3 (2021): November 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v5i3.3386

Abstract

In computer science, specifically in the field of image processing, many reliable algorithms have been found. Previously it was introduced that the YOLO (You Only Look Once) V.3 algorithm. In this case, the application of the YOLO algorithm that we carried out was applied experimentally by utilizing image preprocessing techniques. In this study, image preprocessing was carried out. The image of the Microsoft COCO dataset that was preprocessed in this study used the method of image dimension reduction and image quality improvement. The Microsoft COCO dataset image dimension reduction method used is the Principal Component Analysis (PCA) method and to improve the image quality of the Microsoft COCO dataset using Gaussian Smoothing. Then after the fine-tuning process, there is an increase in the mAP value by an average of 8.99% so that the five models can have an mAP above 80%. The highest mAP value is owned by the model using the schema after the fine-tuning process. From the results of experiments carried out in this study, obtained detection results that have fairly good accuracy in the dataset results. Irregular transformations of position, dimension, composition and, direction can still be captured as the same feature. YOLO's ability in feature engineering is an acknowledgment that has been successfully proven in this research. Although not all the results of using this algorithm are perfect on all data, the results tend to be good. This is related to the services available in the form of a convolutional layer on YOLO reducing downsample or reducing image dimensions by using anchor boxes, this algorithm can also improve accuracy
Komparasi Penilaian Kinerja Karyawan Dengan Menggunakan Pendekatan Pembelajaran Mesin Errissya Rasywir; Yessi Hartiwi; Yovi Pratama
JURIKOM (Jurnal Riset Komputer) Vol 6, No 4 (2019): Agustus 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.723 KB) | DOI: 10.30865/jurikom.v6i4.1328

Abstract

Performance evaluation is an activity to measure whether a worker is able to do his job in accordance with his duties and responsibilities. The results of the assessment will be utilized and evaluated by the management managing the workers. The reason for using machine learning in research is because of its advantages in learning about machines with high accuracy results. There has been a lot of machine learning that has been tested, both guided such as decision trees, neural networks, bayesian learning and non-guidance such as clustering, as well as genetic algorithms and ant colony algorithms. The algorithms chosen in this research are Naïve Bayes, Perceptron and Support Vector Machine (SVM). Naïve Bayes was chosen because of the reliability of results with simple steps from the type of learning with the concept of probability. Perceptron is known to be reliable from the types of neural network-based learning. SVM is a well-known algorithm that is able to find hyperplane values more accurately than other algorithms. The results of the study state that the highest accuracy value is generated by the Perceptron algorithm which is equal to 99.33%. Followed by SVM of 96.64% and naive bayes of 94.63% as a result of the use of training data. For the results of testing using 10-folds cross validation consistently under the training data testing.
Diagnosis Penyakit Tanaman Karet dengan Metode Fuzzy Mamdani Hendrawan Hendrawan; Abdul Haris; Errissya Rasywir; Yovi Pratama
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (649.729 KB) | DOI: 10.31294/p.v22i2.8909

Abstract

Like most plantation plants in general, rubber can be attacked by various diseases originating from fungi, pests, animals and even cancer cells. For that we need a method capable of diagnosing rubber disease. In previous research related to the diagnosis of plant diseases, among others, using the Dempster Shafer method, the Certainty factor method and forward chaining. This study developed an analysis of the results of the diagnosis of rubber plant disease using the Mamdany Fuzzy method. The choice of this method departs from research on fuzzy mamdany which states that the fuzzy mamdany method is able to resemble the intuitive way the human brain works. It is hoped that with this method, the diagnosis of rubber plant disease can help farmers detect symptoms earlier so that the productivity of rubber plantation products can be achieved. increased. This study used rubber plant disease data from the Jambi Provincial Plantation Office in Jambi City. From the results of calculations carried out in diagnosing rubber plant disease, as many as 161 rubber plant object data were equipped with 33 symptom identities and a diagnosis from plantation data, then tested 60 rubber plant data without a diagnostic label, we obtained an accuracy value of 81.28%. Likewise, testing by randomizing training data with Cross Validation obtained close results.
Analisis Statistik Pemilihan Bidang Skripsi Menggunakan Ekspectation Maximization Yovi Pratama
Jurnal Ilmiah Media Sisfo Vol 11 No 1 (2017): JURNAL ILMIAH MEDIA SISFO
Publisher : LPPM Universitas Dinamika Bangsa

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

Abstract

Pada sebuah perguruan tinggi jurusan ilmu komputer, mahasiswa dituntut untuk menerapkan apa yang mereka pelajari ke dalam sebuah implementasi atau penerapan pada bidang tertentu baik dalam bentuk format pembelajaran, analisis maupun berbentuk aplikasi, program atau sistem komputer sebagai syarat lulus (skripsi). Namun dengan banyaknya bidang yang dipelajari membuat mahasiswa bingung menentukan bidang yang akan diambil. Berdasarkan hal tersebut peneliti melakukan perekomendasian bidang skripsi menggunakan algoritma Expectation Maximization Clustering. Cluster yang dihasilkan berasal dari data kelompok mata kuliah terkait penelitian yang diambil dari Computer Science Curriculla yang diterbitkan oleh ACM dan IEEE. Dari data mata kuliah yang terkait bidang penelitian, peneliti mencocokan mata kuliah dengan kode mata kuliah yang terdapat pada program studi Teknik Informatika. Hasil dari penelitian ini membuktikan bahwa rekomendasi bidang Skripsi dengan menggunakan Expectation Maximization Clustering mampu memberi nilai rekomendasi terendah mencapai nilai 1 % dan nilai tertinggi 100 % serta rata-rata 67 % dari jumlah mahasiswa sebanyak 11.167 orang.
Penerapan Algoritma K-Means Pada Penyebaran Covid-19 Di Provinsi Jambi Reza Pahlevi; Muhammad Wahyu Prayogi; Errissya Rasywir; Yovi Pratama
Journal of Computer System and Informatics (JoSYC) Vol 4 No 1 (2022): November 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i1.2550

Abstract

The purpose of this study using the K-Means Cluster method is to determine the level of distribution of Covid-19 cases in the high, medium, and low categories in each region in Jambi Province. There are several aspects that can be measured such as population, population density, positive cases infected with Covid-19, recovered patients, and patients who died. The data collection method used is the documentation method in the form of secondary data obtained from the Jambi Provincial Government website. The data used were positive, recovered, and died and were analyzed using the WEKA application. From the results of research with the K-Means method using 3 clusters. Cluster 0 is a cluster with a high level of distribution category, which is in the city of Jambi. Cluster 1 is a cluster with a medium level distribution category consisting of Batanghari, Merangin, Muaro Jambi, Tanjab Timur. Cluster 2 is a cluster with a low-level distribution category consisting of Bungo, Kerinci, Sarolangun, Sungai Penuh, Tanjab Barat, Tebo.
Eksperimen Pengujian Optimizer dan Fungsi Aktivasi Pada Code Clone Detection dengan Pemanfaatan Deep Neural Network (DNN) Errissya Rasywir; Yovi Pratama; Fachruddin Fachruddin
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.1776

Abstract

The problem of similarity (similarity) of program code can be one solution to the plagiarism detection approach. Plagiarism raises a form of action and consequences of plagiarism itself if the source used is not open source. Plagiarism is an act of deception of the work of others without the knowledge of the original author, which violates a Copyright and Moral Rights. With the increasing amount of data and data complexity, deep learning provides solutions for predictive analytics, with increased processing capabilities and optimal processor utilization. Deep learning shows success and improves the classification model in this field. On the other hand, clone detection code with massive, varied and high-speed data volumes requires feature extraction. With the potential of deep learning to extract better features, deep learning techniques are suitable for code clone detection. For this reason, it is necessary to develop a clone detection code that can process data from a programming language by utilizing deep learning. Based on the results of experiments conducted on 100 PHP program code data files, experimented with several types of activation function and optimizer methods. The average value of the resulting accuracy is good. With a variety of activation functions that we use such as Relu, Linear, Sigmoid, Softmax, Tanh, Elu, Selu, Softplus, Softsign, hard, and sigmoid, as well as variations of the optimizer used are Adagrad, RMSProp, SGD, Adadelta, Adam, Adamax and Nadam , the best attribute selection is in the Selu function and the RMSProp optimizer. The number of epochs used is 1000, the number of neurons per layer is 500 and the best number of hidden layers is 10, the average accuracy is 0.900
Penerapan K-Means Untuk Clustering Kondisi Gizi Balita Pada Posyandu Candra Adi Rahmat; Hilda Permatasari; Errissya Rasywir; Yovi Pratama
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5142

Abstract

Malnutrition in children is a major public health problem in developing countries, including Indonesia. National data show that 36.8% of children under five years of age (toddlers) are stunted (short and very short, measured by height for age). To be able to know the nutritional condition of the toddler, can use analysis and a calculation method. In this study, the authors utilize an analysis and calculation of data, namely data mining. One of the techniques in data mining is clustering. K-Means Clustering is one of the algorithms in the Clustering technique in data mining. In this study the authors used as many as 20 data on toddlers. From the 20 data on toddlers, the authors determined the cluster center randomly as much as 3 data and resulted that, 4 toddlers were malnourished, 7 toddlers were well nourished, and 9 toddlers were obese.
Co-Authors Abdul Haris Abdul Harris Achpal Haddid Adelia Putri, Ananda Afrizal Nehemia Toscany Agus Siswanto Akbar Ramadhan Akwan Sunoto Alvito Widianto Amroni, Amroni Angelica, Felicia Anggraini, Dila Riski Anggy Utama Putri Annisa putri Anton Prayitno Arahmad Taupiq asih asmarani Bayu saputra Beni Irawan Borroek, Maria Rosario Bustami, M Irwan Cahyana Putra Pratama Candra Adi Rahmat Carenina, Babel Tio Chindra Saputra Defrin Azrian Desi Kisbianty, Desi Despita Meisak Dimas Pratama Dimas Yudha Prawira Dinata, Despan elvi yanti Emelia, Shinta Enjelina, Mia Errissya Rasywir Evan Albert Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin, Fachruddin farchan akbar Feranika, Ayu Fingki Lamhot Pasaribu fiqri ansyah Hartiwi, Yessi Hendrawan Hendrawan Hendrawan Hendrawan Hendrawan Hendrawan Hilda Permatasari Hussaein, Ahmad Ilham Adriansyah ilham permana Imelda Yose Indana Arum , Refi Irawan Irawan Irawan Irawan Irawan, Beni Istoningtyas, Marrylinteri Janu Hadi Susilo Jopi Mariyanto Julia Triani khalil gibran ahmad Kholil Ikhsan Luthfi Rifky M Fikrul Hakimi M Reihan Al Fajri M.Rizky Wijaya Manyu, Dimas Abi Maria Rosario Borroek Marrylinteri Istoningtyas Marrylinteri Istoningtyas Marrylinteri Istoningtyas Marshal` Koko Anand masgo Maulana Qaedi Aufar Mayang Ruza Muhammad Afif Dzaky Khairullah Muhammad Diemas Mahendra Muhammad Irwan Bustami Muhammad Ismail Muhammad Riza Pahlevi MUHAMMAD SURYA Muhammad Wahyu Prayogi Muhammad Zulfi Tisna Tama Mumtaz Ilham S Mumtaz Ilham Syafatullah NAIBAHO, RONALD Najmul Laila Naldi Irfan Nanda Ghina Nia Azzahra Nur Aini Nurhadi Nurhadi Pahlevi, M. Riza Pahlevi, M.Riza Pareza Alam Jusia Pareza Alam Jusia, Pareza Alam Ramadhan Saputra, Tri Ramadhani, Utari Reza Pahlevi Rezky Pramudia, Muhammad Riki Bayu Andhika Rio Ferdinand ROBY SETIAWAN Rohaini, Eni Rosario B, Maria Rosario, Maria Rudolf Sinaga Sandi Pramadi Santoso Saparudin, Saparudin Sariyani SIKA, XAVERIUS Steven Ie Sudewo, Raden Tio Putra Sutoyo, Mochammad Arief Hermawan Suyanti taupiq, Arahmad Toscany, Afrizal Verna Anatasya, Rara Verwin Juniansyah virginia casanova andiko andiko Warcita Warcita WILLY RIYADI Xaverius Sika Yaasin, Muhammad Yanti, Elvi Yessi Hartiwi Yessi Hartiwi Yoga Rizki Yuga Pramudya Zahlan Nugraha Zulia, Restutik