Article Per Year (5 Year)
p-Index From 2019 - 2024
6.533
P-Index
This Author published in this journals
All Journal Perfecting a Video Game with Game Metrics Annual Research Seminar Paradigma JURNAL MEDIA INFORMATIKA BUDIDARMA PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer 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 Journal of Applied Business and Technology Jurnal Informatika dan Rekayasa Komputer Jurnal Manajemen Teknologi dan Sistem Informasi PROCEEDING OF INTERNATIONAL CONFERENCE ON BUSINESS MANAGEMENT AND ACCOUNTING Bulletin of Informatics and Data Science
Errissya Rasywir
Universitas Dinamika Bangsa
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Social Sciences Veterinary Other

Published : 53 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 8 Documents
Search
Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

 1 
Sistem Manajemen Absensi dengan Fitur Pengenalan Wajah dan GPS Menggunakan YOLO pada Platform Android Hartiwi, Yessi; Rasywir, Errissya; Pratama, Yovi; Jusia, Pareza Alam
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.v4i4.2522

Abstract

This study offers an attendance system that can be run with the Global Positioning System (GPS) feature to automatically check the location of the face owner. Recently, the YOLO algorithm is the world's most popular method of facial recognition. Currently the You Only Look Once (YOLO) algorithm toolbox has been provided in various programming language platforms for use. The system we offer is also able to check the position or whereabouts of objects using Global Positioning System (GPS) technology. The results of this test obtained an accuracy of 0.93435 and the lowest was within the range of 93%, while the average accuracy values were 93.26%. Of the 20 assessment data carried out by the Attendance Management System with Face Recognition and GPS Features using YOLO on the Android Platform. The evaluation of the accuracy of student attendance is expected to support the process of academic activities on campus. In addition, this product is expected to be able to assist management who require evaluation results as well as an effort to improve business processes in an agency in order to improve their performance. This research proves that the use of the tool library with the You Only Look Once (YOLO) algorithm is the most popular method in the world of facial recognition and is proven to be tough and very good at this time.
Pengukuran Perangkat Lunak Untuk Effort Estimation Dengan Teknik Pembelajaran Mesin Borroek, Maria Rosario; Rasywir, Errissya; Pratama, Yovi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 2 (2020): April 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i2.2083

Abstract

Software effort estimation is to estimate the amount of resources needed in developing the software. For that software effort estimation is important so need to see the effect of software measurement to software effort estimation which is done by machine learning technique. Based on this the researcher tries to build a system capable of measuring software. In this study experiments on software measurement techniques (FPA, FPA with Sugeno fuzzy and FPA with mamdani fuzzy). The three types of techniques are compared with the three project data for further software effort estimation. For evaluation, this study evaluates using the assessment of the Developeras Analyst of the Project. The results of the study that the LOC and effort values on a similar system can be different if calculated by the use of FPA, Fam Mamdany fuzzy and FPA Sugeno Fuzzy. The highest LOC and Effort values are generated by FPA Mamdany Fuzzy on Project DUMAS POLDA SUMSEL. While the lowest effort value and lowest LOC produced by FPA Sugeno Fuzzy. This can be traced from the calculation mechanisms performed by FPA Sugeno Fuzzy where this method does not count the input, output, file, query and interface values at all. The calculation of FPA Sugeno fuzzy is done by roughly judging only from the difficulty of making the system. To raise the price of a project in order to be rewarded higher FAT methods Mamdani Fuzzy is recommended
Analisis Usability Pada Implementasi Sistem Pengelolaan Keuangan Masjid Menggunakan USE Questionnaire Fachruddin, Fachruddin; Pahlevi, Muhammad Riza; Ismail, Muhammad; Rasywir, Errissya; Pratama, Yovi
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.v4i4.2520

Abstract

The financial management of mosques with the use of technology can make financial data more organized, filed neatly and transparently. Moreover, financial reports are data that must be accounted for in order to be trusted by the public. However, it is necessary to know how good a financial management system is. By using the USE Questionnaire we can find out that an application can still run in accordance with applicable business processes without changing the data flow and some rules and reports that have been running previously. The need to analyze usability testing on financial applications is to support automatic and computerized mosque financial management and is considered very good in user testing. This study resulted in an average rating for the "Usefulness" instrument, the "Ease of Use" instrument, the "Ease of Learning and Satisfaction" instrument, which scored well above 93%. The “Usefulness” instrument received an average of 99.00%, the “Ease of Use” instrument received an average of 94.55%, the “Ease of Learning and Satisfaction” instrument received an average of 93.82%. Thus it can be stated that the mosque financial application built for mosque management is able to meet good criteria in the rules of the USE Questionnaire method.
Pengujian Algoritma MTCNN (Multi-task Cascaded Convolutional Neural Network) untuk Sistem Pengenalan Wajah Yovi Pratama; Marrylinteri Istoningtyas; Errissya Rasywir
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 3 (2019): Juli 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i3.1324

Abstract

Measurement of facial similarity or checking similarity is done using features. The algorithm for describing the most up-to-date and best face features for generating features is Deep Convolutional Neural Network (DCNNs). Based on this, this study uses MTCNN (Multi-task Cascaded Convolutional Neural Network) as one variation of the DCNN method. In this research, we built a research system to test results with javascript. Given the many needs that are based on mobile or can be run on a smartphone. One of them is to support the absent feature that is used in a mobile manner such as the reporting system of sales and marketing performance or members of the police personnel who normally work on a mobile basis. From the results of the tests carried out automatically using several variation models testing the image of the Aberdeen dataset as many as 60 images from 30 different people used in the face recognition research system using MTCNN with influencing image parameters such as lighting variations, object position variations, then the position taken and expression face on the object image, the research system managed to do face recognition by 100%. Thus, true positive values are equal to the amount of data tested and zero negative true values.
Evaluasi Pembangunan Sistem Pakar Penyakit Tanaman Sawit dengan Metode Deep Neural Network (DNN) Errissya Rasywir; Rudolf Sinaga; 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.v4i4.2518

Abstract

The limited knowledge of oil palm farmers on oil palm pests and diseases is related to oil palm productivity. Jambi Province is one of the largest oil palm producers on the island of Sumatra. Usually, to find out the types of pests and diseases in oil palm in the field, farmers need knowledge like that of experts about oil palm diseases. However, the limitation of facilities and capabilities becomes an obstacle. This study offers an expert system to analyze oil palm disease using deep learning. This method is deep learning with excellent accuracy. Various recent studies using DNN state that the classification accuracy results are very good. The data used for the expert system using the DNN algorithm comes from oil palm diagnostic data from the Jambi Provincial Plantation Office. After the oil palm disease diagnosis data is trained, the training data model will be stored for the oil palm disease diagnosis testing process. With a total of 11 classes (Leaf Spot Disease, Anthrox Leaf Blight, Leaf Rust Disease, Leaf Canopy Disease, Bud Rot Disease, Root Rot Disease, Fire Caterpillar or Setora Nitens, Red Mites or Oligonychus, Horn Beetle or Orycte rhinoceros, Bunch Borer Fruits and Nematodes Rhadinaphelenchus Cocophilus), with test variables including the number of classes, TP, TN, FP, FN, precision, recall, F1-score, accuracy, and Missclassificaion rate. The highest accuracy value was 0.88, while the lowest value was 0.83 and the average accuracy was 0.86. This shows that the results of expert system diagnosis on oil palm disease data with DNN are quite good.
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.
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 Abdurrahman Ade Saputra Akwan Sunoto Anita Anita Nurjanah Annisa putri Anton Prayitno Arya Atmanegara asih asmarani Babel Tio Carenina Bayu saputra Betantiyo Prayatna Borroek, Maria Rosario Briyan Chairullah Candra Adi Rahmat Clara Zuliani Syahputri Defrin Azrian Desi Kisbianty Despita Meisak desy ayu ramadhanty Dila Riski Anggraini Dimas Pratama Dodo Zaenal Abidin Elsa Charolina L Siantar eni rohaini Eni Rohaini Evan Albert Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin Fachruddin, Fachruddin farchan akbar Feranika, Ayu Fernando Fernando fiqri ansyah Fradea Novi Ramadhayanti Hani Prastiwi Hartiwi, Yessi Hendrawan Hendrawan Hendrawan Hendrawan Hendrawan Hendrawan Hilda Permatasari Ilham Adriansyah Ilham Fahrozi ilham permana Imelda Yose Iqbal Pradibya Irawan Irawan Irawan, Beni Jasmir Jasmir Jeny Pricilia Jopi Mariyanto khalil gibran ahmad Kholil Ikhsan Li Sensia Rahmawati Lies Aryani Luthfi Rifky M.Rizky Wijaya Macharani Raschintasofi Maliyatul Khasanah Maria Rosario Borroek Marrylinteri Istoningtyas Marrylinteri Istoningtyas Marrylinteri Istoningtyas Mayang Ruza Migi Sulistiono Muhammad David Adrilyan Muhammad Diemas Mahendra Muhammad Ismail Muhammad Ismail Muhammad Riza Pahlevi Muhammad Satria Mubin Muhammad Wahyu Prayogi Mulyadi Mumtaz Ilham S Mumtaz Ilham Syafatullah Muttaqin Nabila Khumairo Najmul Laila Nanda Ghina Nasrul Ahlunaza Nilu Widyawati Nungky Septia Kurnicova Nur Aini Nurul Aulia Pareza Alam Jusia Pareza Alam Jusia Pareza Alam Jusia, Pareza Alam Renita Syafitri Reza Pahlevi Rio Ferdinand Rts CiptaNingsi Rudolf Sinaga Sandi Pramadi Saparudin Saparudin Saparudin Saparudin Satria Oldie Versileno Sri Wahyuni Nainggolan Sulistia Ramadhani Tasya Basalia Sihombing Tedy Hardiyanto Tondy Maulana Tambunan Verwin Juniansyah virginia casanova andiko andiko Wahid Hasyim Wahyudi Nasutioni Yessi Hartiwi Yessi Hartiwi Yoga Rizki Yovi Pratama Yuga Pramudya Zahlan Nugraha