Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

2.766

P-Index

This Author published in this journals

All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Ilmu Komputer Transmisi: Jurnal Ilmiah Teknik Elektro Jurnal INKOM Proceedings of KNASTIK Bulletin of Electrical Engineering and Informatics JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal technoscientia Jurnal Teknologi Prosiding SNATIKA Vol 01 (2011) JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Seminar Nasional Informatika (SEMNASIF) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Proceeding of the Electrical Engineering Computer Science and Informatics Journal of Information Technology and Computer Science Emerging Science Journal IJID (International Journal on Informatics for Development) CCIT (Creative Communication and Innovative Technology) Journal JISKa (Jurnal Informatika Sunan Kalijaga) JURNAL TEKNOLOGI TECHNOSCIENTIA Journal of Applied Data Sciences Makara Journal of Science Jurnal Informatika dan Multimedia JEECS (Journal of Electrical Engineering and Computer Sciences) Madani: Multidisciplinary Scientific Journal

Retantyo Wardoyo

Universitas Gadjah Mada

Author-ID : 359720

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 69 Documents Claim Missing Document

Claim Missing Document

Articles

3 4 5 6 7

3D Simulation of Plant Growth Modeling Using Neuro-Fuzzy, Lindenmayer System, and Turtle Geometry Wiwiet Herulambang; Retantyo Wardoyo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 1 No. 2 (2016): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Applications that are able to predict plants growth patterns as a function of the nutrients obtained from fertilization pattern, is very useful in agriculture. The purpose of this study was to design and build a system of plants growth simulation models with Neuro-fuzzy method, then visualized by methods Lindenmayer system represented by three-dimensional use of Turtle Geometry. As the object of research is Soybean (Glycine max (L.) Merrill). Modeling parameters is long growth trunk / branches (L), a wide cross section of the leaf (W), and branch growth (B), as a function of changes in the fertilizing elements Nitrogen (N), Phosphate (P) and potassium (K). Modeling done on the vegetative phase of the soybean crop.First step is the modeling output L-W-B as a function of changes in the values of NPK using neurofuzzy (ANFIS). The final step is to combine plant growth pattern parameters (L-W-B) and L-system strings into the visualization process plant structure using Turtle Geometry.The test results on the system to grow plants pattern proves that ANFIS method is quite adaptive to variation of NPK value changes, and able to predict the output value L, W, and B. The final result of string-set of L-system and also it's visualization by Turtle Geometry, has proven to be influenced by variations in the composition of NPK values. Overall, the system has been running as expected.

Pattern Recognition of Signature Verification Using Cellular Automata Methods Adiananda; Retantyo Wardoyo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 1 No. 2 (2016): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

A pattern recognition technique in the field of machine learning and can be defined as "the act of taking raw data and act upon data classification". Much research has been done on the topic of pattern recognition using a variety of methods one of which is by using the cellular automata. In this study used cellular automata method for finding and extracting characteristics of an image of the signature and realized in a pattern recognition software that can verify the authenticity of the signature image by using cellular automata method for the extraction process characteristics. In this study used data 57 respondents with 6 signatures used as a reference image. Three pieces of the original signature image and 10 pieces of counterfeit signature image is used as the test images (query). From the testing that has been done precision 88.30%, recall 65.37% and accuracy 71.31%.

Face recognition for occluded face with mask region convolutional neural network and fully convolutional network: a literature review Rahmat Budiarsa; Retantyo Wardoyo; Aina Musdholifah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5662-5673

Face recognition technology has been used in many ways, such as in the authentication and identification process. The object raised is a piece of face image that does not have complete facial information (occluded face), it can be due to acquisition from a different point of view or shooting a face from a different angle. This object was raised because the object can affect the detection and identification performance of the face image as a whole. Deep leaning method can be used to solve face recognition problems. In previous research, more focused on face detection and recognition based on resolution, and detection of face. Mask region convolutional neural network (mask R-CNN) method still has deficiency in the segmentation section which results in a decrease in the accuracy of face identification with incomplete face information objects. The segmentation used in mask R-CNN is fully convolutional network (FCN). In this research, exploration and modification of many FCN parameters will be carried out using the CNN backbone pooling layer, and modification of mask R-CNN for face identification, besides that, modifications will be made to the bounding box regressor. it is expected that the modification results can provide the best recommendations based on accuracy.

Survey Model-Model Pencarian Informasi Rekam Medik Elektronik Muhammad Mustakim; Retantyo Wardoyo
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 3 No. 3 (2019): Januari 2019
Publisher : UIN Sunan Kalijaga Yogyakarta

Pertumbuhan jumlah data rekam medik yang pesat, menjadi masalah tersediri yang harus diantisipasi. Untuk menangani fenomena information overload dalam informasi rekam medis, perlu studi yang mendalam untuk dapat mengembangkan model filtering informasi rekam medik yang secara efektif mendukung peningkatan kualitas rekomendasi proses pencarian informasi. Berbagai penelitian terkait pencarian informasi medis telah banyak dilakukan, diantaranya mengembangkan penelitian dengan konsentrasi pada kebaruan dan keberagaman, menggunakan fuzzy ontology, berbasis factor tensor, memepertimbangkan niatan/intention pengguna ketika melakukan pencarian serta pendekatan dengan menggabungkan pencarian berbasis frasa dengan alat pemetaan konsep yang ada menggunakan MetaMap dan sumber data ULMS Metathesaurus.

PERSONALIZATION SISTEM E-LEARNING BERBASIS ONTOLOGY Suteja, Bernard Renaldy; Guritno, Suryo; Wardoyo, Retantyo; Ashari, Ahmad
Makara Journal of Science Vol. 14, No. 2
Publisher : UI Scholars Hub

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

A Mamdani FIS to Monitor Programmer Performance on GitHub Purba, Susi Eva Maria; Wardoyo, Retantyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 18, No 2 (2024): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.88575

A collaborative activity used to accomplish shared objectives is teamwork. It is essential to know how unequal contributions can inhibit team members' chances to give their all in achieving these objectives. It will be necessary to manage resources in this joint approach. Monitoring each team member’s performance in one technique to do this. In previous research, performance measurement was designed using Prometer with several parameters, utilizing the crisp set at each stage. This study developed the method by adding variables and utilizing fuzzy logic, which can consider the membership value for each value involved. The membership value considered for each variable is expected to provide a significant assessment of each team working on developing software projects using the GitHub platform. The results will be monitored based on the involvement of each collaborator in project work through the data recorded in the pull requests, issues, commits, additions code, and deletion code variables. The results obtained by utilizing the variables and several rules that have been designed with the Mamdani implication function are then compared with the observations obtained by the Project Manager so that an accuracy value of 86.67% is accepted for the use of inclusive and exclusive rules (operand AND).

Fine tuning attribute weighted naïve Bayes model for detecting anxiety disorder levels of online gamers Latubessy, Anastasya; Wardoyo, Retantyo; Musdholifah, Aina; Kusrohmaniah, Sri
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3277-3286

This research applies the fine tuning attribute weighted naïve Bayes (FTAWNB) model using ordinal data. It is known that in previous research, the FTAWNB model outperformed its competitors on the dataset used. However, the FTAWNB model has not been applied in the mental health domain that uses ordinal data. Therefore, this research used the anxiety gamers dataset to test the fine-tuning attribute weighted Naïve Bayes (FTAWNB) model. Anxiety disorders are mental health disorders that can indicate the emergence of a gaming disorder. Gamers can experience anxiety disorders classified into four classes, namely minimal, mild, moderate, and severe anxiety. Then compare the results by FTAWNB obtained with three other naïve Bayes algorithms, namely Gaussian naïve Bayes, multinomial naïve Bayes, and categorical naïve Bayes, using the same dataset. Model performance is measured based on accuracy, precision, recall, and processing time. The test results show that the FTAWNB outperforms the other three models' accuracy, precision, and recall, with an accuracy value of 99.22%. While the accuracy of Gaussian NB is 91.132%, Categorical is 91.592%, and multinomial naïve Bayes is 61.104%. However, the FTAWNB takes slightly longer than the other three models' processing time. The FTAWNB takes 0.07 seconds to build the model and 0.05 seconds to test the model on training data.

Face recognition with occluded face using improve intersection over union of region proposal network on Mask region convolutional neural network Budiarsa, Rahmat; Wardoyo, Retantyo; Musdholifah, Aina
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3256-3265

Face recognition entails detecting and identifying facial attributes. Mask region convolutional neural network (R-CNN) method is a prominent approach, while prior research predominantly delved into refining loss functions and perfecting object and face detection, recognizing, and identifying faces using imperfect data remained relatively unexplored. This study focuses on an occluded dataset comprising Indonesian faces, wherein 'occluded' denotes facial data that lacks complete visibility-encompassing instances where objects obscure faces or are partially cropped. This investigation involves a deliberate experiment that tailors the intersection over union (IoU) of the region proposal network (RPN) to suit the nuances of occluded Indonesian faces, thereby augmenting accuracy in recognition and segmentation tasks. The innovation IoU in the strategic utilization of Anchors, which involves the exclusion of anchors falling beyond the image borders to optimize computational efficiency. The outcomes of this research are striking; it showcases a remarkable 14.75%, 10.9%, and 12.97% surge based on mean average precision (mAP), mean average recall (mAR), and F1-Scores compared to the conventional Mask R-CNN approach. Notably, our proposed model elevates the average accuracy by 10% to 15% and decreases running time by 21%, a noteworthy enhancement compared to the preceding model. This progress is substantiated by validation utilizing 300 instances dataset, reinforcing the robustness of our approach.

Feature selection based on chi-square and ant colony optimization for multi-label classification Widians, Joan Angelina; Wardoyo, Retantyo; Hartati, Sri
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3303-3312

Text classification is widely used in organizations with large databases and digital documents. In text classification, there are many features, most of which are redundant. High-dimensional features impact multi-label classification performance. Feature selection is a data processing technique that can overcome this problem. Feature selection techniques have two major approaches: filter and wrapper. This paper proposes a hybrid filter-wrapper technique combining two algorithms: Chi-square (CS) and ant colony optimization (ACO). In the first stage, CS is used to reduce the number of irrelevant features. The ACO method is in the second stage. The ACO is applied to select the efficient features and improve classifier performance. The experiment results show that CS-ACO, CS-grey wolf optimizer (GWO), CS, and without feature selection (FS) have a micro F1-score based multinomial naïve Bayes classifier including 80%, 79.75%, 79.64% and 77.78%. The result indicates that the CS-ACO algorithm is suitable for solving multi-label classification problems.

Classification of clove types using convolution neural network algorithm with optimizing hyperparamters Tempola, Firman; Wardoyo, Retantyo; Musdholifah, Aina; Rosihan, Rosihan; Sumaryanti, Lilik
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5533

This study uses clove imagery by classifying it according to ISO 2254-2004 standards: whole, headless, and mother clove. This type of clove will affect the quality and economic value when it has been dried. For this reason, it is necessary to take a first step to control cloves' quality. One way is to classify it from the start. This research will utilize the convolution neural network algorithm and compare it with model transfer learning and modified VGG16 architecture on clove images. In addition, research is also looking for the most optimal hyperparameter. The results of this study indicate that the application of convolution neural network (CNN) to clove images obtains an accuracy value of 84% using a hyperparameter of 50 epochs, a learning rate of 0.001, and a batch size of 16. Meanwhile, for the application of transfer learning VGG16, Resnet50, MobileNetV2, InceptionV3, DensetNet151, and modified VGG16 have respectively each of the highest accuracy including 95.70%, 76.15%, 96.89%, 98.07%, 98.96%, and 99.11%.

Co-Authors Abdul Wahid Adiananda Adiananda Agus Harjoko Ahmad Ashari Ahmad Asharit Aina Musdholifah Aina Musdholifah Albert Dian Sano Anastasya Latubessy Andeka Rocky Tanaamah Andika Kurnia Adi Pradana Andriyani, Widyastuti Anny Kartika Sari Arief Kelik Nugroho, Arief Kelik Azhari Azhari Azhari Azhari Azhari Subanar Bambang Sugiantoro Bambang Sugiantoro Bangun Wijayanto Bernard Renaldy Suteja Christian Dwi Suhendra Clara Hetty Primasari Danang Lelono Decky Hendarsyah Desyandri Desyandri Djemari Mardapi Doni Setyawan E. Elsa Herdiana Murhandarwati Edhy Sutanta (Jurusan Teknik Informatika IST AKPRIND Yogyakarta) Edi Winarko Edi Winarko Enny Itje Sela Gede Angga Pradipta, Gede Angga Hananto, Andhika Rafi Hardyanto Soebono Herri Setiawan Herri Setiawan I Made Agus Wirawan I Made Agus Wirawan Ida Ayu Putu Sri Widnyani Istiyanto, Jazi Eko Jazi Eko Istiyanto Jazi Eko Istiyanto Jazi Eko Istiyanto Joan Angelina Widians, Joan Angelina Khabib Mustofa Khairunnisa Khairunnisa Kusrini Kusrini Lausu, Suwandi Lilik Sumaryanti M Mustakim M.Cs S.Kom I Made Agus Wirawan . Moh Edi Wibowo Muhamad Munawar Yusro Muhammad Fakhrurrifqi Muhammad Mukharir Munakhir Mudjosemedi Mustakim, M Nola Ritha NUR HASANAH Peggi Sri Astuti Pratama, Kharis Suryandaru Purba, Susi Eva Maria Purwo Santoso Putri Elfa Mas`udia Rahman Erama Rahmat Budiarsa Ramos Somya Rika Rosnelly Rosa Delima Rosihan Rosihan, Rosihan Santoso, Purwo Silmina, Esi Putri Sri Andayani Sri Hartati Sri Hartati Sri Hartati Sri Hartati Sri Kusrohmaniah, Sri Sri Kusumadewi Sri Mulyana Subahar, Subahar subanar subanar Suryo Guritno Suryo Guritno Suryo Guritno Tempola, Firman Tenia Wahyuningrum Wenty Dwi Yuniarti, Wenty Dwi Wibowo, Moh Edi Winarko, Edi Wiwiet Herulambang Yayi Suryo Prabandari

Title

Found 69 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 69 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 69 Documents
Search