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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) International Journal of Computer and Information System (IJCIS) Kreator Journal of Society Innovation and Development (JSID)
Riyono, Dwi
Politeknik Negeri Media Kreatif
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Physics Social Sciences Other

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CONTROL OF PACKAGING PRINT QUALITY WITH AN INTEGRATED PRODUCTION FLOW SYSTEM IN PREPRESS Tri Cahyadi; Adi Susanto; Dwi Riyono
Kreator Vol 6, No 1 (2019): Kreator
Publisher : Politeknik Negeri Media Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46961/kreator.v2i1.283

Abstract

The integration of the production flow on precast is the initial requirement in determining the results that will be obtained on a graphic product, especially on the resulting color. The goal is to produce accurate prints with the processed data on a computer device. In the data process conducted using interview and observation methods. Interviews were conducted with resource persons who were experts in their fields and observations made were direct practice guided by experts. The results obtained from the data study carried out are in the form of a file format that is useful for integrating work system flows in the precast section of a graphics industry.Keywords— Control, Integrated Systems, Graphics Technology
The Design Motif of Batik Grafika Indonesia (Batik Pusgrafin) in National Batik Diversity Through Application Subject Nirmana Dwimatra-Trimatra Sri Herti, Dayu; Riyono, Dwi; Triana, Eka; David Mongkau, Immanuel Ronald
JOURNAL OF SOCIETY INNOVATION AND DEVELOPMENT Vol 5 No 1 (2023): Journal of Society Innovation and Development
Publisher : Winaya Inspirasi Nusantara Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63924/jsid.v5i1.25

Abstract

This research is a continuation of the dissertation on 'Transformation of the Indonesian Graphics Center/Pusgrafin in the Renewal of Educational Media in Indonesia, 1969–2008'. As a government institution in the field of graphics, one of its tasks and functions is to develop non-formal education through graphic training throughout Indonesia. This research aims to memorize pusgrafin as a renewal of educational media through the concept of creating pusgrafin batik motifs or Indonesian graphic batik so that it can enrich the diversity of batik motifs in Indonesia. Motifs with the philosophy of graphical batik motifs from local wisdom become one of the national batik diversities and support the program to increase the creative industry in Indonesia, both in books, journals, and scientific studies. The novelty of this research is that the existence of Indonesian graphical batik motifs as the embodiment of pusgrafin as one of the media to display a new identity or characteristics of a product will be able to contribute value to regional socio-economic growth, especially in the tourism and creative industry sectors. The locus at Politeknik Negeri Media Kreatif (PoliMedia Kreatif) is one of the vocational education institutions and the only state polytechnic in DKI Jakarta Province. As a revitalization of Pusgrafin, it has a role in developing various superior products, both produced by each study program and through collaboration between study programs. This research uses an art history/historiography research method with a methodology of social science, culture, and creative industry approaches. This research uses the subject matter of Indonesian Batik Grafika motif design in advanced courses: two-dimensional nirmana and three-dimensional nirmana. The results of batik motif design in the future will be applied to fashion products, especially batik clothing and merchandise/gimmicks.
Performance Comparison K-Nearest Neighbors and Random Forest on Predicting The Performance New Polimedia Student Admissions Riyono, Dwi; Mawardi, Cholid
International Journal of Computer and Information System (IJCIS) Vol 6, No 2 (2025): IJCIS : Vol 6 - Issue 2 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i2.237

Abstract

New student admissions are at the forefront of the school's operational process. the success of each college's input stems from this. Polimedia always conducts new student admissions every year with various strategies used. Polimedia has 23 study programmes that can enable it to move in the creative industry that can be utilised by the community. in this study, a strategy using a prediction algorithm is used to be able to see the possible opportunities that occur if implemented in the coming year. with a dataset of 3738 data received by new students, an analysis will be carried out on prospective students who have re-registered or who have not re-registered. The classification model with 2 classes will be used. by conducting a data analysis process using exploratory data analysis (EDA) and also performing data cleansing so that the data modelling process runs well. The method used uses the main model of K-Nearest Neighbors by comparing with other machine learning models such as decision tree and random forest. It is expected that this research can produce high accuracy values 86.90% with powerful machine learning model comparisons. This research is also expected to be a reference for other studies that also conduct performance testing processes with machine learning models using various objects.
COMPARATIVE PERFORMANCE OF SEQUENTIAL CNN AND PRE-TRAINED LEARNING FOR 3D PRINTING DEFECT CLASSIFICATION Riyono, Dwi; Mawardi, Cholid; Herianto
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7337

Abstract

3D Printing is currently needed in various industries, including education in terms of research development. In this study, researchers classify 3D printing defect images to recognize images that are difficult to see with the naked eye. With limited observation, an image classification method is needed to help users detect defects in the printing process with a Deep Learning model. The printing process uses PLA and ABS-based filament materials, which are mostly used in 3D Printing objects with fused deposition modeling (FDM)-based 3D Printer machines. In this study, there are several stages, including data augmentation, model development using sequential CNN, pre-trained CNN based with pre-trained models, namely VGG-16 and VGG-19, training, validation, and model evaluation. The dataset taken for training is 1557, with a ratio of 80 percent training and 20 percent validation between defective and non-defective objects. The results of this study have a good accuracy value on Sequential CNN with an accuracy of 99.68% compared to pre-trained CNN models, namely VGG-16 and VGG-19. The classification results are also compared with other additive manufacturing classification methods with different machines and materials such as metal and 3D Food Printing which are measured based on classification model optimization analysis
Co-Authors Adi Susanto Cholid Mawardi David Mongkau, Immanuel Ronald Dayu Sri Herti Eka Triana, Eka Herianto Tri Cahyadi