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All Journal Jurnal Teknoin SCIENCE TECH: Jurnal Ilmiah Ilmu Pengetahuan dan Teknologi VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Jurnal Infomedia JURIKOM (Jurnal Riset Komputer) JURTEKSI Building of Informatics, Technology and Science JATI (Jurnal Mahasiswa Teknik Informatika) Information System Journal (INFOS) J-Intech (Journal of Information and Technology) Journal of Practical Computer Science (JPCS) EXPLORE Explore Jurnal Pengabdian Masyarakat Inovasi Indonesia Journal of Information Technology
Arifiyanto Hadinegoro, Arifiyanto
Universitas Amikom Yogyakarta, Yogyakarta
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences

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Journal : Building of Informatics, Technology and Science

 1 
Pengaruh HSV Pada Pengolahan Citra Untuk Kematangan Buah Cabai Hadinegoro, Arifiyanto; Rizaldilhi, Dicky Andhika
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (780.157 KB) | DOI: 10.47065/bits.v3i3.1020

Abstract

Image or image recognition has quite complex stages so that the computer is able to recognize what objects to identify, there are several stages used in the image processing process, image extraction data input and image classification, this study will examine the extent to which the algorithm for extraction have an influence on the final classification results. This study uses the image of chili as a test material and the results of the test are the introduction of chili with 4 levels, ripe, half cooked, raw and rotten. This study also uses tools to perform the image recognition process. The image recognition method used in this study is Hue Saturation Value (HSV) Gray Level Co-occurrence Matrix (GLCM) and Learning Vector Quantization (LVQ3) for classification, in the process it will be tested. With 2 image recognition scenarios, the first method uses GLCM and LVQ3, the second scenario uses HSV GLCM and LVQ3. The results of this study are to see how much influence HSV has on the digital image recognition process of chili, the extraction results using GLCM extraction LVQ3 classification is 59.58%, and the results of LVQ3 classification using HSV and GLCM extraction yields 93.58%. In conclusion, the HSV extraction method provides an additional 34% accuracy compared to using only GLCM as the extraction method
Sistem Rekomendasi Content-based Filtering Menggunakan TF-IDF Vector Similarity Untuk Rekomendasi Artikel Berita Huda, Arif Akbarul; Fajarudin, Rohmad; Hadinegoro, Arifiyanto
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2511

Abstract

The population of active students in the Informatics Bachelor Program, Universitas Amikom Yogyakarta, in the odd semester of 2021 is 3,870. Efforts to track interest in the three concentration options were carried out early on through article literacy recommendations. Various articles are produced continuously and provided on an ongoing basis to students. However, the many articles offered daily make students overwhelmed and tend to choose articles that do not match what they want. To help solve this problem, recommender system is developed. A recommender system helps to estimate the prediction value or relevancy of an article and create a ranking according to user's taste. Content-based Filtering technique is used in this research. Using the dataset from Kabar Informatika news portal of University of Amikom Yogyakarta, the developed Content-based Filtering Recommendation System is able to produce Recall@5 score at around 73% and Recall@10 at around 80%.
Penerapan Logits Processing Pada Teknologi Transformer untuk Penciptaan Melodi Berbentuk Notasi ABC dalam Pengembangan Game Indie Dhiaulhaq, Muhammad Faishal Ali; Huda, Arif Akbarul; Hadinegoro, Arifiyanto
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6642

Abstract

Generative Artificial Intelligence (Gen AI) technology is increasingly being used by creative professionals, including musicians and game developers. Many game developers now turn to open or paid music assets, but the variety of options is usually quite limited. This research aims to assist game developers in generating music assets in ABC notation format. The research methods include data collection in the form of ABC notation, data processing, model development, and metric evaluation. The data was collected by extracting ABC notation along with the characteristic musical components of each item. Data processing involved handling missing values and feature selection, while data preparation included labeling and tokenization. The model used was GPT-2 based on the Transformer architecture, pretrained on a general dataset. Integration of the model with ABC notation data was enhanced using Logits Processing to improve output control. The evaluation results show that Transformer technology can generate pitch patterns consistent with the validation data, with the EMD values concentrated in the range of 1.0–1.5 and an average of 1.60. Although there are some outliers and differences in pitch distribution between the validation data and generated results, the Horror genre with a Joyful mood and Excitement emotion achieved the highest combined fitness score of 0.528. The model still requires further refinement to produce more consistent pitch distributions. This research demonstrates the potential of Transformer technology in generating music assets for games, but further studies are needed to improve accuracy and consistency in the results.
Co-Authors Adi Saputro, Johan Agung Pambudi Anggit Dwi Hartanto Arif Akbarul Huda Arya Yudistira Dhiaulhaq, Muhammad Faishal Ali Drajat Indah Mawarni Fajarudin, Rohmad Faris Fathahillah Herman Fikri, Muhammad Ainul Hafizh, Saifan Hasif Priyambudi Hendrawan, Mohammad Yan Fikri Huda, Amirudin Khorul Icha Widya Pratiwi Ikramillah, Syauqi Khairan AR Kusuma Wardana, Raka Muhamad Syah Reza Muhamad Sysah Reza Nazaruddin Ahmad Ningrum, Fauzia Anis Sekar NUR AINI Nuri Cahyono Pratiwi, Icha Widya Rahim, Abd. Mizwar A. Rana Sulthanah Rizaldilhi, Dicky Andhika Saifan Hafizh Sasongko, Theopilus Bayu Siti Fatonah Subektiningsih Subektiningsih Sulthanah, Rana Teguh Wibowo Uyock Anggoro Saputro Yuana, Kumara Ari