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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) JURNAL ISTEK Computer Science and Information Technologies Jurnal Algoritma
Taufik, Ichsan
UIN Sunan Gunung Djati Bandung
Computer Science & IT Engineering

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Breakdown film script using parsing algorithm Agung Wahana; Diena Rauda Ramdania; Dhanis Al Ghifari; Ichsan Taufik; Faiz M. Kaffah; Yana Aditia Gerhana
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14849

Abstract

Breakdown script is a breakdown of the scenario into parts that describe each detail of the scene for shooting. The scenario is broken down into more detailed parts using the parsing algorithm. The film script used is a script in Bahasa Indonesia. The process starts from the film script file/scenario in FBX format uploaded to the website then is solved using a parsing algorithm into film elements such as cast members, extras, props, costumes, makeup, vehicles, stunts, special effects, music and sound. The results of this breakdown into sheets according to film elements. The purpose of this research is to produce breakdown sheets from film scripts according to film elements. The parsing algorithm test results showed the correct results of 12 scenes out of 19 scenes.
PERANCANGAN IT GOVERNANCE LAYANAN AKADEMIK MENGGUNAKAN FRAMEWORK INFORMATION TECHNOLOGY INFRASTRUCTURE LIBRARY (ITIL) VERSI 3 (STUDI KASUS: UIN SGD BANDUNG) Ichsan Taufik
JURNAL ISTEK Vol 5, No 1-2 (2011): ISTEK
Publisher : JURNAL ISTEK

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Abstract

The main activity in higher education in accordance with its main function is as education is academic service providers. This paper conducted a study of how the governance of information technology related to academic service to the organization UIN SGD Bandung, so that using information technology especially in terms of academic service which is a new service can help the organization in achieving its objectives. This paper refers to one of the governance framework for information technology that is ITIL (IT Infrastructure Library) version 3 which is the latest version of the ITIL framework is based on lifecycle. One of the cycles that exist in ITIL version 3 is the IT Service Operation which is the focus area of this paper. The procedure in this paper are: 1. Study of literature from a variety of relevant literature. 2. The collection of data and information through survey, observation, interview and collecting documents. 3. Data analysis. 4. Creating strategies and evaluate the application of IT Service Operation in UIN SGD Bandung. From the survey which was conducted with students, lecturers and employees of IT and Non IT regarding their response to conditions of readiness for implementing IT Service Operation in UIN SGD Bandung, so we found the conditions currently in the initial and repeatable stage where the condition is still necessary corrective steps which related to the implementation IT Service Operation. In this paper conducted an evaluation of strategy formulation and implementation of improvements to IT Service Operation in UIN SGD Bandung using frameworks IT Infrastructure Library (ITIL) version 3.
Deteksi Deepfake pada Gambar Medis Menggunakan YOLOv11 Pancadrya Yashoda Pasha; Ichsan Taufik; Aldy Rialdy Atmadja
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.2982

Abstract

Advances in artificial intelligence have given rise to challenges involving realistic deepfake images, extending into the healthcare sector. The contribution of this study lies in the implementation and performance analysis of YOLOv11 for detecting medical image deepfakes on a lung CT scan dataset covering variations of benign and malignant cases. The scope of the study is limited to binary classification between authentic and fake images, tested in a staged manner. CT-GAN and stable diffusion (SD) manipulation methods are employed to evaluate model performance. The results show that the YOLOv11 model achieves 100% accuracy, precision, recall, and F1-score on images manipulated using stable diffusion. In contrast, CT-GAN–based manipulations present challenges in distinguishing between authentic and fake lung cancer CT scan images. With further improvements and enhancements, fine-tuned YOLOv11 has the potential to become a relatively lightweight, fast, and accurate model for medical image deepfake detection. These results have the potential to support patient data security and maintain the integrity of clinical diagnostics in the future.
Vector space model, term frequency-inverse document frequency with linear search, and object-relational mapping Django on hadith data search Ichsan Taufik; Agra Agra; Yana Aditia Gerhana
Computer Science and Information Technologies Vol 5, No 3: November 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i3.p306-314

Abstract

For Muslims, the Hadith ranks as the secondary legal authority following the Quran. This research leverages hadith data to streamline the search process within the nine imams’ compendium using the vector space model (VSM) approach. The primary objective of this research is to enhance the efficiency and effectiveness of the search process within Hadith collections by implementing pre-filtering techniques. This study aims to demonstrate the potential of linear search and Django object-relational mapping (ORM) filters in reducing search times and improving retrieval performance, thereby facilitating quicker and more accurate access to relevant Hadiths. Prior studies have indicated that VSM is efficient for large data sets because it assigns weights to every term across all documents, regardless of whether they include the search keywords. Consequently, the more documents there are, the more protracted the weighting phase becomes. To address this, the current research pre-filters documents prior to weighting, utilizing linear search and Django ORM as filters. Testing on 62,169 hadiths with 20 keywords revealed that the average VSM search duration was 51 seconds. However, with the implementation of linear and Django ORM filters, the times were reduced to 7.93 and 8.41 seconds, respectively. The recall@10 rates were 79% and 78.5%, with MAP scores of 0.819 and 0.814, accordingly.
Co-Authors Agra Agra Agung Wahana Aldy Rialdy Atmadja Dhanis Al Ghifari Diena Rauda Ramdania Faiz M. Kaffah Pancadrya Yashoda Pasha Yana Aditia Gerhana Yana Aditia Gerhana, Yana Aditia