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Jurnal Sisfotek Global
Published by Institut Teknologi dan Bisnis Bina Sarana Global
ISSN : 20881762     EISSN : 27213161     DOI : http://.doi.org/10.38101/jsg
Core Subject : Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering
Jurnal Sisfotek Global is a peer-reviewed open access journal published twice a year (March and September), a scientific journal published by Institut Teknologi dan Bisnis Bina Sarana Global. Jurnal Global Sisfotek aims to provide a national forum for researchers and professionals to share their ideas on all topics related to the field of computer science. It is published in online version (e-ISSN 2721-3161) and printed version (p-ISSN 2088-1762). Jurnal Global Sisfotek has been indexed and abstracted in Index Copernicus, GOOGLE Scholar, BASE (Bielefeld Search Engine), Crossref Search, One Search, PKP-Indexed, Neliti search, Garuda, Dimensions, Scilit. Jurnal Sisfotek Global accepts quality manuscripts produced from research projects within the scope of the field of computer science, which include, but are not limited to the following topics: information systems, image processing, multimedia, mobile computing, artificial intelligence, expert systems, computer systems. The manuscript must be original research and written in English (from 2021).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 353 Documents
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Customer Segmentation Based on RFM Value on the Sale of Electronic Kopmen BMI Using K-Means Clustering Algorithm Zainul Hakim; Detin Sofia; Annida Rosna Fadhilah
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9693

Abstract

At present, the development of information technology is increasing rapidly. The need for information and data processing in various aspects of human life is critical, as well as customer data processing in BMI Consumer Cooperatives. This situation can impact information providers in an organization or company that requires fast, precise, and accurate data processing. The customer segmentation clustering system at the BMI Consumer Cooperative has yet to be implemented. A K-means clustering system is needed to increase customer loyalty, which can simplify the process of grouping customer segmentation. In this thesis, researchers use a descriptive method as a research methodology, which is used to get an overview and explanation of the state of the research object based on facts. As for the data collection method, researchers used interviews, observation, and literature study. In developing the system, researchers use prototyping. The customer segmentation information system application prototype describes the implementation of Astah's UML (Unified Modeling Language) and program planning used by Python. The conclusion of this prototype application can make it easier for managers to get information about customer segmentation data.
Educational Game-Based Mathematics Learning Media for Elementary School Children Agustinus Sirumapea; Ferawati Ferawati; Fiqih Hana Saputri; Andhika Fajar Utama
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9700

Abstract

This study aims to produce and test the feasibility of an educational game for Mathematics using Construct 2 software. This game contains Mathematics subject matter and is used as a learning medium at SDIT Smart Syahid. The research method used in making this Educational game is ADDIE (Analysis – Design- Development – Implementation – Evaluation), where the research stages are in the form of needs analysis, design process, product development, implementation, and evaluation. The analysis phase includes a needs analysis related to the product. The stages in the design process include the design process and making improvements if there are still design discrepancies between the user and the analyst. The product development stage contains manufacturing based on the analysis and design results that have been done before. Next is the implementation stage; at this stage, the programmer develops the design into a program that can be tested. The last step is the evaluation stage and making improvements if there are still design discrepancies between the user and the analyst. From the results of this study, the researcher succeeded in creating a Mathematics educational game.
Prediction of Domino Pizza Customer Service Quality Level in Tangerang Area using Heteroscedasticity Purchase Satisfaction Test using Sampling Method Tapawinaka, Gusti Agung Gede
JURNAL SISFOTEK GLOBAL Vol 15, No 1 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i1.15823

Abstract

Pizza is one of the Italian foods that is a favorite menu in various parts of the world. In Indonesia itself, we can more easily find pizza variants spread across various regions in Indonesia. We just have to choose according to taste. The pizza that is the object of the study is some that come from original Italian recipes, some that adopt typical Indonesian. The pizza that is the object of the study is Domino's Pizza. The purpose of this study is to determine the effect of Instagram influencer endorsement on pizza purchasing decisions, which focuses on product factors, price factors, promotion factors, place factors and influencer factors. The product, price, promotion, place and influencer variables are independent variables and the purchasing decision variable is the dependent variable, so that the calculation carried out by the sampling method can be appropriate. The study was conducted on consumers in the Tangerang area using the sampling method. The use of datasets in this study was carried out with a quantitative approach. Data collection was carried out by collecting online questionnaires filled out by pizza consumers. The independent variables of the study are product (X1), price (X2), promotion (X3) and place (X4). As a moderating variable, namely Instagram influencer endorsement (Y) on purchase satisfaction (Z), this is the data collection that will be processed later. In this study, the questionnaire will be tested with validity and reliability tests. Then classical testing is carried out, hypothesis testing with the F test and t test.
Evaluation of SAPA WARGA Application System and User Satisfaction: Public Service Technology Management Perspective Based on PIECES Framework Fauzi, Irwan Maulana; Nugroho, Ario Adi; Khoirunisa, Alfiah
JURNAL SISFOTEK GLOBAL Vol 15, No 1 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i1.15836

Abstract

The utilization of technology in public services continues to evolve to enhance efficiency, transparency, and service quality for society. However, the implementation of technology in the public sector still faces various challenges, such as human resource readiness, infrastructure, and resistance to change. This study aims to evaluate the SAPA WARGA application using the PIECES framework, which includes aspects of Performance, Information, Economy, Control, Efficiency, and Service. The application is used by the West Java Provincial Government to improve public services by providing convenience for the public in reporting complaints, conveying aspirations, and accessing information related to public services. The survey results showed that the majority of respondents were satisfied with the application's performance, customer support, and vehicle tax due reminder feature. However, several areas still require improvement, such as application speed, information consistency, and response to user complaints.
Introduction of Indonesian Significant Alphabet Images (BISINDO) using The Convolutional Neural Network Algorithm Kabut, Stefanus; Kelen, Yoseph Pius Kurniawan; Baso, Budiman; Chrisinta, Debora
JURNAL SISFOTEK GLOBAL Vol 15, No 1 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i1.15678

Abstract

Bisindo alphabet recognition is the process by which a computer system or software recognizes and recognizes the letters of the Bisindo alphabet. The Bisindo alphabet is a special alphabet used to communicate with people who are hearing or speech impaired. This process uses image processing and machine learning techniques to identify and classify each letter based on its shape and visual characteristics. This study used a dataset consisting of 520 Kaggle images divided into 26 categories. These images are resized, normalized and scaled up to improve model performance. A Convolutional Neural Network (CNN) model was developed and achieved 99.12587% accuracy after training. After the model was developed, the API was implemented using Flask. API functionality is tested using online interactions, ensuring accurate responses to image classification before implementation in mobile applications.
Comparison of the Performance of Multiple Linear Regression and Multi-Layer Perceptron Neural Network Algorithms in Predicting Drug Sales at Pharmacy XYZ Arifuddin, Danang; Kusrini, Kusrini; Kusnawi, Kusnawi
JURNAL SISFOTEK GLOBAL Vol 15, No 1 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i1.15822

Abstract

The needs of better drugs management tool especially that can predict specific drugs consumption volume are needed by any healthcare facility including retail pharmacies. Thus, finding better prediction algorithm with suitable variable internally and externally becoming this research objectives. The research compares correlation score and histogram of each predictor variable with target variable and further input the selected variable into MLR and MLPNN algorithm to find recommended algorithm with better MSE and MAPE. The findings indicate that MLPNN with backpropagation method slightly outperforms MLR with ‘h-7’ as single input variable but with unstable predictions with lower MSE of 19588 and MAPE of 22,3%. While MLR's MSE of 22346,129 and MAPE of 25.4% with ‘h-7’ and ‘bm’ as input variable perform stable prediction. Finally, the research find ‘h-7’ is the most significant variable among other variables and both MLR and MLPNN are both need better improvement to perform drugs prediction analysis.
Sentiment Analysis on User Reviews of the Edlink Application Using the Random Forest Classifier Method Mola, Sebastianus Adi Santoso; Polly, Dian Putri Novita; Rumlaklak, Nelcy D.
JURNAL SISFOTEK GLOBAL Vol 15, No 1 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i1.15788

Abstract

Edlink is a learning platform developed by PT. Sentra Vidya Utama (SEVIMA), established in 2004. Although it offers useful features, some aspects need improvement based on user reviews on Google Play Store. This study aims to accurately classify user sentiment to identify areas that need enhancement. The main challenges include language diversity, sentiment class imbalance, and the need for a reliable classification method. The random forest classifier method was chosen for its ability to handle overfitting and optimize performance. The dataset consists of 1,117 reviews divided into three classes: 385 negative, 118 neutral, and 614 positive. Data was collected through web scraping and processed using cleaning, normalization, tokenizing, stemming, negation conversion, and stopword removal, then weighted using TF-IDF. Testing results showed an accuracy of 86% using 5-Fold cross-validation and SMOTE. The 10-Fold cross-validation test demonstrated that this method outperforms other classification methods with 90% accuracy.
Implementation of Fisher Yates Algorithm for Question Randomization in Human Digestive System Educational Application Mughits, Muhammad Choirul; Krisdiawan, Rio Andriyat; Herwanto, Heri
JURNAL SISFOTEK GLOBAL Vol 15, No 2 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i2.15825

Abstract

At SMPN 1 Lebakwangi, the teaching and learning process of science subjects in class VIII has utilized media such as books and videos, with identical exercises and quizzes given to all students. However, this approach faces challenges due to the limited variety of learning media and practice questions, which rely heavily on textbooks. As a result, students often struggle to absorb and understand the material effectively, finding the learning process less interesting and diverse. This research aims to develop alternative learning media in the form of an educational application that focuses on the human digestive system. The app incorporates the Fisher-Yates algorithm to randomize quiz questions, ensuring that students receive different sequences of questions. The system was developed using RUP (Rational Unified Process) methodology, and the design was made with UML (Unified Modeling Language). User Acceptance Test (UAT) results show the effectiveness of the application, with scores of 91.66% for appearance, 92.47% for material content, 89.74% for learning process, and 91.77% for improving understanding. This educational app serves as an interactive, engaging, and diverse learning medium, offering alternative practice questions that improve understanding of human digestive system material.
Implementation of AHP and TOPSIS: Selection of Medical Equipment Distributors at the Ministry of Health of the Republic of Indonesia Taufiq, Muhammad; Septian, Ghofur Rahmat
JURNAL SISFOTEK GLOBAL Vol 15, No 2 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i2.15937

Abstract

This research aims to develop a Decision Support System (DSS) using the Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assist the Ministry of Health in selecting the most suitable medical equipment distributor. The AHP method is employed to determine the weight of multiple evaluation criteria, including Quality Management System, Human Resources Management, Infrastructure, Inventory Handling, Traceability, Complaint Handling, FSCA, Returns, Disposal, Illegal Access, Internal Audit, Management Review, and Third-Party Activities. Once the weights are established, the TOPSIS method is applied to evaluate and rank the distributor alternatives based on their relative proximity to the ideal and anti-ideal solutions. The integration of AHP and TOPSIS ensures a more structured, objective, and data-driven decision-making process. The results show that the distributor labeled D4 has the highest preference value (0.64632), indicating the best performance among all alternatives evaluated. This combined method enhances decision-making accuracy, reduces subjectivity, and aligns selection outcomes with operational and regulatory standards. The study concludes that implementing a DSS using AHP and TOPSIS can significantly improve the efficiency, transparency, and effectiveness of medical equipment distributor selection within the healthcare logistics system.
EXIF Metadata Feature Extraction to Improve Source Device Identification Accuracy in Digital Images within a Digital Forensics Approach Bahreisy, Muhammad Naufal; Pratama, Adi Rizky; Munzi, Gugy Guztaman; Wicaksana, Yusuf Eka
JURNAL SISFOTEK GLOBAL Vol 15, No 2 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i2.15998

Abstract

This study aims to develop and evaluate methods for digital image source device identification through three main approaches, namely EXIF metadata feature extraction, visual analysis using Convolutional Neural Networks (CNN), and Photo Response Non-Uniformity (PRNU). The dataset consists of 500 original images captured from five different devices, with 100 images per device containing intact metadata. The EXIF-only model was built using the Random Forest algorithm, the CNN model employed a ResNet18 architecture, while PRNU utilized high-pass filtering to construct sensor noise templates for each device. Evaluation was carried out using accuracy, precision, recall, and f1-score metrics. The results show that EXIF-only achieved perfect accuracy (100%) on the dataset with complete metadata, CNN reached 21% accuracy with imbalanced recall across classes, and PRNU demonstrated low performance due to the limited number of templates and image quality. These findings indicate that EXIF-only excels under intact metadata conditions but is vulnerable to manipulation, CNN can be applied when metadata is unavailable but requires optimization, while PRNU has potential resilience against metadata manipulation but demands higher-quality data. The novelty of this study lies in its comparative multi-method approach that integrates metadata-based, visual-based, and sensor fingerprint-based analyses, along with the proposal of a multimodal integration framework to enhance the reliability of device identification systems in digital forensic practice.

Page 33 of 36 | Total Record : 353

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