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PERANCANGAN AUTENTIKASI MULTI FAKTOR DENGAN PENGENALAN WAJAH DAN FIDO (FAST IDENTITY ONLINE)
Get PDFDigital services based online are assets that need to be safeguarded, especially if the application still uses single-factor authentication vulnerable to cyberattacks and potential data leaks and identity theft. The proposed solution is to implement multi-factor authentication (MFA) utilizing facial recognition, particularly through FaceNet technology. Although facial recognition can provide an additional layer of security, the main challenge is to maintain user privacy even if biometric information might leak. This research aims to create a secure, reliable MFA model that protects the privacy of employees at PT Traspac Makmur Sejahtera. The proposed method involves an MFA system with four factors: knowledge factor (password), biometric factor (facial measurements), ownership factor (OTP) and location factor (optional if facial accuracy is insufficient). The implementation of this MFA model enhances security, reliability, and protects employee privacy. Considering the specific needs of the company, this research can assist the company in monitoring the locations of employees working from home (WFH)
PENERAPAN MODEL WATERFALL DALAM MERANCANG APLIKASI PEMILIHAN SISWA TELADAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING
Get PDFBy having exemplary students, it is hoped that students at school will have good role models in all aspects. Unfortunately, subjective selection because it is done using voting can lead to unhealthy competition. So far, the selection of exemplary students begins with the selection of students with the highest average scores, then looks at the student's activity and record of violations which culminates in a vote carried out in the exemplary student selection meeting. Voting at the end of the election can cause the selection of exemplary students to no longer be objective and no longer fair. The application design will use the waterfall method by implementing the SAW method as a method used to help make decisions. The criteria used are 7 criteria in accordance with school policy and the results of this analysis, first the system is able to record all students who will be alternative exemplary students and also the criteria set in accordance with school policy. Second, by implementing a decision support system using CBIS, it can minimize the objectivity and complexity of stakeholders in making decisions and can increase data accuracy. Third, based on the management using this decision support application, an alternative ranking of exemplary students was obtained with the first alternative position being Siska Azzahra Shafa with a total score of 19,790, the second alternative being Andrawan Erlang Padana with a total score of 19,654 and the third being Ichsan Sandi with a total score of 19,645
PENGARUH PENJUALAN KONVENSIONAL DAN PENJUALAN E-COMMERCE TERHADAP KEPUTUSAN PEMBELIAN MENGGUNAKAN METODE REGRESI
Get PDFThe widespread use of e-commerce in the digital era has increased information disclosure while changing the way consumers make purchases. Consumer decisions are influenced by several factors, including the influence of technology, price and product comparison, information disclosure, and ease of access. The purpose of this study is to use regression analysis to examine the impact of traditional and online sales on PT Airlangga Jaya Mandiri. This study also looks at additional factors that can influence consumer purchasing decisions and determine the relationship between the variables studied. The regression analysis of PT Airlangga Jaya Mandiri, however, shows that neither traditional sales nor online sales significantly affect the dependent variable in this study. The resulting constant value is 1.740, and has a coefficient for conventional sales of 0.057 and a coefficient for E-commerce sales of -0.020. Although the p value is greater than 0.05, indicating statistical insignificance, further research and data collection is needed to confirm the relationship between these variables and consider other factors that may affect the dependent variable. The results of this study provide insights for businesses in developing more effective marketing strategies and improving customer service, with the understanding that the factors that consequence purchase decisions may be more complex than revealed in this regression mode
PENGARUH STRES, KEPUASAN KERJA DAN SELF-LEADERSHIP TERHADAP KINERJA PEGAWAI PT. BPR KHRISNA DARMA ADIPALA
Get PDFHuman resources continue to be the central focus and backbone for companies to maintain their operations. The vital role of human resources is apparent in all company activities. The study was carried out at PT BPR Khrisna Darma Adipala in Badung Regency, with a sample of 50 employees serving as respondents, employing a saturated sampling method for sampling. Data collection involved the use of questionnaires, interviews, observations, and documentation. Data analysis involved the application of multiple linear regression analysis with SPSS version 25. The findings indicate that work-related stress detrimentally affects employee performance, suggesting that heightened stress levels correspond to diminished performance at PT BPR Khrisna Darma Adipala in Badung Regency. Conversely, job satisfaction positively influences employee performance, indicating that higher satisfaction levels correspond to better performance at PT BPR Khrisna Darma Adipala in Badung Regency. Moreover, self-leadership also yields a positive impact on employee performance, indicating that an increase in self-leadership is associated with improved performance at PT BPR Khrisna Darma Adipala in Badung Regency
A SYSTEMATIC LITERATURE REVIEW: RECURSIVE FEATURE ELIMINATION ALGORITHMS
Get PDFRecursive feature elimination (RFE) is a feature selection algorithm that works by gradually eliminating unimportant features. RFE has become a popular method for feature selection in various machine learning applications, such as classification and prediction. However, there is no systematic literature review (SLR) that discusses recursive feature elimination algorithms. This article conducts a SLR on RFE algorithms. The goal is to provide an overview of the current state of the RFE algorithm. This SLR uses IEEE Xplore, ScienceDirect, Springer, and Scopus (publish and publish) databases from 2018 to 2023. This SLR received 76 relevant papers with 49% standard RFEs, 43% strategy RFEs, and 8% modified RFEs. Research using RFE continues to increase every year, from 2018 to 2023. The feature selection method used simultaneously or for comparison is based on a filter approach, namely Pearson correlation, and an embedded approach, namely random forest. The most widely used machine learning algorithms are support vector machines and random forests, with 19.5% and 16.7%, respectively. Strategy RFE and modified RFE can be referred to as hybrid RFEs. Based on relevant papers, it is found that the RFE strategy is broadly divided into two categories: using RFE after other feature selection methods and using RFE simultaneously with other methods. Modification of the RFE is done by modifying the flow of the RFE. The modification process is divided into two categories: before the process of calculating the smallest weight criteria and after calculating the smallest weight criteria. Calculating the smallest weight criteria in this RFE modification is still a challenge at this time to obtain optimal results
APPLICATION OF GROUP DECISION MAKING IN DETERMINING CULINARY TOURISM WITH TOPSIS AND BORDA METHODS
Get PDFMakassar City is one of the destination cities for traveling. Makassar City offers a variety of interesting tours, one of which is culinary tourism. The determination of the best culinary tourism is based on the criteria set by the Makassar City Tourism Office. In managing culinary destinations, tourists are often faced with many choices, so they are confused about choosing the most attractive culinary destinations. This research uses the TOPSIS and BORDA methods. The TOPSIS method is used in determining culinary tourism alternatives based on criteria that become recommendations and the BORDA method is used in determining the selected alternatives based on several DMs who evaluate alternatives. The main objective of this research is to apply group decision making in selecting the best culinary tourism destinations in Makassar City based on group preferences and related criteria with TOPSIS and BORDA methods. This research has conducted 5 iterations involving 4 DMs from the Makassar City Tourism Office. Based on the results of the interview, 8 criteria and 35 alternatives were obtained. Where the Coto Nusantara alternative is ranked the highest with a value of 109,949. While Sop Saudara Irian is ranked last with a value of 62,896. The general benefit of this research is the application of group decision making in determining culinary tourism with the TOPSIS and BORDA methods can produce more objective and representative decision results. This can increase tourist satisfaction in determining culinary tourism
ENHANCING SENTIMENT ANALYSIS ACCURACY IN DELIVERY SERVICES THROUGH SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE
Get PDFPaxel is one of the delivery services that use the application. On Google Play, there are more than 10 thousand users leaving reviews. From this review data, a sentiment analysis was then carried out to determine the level of user satisfaction with Paxel's services. The methods used in this study are Random Forest (RF) and Support Vector Machine (SVM), as well as applying Synthetic Minority Oversampling Technique (SMOTE) to overcome data imbalance. The results showed that the method testing by dividing the data into two, namely training data and testing data by 80:20, stated that by applying the SMOTE, a higher accuracy value was obtained, where the accuracy of the RF method reached 91%, and the SVM method reached 87%. The level of user satisfaction with Paxel services tends to be neutral. This can be seen in the classification of the RF method with F1-Score values for the Positive class 89%, Neutral class 93%, and Negative class 92%
CLUSTERING DATA METEOROLOGI WILAYAH INDONESIA TIMUR DENGAN METODE K-MEANS DAN FUZZY C-MEANS
Get PDFClimate change is a global issue that affect human life and the environment. Signs of climate change can be observed from long-term meteorological data. This research uses clustering techniques with the K-Means and Fuzzy C-Means methods to group cities in the Eastern Indonesia region based on numerical daily time series meteorological data from 1 January 2010 to 31 August 2023. The variables are minimum temperature, maximum temperature, temperature average, humidity, rainfall, duration of sunlight, maximum wind speed, and average wind speed. The dataset was collected from 28 meteorological stations. The K-Means and Fuzzy C-Means methods obtained the same results, namely the highest silhouette value of 0.218 with the number of clusters k = 2. In general, the annual trend shows an increase in temperature and a decrease in wind speed which are signs of climate change. This research is an early study of climate change in East Indonesia. The results of this research are expected to contribute to the study of climate change in Indonesia
AUTOMATION OF THE BERT AND RESNET50 MODEL INFERENCE CONFIGURATION ANALYSIS PROCESS
Get PDFInference is the process of using models to make predictions on new data, performance is measured based on throughput, latency, GPU memory usage, and GPU power usage. The models used are BERT and ResNet50. The right configuration can be used to maximise inference. Configuration analysis needs to be done to find out which configuration is right for model inference. The main challenge in the analysis process lies in its inherent time-intensive nature and inherent complexity, making it a task that is not simple. The analysis needs to be made easier by building an automation programme. The automation programme analyses the BERT model inference configuration by dividing 10 configurations namely bert-large_config_0 to bert-large_config_9, the result is that the right configuration is bert-large_config_2 resulting in a throughput of 12.8 infer/sec with a latency of 618 ms. While the ResNet50 model is divided into 5 configurations, namely resnet50_config_0 to resnet50_config_4, the result is that the right configuration is resnet50_config_1 which produces a throughput of 120.6 infer/sec with a latency of 60.9 ms. The automation programme has the benefit of facilitating the process of analysing the inference configuration
A SYSTEMATIC LITERATURE REVIEW ON ROLE OF PROJECT MANAGEMENT IN DIGITAL FORENSICS INVESTIGATION
Get PDFThe landscape of digital forensics has evolved significantly with the advent of sophisticated cybercrimes and the proliferation of digital devices. Digital forensics is a rapidly evolving discipline, characterized by unique challenges such as rapidly changing technology, large volumes of data, and stringent legal requirements. Effective project management in this context is crucial to ensure that investigations are conducted efficiently, accurately, and in compliance with legal standards. This systematic literature review aims to comprehensively analyze the role of project management practices in optimizing digital forensics investigations. Using established search protocols and selection criteria, we identified and analyzed relevant studies published between 2016 until 2023 that explored the application of project management methodologies, challenges, and best practices within the context of digital investigations. By applying effective project management strategies, investigators can ensure efficient, accurate, and legally sound digital investigations, ultimately contributing to successful criminal prosecutions and civil litigation outcomes