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LAPORAN PRAKTIK MAGANG USER INTERFACE, USER EXPERIENCE, AND ANDROID MOBILE DEVELOPMENT DI PT KINEMA SYSTRANS MULTIMEDIA
Get PDFAnalisis Good Corporate Governance Perbankan Syariah Indonesia: Perspektif Maqashid Syariah
Get PDFDalam mendorong kinerja perbankan, pelaksanaan good corporate governance (GCG) menjadi salah satu kunci keberhasilan. Sebagaimana praktik perbankan syariah bertumpu pada syariat Islam, diharapkan penerapan GCG akan mengandung dan mendorong tercapainya tujuan syariat (maqashid syariah). Penelitian ini merumuskan sebuah indeks pengukuran kandungan maqashid syariah dalam praktik GCG yang berangkat dari indikator maqashid dharuriyyat dengan dimensi dan elemen disesuikan dengan faktor penilaian GCG. Kemudian secara deskriptif kualitatif menganalisis laporan pelaksanaan GCG perbankan syariah di Indonesia menggunakan indeks pengukuran yang sudah disusun. Ditemukan bahwa praktik GCG perbankan syariah di Indonesia sudah berjalan dengan baik dan mengandung nilai-nilai maqashid syariah, namun masih terdapat beberapa catatan kekurangan yang harus diperbaiki
'Aabidah Ummu 'Aziizah_Peer Review Artikel Jurnal The Amalgamation of Traditional and Contemporary Elements in Islamic Education
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Usage of Unsupported Technologies in Websites Worldwide
Get PDFWebsites using unsupported 3rd party technologies (libraries, frameworks, plugins, etc) are generally not recommended, especially due to security issues that are left unfixed. However, upgrading to supported technologies is also challenging, hence not all web maintainers upgrade their technology dependencies. Measuring the existence of unsupported technologies in the wild may contribute to the sense of urgency in keeping technologies updated. Our research proposed a method to measure the existence of unsupported technologies in international websites, using HTTP Archive as the data source. The contribution from our research is the method as well as the snapshot result from January 2023 data. The method is composed of four steps, namely: identify the list of websites, identify technologies used, group by technology names and retrieve currently supported versions, and compare versions between usage and supported versions. From the January 2023 data, we found several interesting results. One is that the higher the website rank is, the higher the number of supported technologies used. Another finding was that worldwide websites also generally use more supported versions of technologies, compared to Indonesian websites. Further research may be performed for longitudinal analysis of technology support evolution
Exploring Energy Data through Clustering: A Hyperparameter Approach to Mapping Indonesia's Primary Energy Supply
Get PDFThe rapid economic growth and population development in Indonesia have significantly increased the demand for energy, presenting complex challenges in managing the primary energy supply due to geographical variability and dispersed natural resources. This study addresses these challenges by applying clustering techniques with a hyperparameter approach to explore and map Indonesia's primary energy supply. The research contributes to the field by offering an effective method for analyzing energy data patterns and optimizing energy management. Secondary data on energy production, consumption, and distribution from reliable sources such as the Ministry of Energy and Mineral Resources were collected and analyzed. Various clustering algorithms, including K-Means, Fast K-Means, X-Means, and K-Medoids, were applied to identify energy supply patterns across different regions. The Davies-Bouldin Index was used to evaluate the effectiveness of the clustering algorithms. The results indicate that distance measures such as Euclidean Distance and Chebychev Distance consistently show excellent clustering performance. The study found that the choice of distance measure significantly impacts the clustering quality. The insights gained from this analysis provide valuable information for stakeholders involved in energy planning and policy-making, enhancing the efficiency and sustainability of energy management in Indonesia. This research establishes a foundation for further detailed and holistic energy data analysis, supporting better decision-making in energy planning and development
Addressing Overfitting in Dermatological Image Analysis with Bayesian Convolutional Neural Network
Get PDFVGG, ResNet, and DenseNet are popular convolutional neural network (CNN) designs for transfer learning (TL), aiding dermatological image processing, particularly in skin cancer categorization. These TL-CNN models build extensive neural network layers for effective image classification. However, their numerous layers can cause overfitting and demand substantial computational resources. The Bayesian CNN (BCNN) technique addresses TL-CNN overfitting by introducing uncertainty in model weights and predictions. Research contributions are (i) comparing BCNN with three TL-CNN architectures in dermatological image processing and (ii) examining BCNN ability to mitigate overfitting through weight perturbation and uncertainty during training. BCNN uses flipout layers to perturb weights during training, guided by the KL divergence and Binary Cross Entropy (BCE) loss function. The dataset used is the ISIC Challenge 2017, categorized as malignant and benign skin tumors. The simulation results show that three TL-CNN architectures, namely VGG-19, ResNet-101, and DenseNet-201, obtained training accuracies of 96.65%, 100%, and 97.70%, respectively. However, all three were only able to achieve a maximum validation accuracy of around 78%. In contrast, BCNN can produce training and validation accuracy of 81.30% and 80%, respectively. The difference in training and validation accuracy values produced by BCNN is only 1.3%. Meanwhile, the three TL-CNN architectures are trapped in an overfitting condition with a difference in training and validation values of around 20%. Therefore, BCNN is more reliable for dermatological image processing, especially for skin cancer images