Implementasi Unified Modeling Language (UML) pada Perancangan Aplikasi WiFiTalkie Berbasis TCP/IP

Di dunia komunikasi analog kita mengenal perangkat yang bernama HT (Handy Talkie). Perangkat ini bekerja dengan menggunakan sinyal elektromagnetik pada frekuensi radio tertentu. Perangkat ini berfungsi sebagai pengirim dan penerima sinyal radio.Sinyal yang dikirimkan adalah sinyal suara yang telah diubah menjadi sinyal elektromagnetik. Untuk dapat berkomunikasi satu sama lain, maka harus ada kesepakatan antar pengguna untuk menyetel perangkatnya pada frekuensi yang sama. Salah satu kelemahan dari perangkat ini adalah kualitas suara yang cenderung noisy dan sangat bergantung pada kondisi cuaca. Dengan seiring teknologi semikonduktor yang berkembang pesat, terciptalah perangkat digital yang semakin bervariasi kegunaannya. Saat ini sudah banyak diciptakan perangkat digital yang dapat menggantikan perangkat analog secara keseluruhan. Sebagai contohnya adalah pesawat televisi. Pesawat televisi digital memberikan kualitas yang jauh lebih baik daripada perangkat televisi analog dengan ukuran yang jauh lebih ramping. Contoh yang lain saat ini tersedia smartphone yang memiliki fitur yang sangat lengkapyang tertanam pada perangkat yang berukuran relatif kecil. Salah satu fiturnya adalah wifi. Dengan fitur ini sebuah smartphone dapat terhubung satu sama lain, bahkan dapat terhubung dengan internet dengan mudahnya. Dalam rangka digitalisasi perangkat analog dan tersedianya fiturwifidi dalam smartphone ini, maka diciptakan sebuah aplikasi WiFiTalkie. Cara kerjanya yaitu smartphone akan mengirimkan sinyal suara dengan memanfaatkan teknologi TCP/IP melalui jaringan wifi, kemudian smartphone yang lain di dalam network yang sama menerima sinyal ini dan memprosesnya kembali menjadi sinyal suara. Aplikasi ini dibangun dengan mengimplementasikan metode perancangan Unified Modeling Language (UML). Hasil penelitian ini menunjukkan bahwa kualitas suara yang dihasilkan oleh WiFiTalkie jauh lebih baik daripada HT yang berbasis pada sinyal analog

Rancang Bangun Aplikasi Smart Touring Berbasis Android

Perkembangan teknologi saat ini begitu cepat. Teknologi membuat perubahan pada peradaban manusia. Telah banyak kegiatan manusia yang didukung oleh kemajuan teknologi. Tak terkecuali kegiatan touring yang dilakukan bersama-sama. Touring adalah kegiatan berkendara dari suatu tempat ke tempat lain secara bersama-sama. Saat ini komunitas touring terus meningkat, namun masih memiliki beberapa permasalahan saat melakukan aktifitasnya. Saat ini salah satu permasalahan yang ada pada aktifitas touring adalah pengendara satu dengan yang lainnya tidak bisa mengetahui lokasi semua teman touring mereka. Oleh karena itu sangat dimungkinkan ada anggota touring mereka yang tertinggal jauh atau salah jalur. Dengan teknologi smartphone yang sangat pesat, dimungkinkan dibangun sebuah sistem yang dapat mendukung kegiatan touring tersebut. Pada penelitian ini telah berhasil dibangun sistem yang dapat mendukung kelancaran aktifitas touring. Fokus penelitian ini adalah membangun sistem touring yang dapat mendeteksi keberadaan semua member touring ketika sedang melakukan kegiatan touring. Sistem yang dibangun adalah berbasis contextual awareness, yaitu sistem yang mampu memberikan informasi kepada pengguna dengan data yang didapat dari lingkungannya. Dalam hal ini adalah memberikan informasi ketika ada member touring yang berjauhan dengan member touring lainnya

AuSR2: Image watermarking technique for authentication and self-recovery with image texture preservation

This paper presents an image watermarking technique for authentication and self-recovery called AuSR2. The AuSR2 scheme partitions the cover image into 3 × 3 non-overlapping blocks. The watermark data is embedded into two Least Significant Bit (LSB), consisting of two authentication bits and 16 recovery bits for each block. The texture of each block is preserved in the recovery data. Thus, each tampered pixel can be recovered independently instead of using the average block. The recovery process may introduce the tamper coincidence problem, which can be solved using image inpainting. The AuSR2 implements the LSB shifting algorithm to increase the imperceptibility by 2.8%. The experimental results confirm that the AuSR2 can accurately detect the tampering area up to 100%. The AuSR2 can recover the tampered image with a PSNR value of 38.11 dB under a 10% tampering rate. The comparative analysis proves the superiority of the AuSR2 compared to the existing scheme

AuSR1 : Authentication and self-recovery using a new image inpainting technique with LSB shifting in fragile image watermarking

With the rapid development of multimedia technology, editing and manipulating digital images have become more accessible than ever. This paper proposed color image authentication based on blind fragile image watermarking for tamper detection and self-recovery named AuSR1. The AuSR1 divides each channel of the cover image into non-overlapping blocks with the size of 2 × 2 pixels. The authentication data is embedded into the original block location, while the recovery data is embedded into the distant location from the original location based on the block mapping algorithm. The watermark data is then embedded into the 2 LSB to achieve high quality of the recovered image under tampering attacks. In addition, the permutation algorithm is applied to ensure the security of the watermark data. The AuSR1 utilizes a three-layer authentication algorithm to achieve a high detection rate. The experimental results show that the scheme produced a PSNR value of 45.57 dB and an SSIM value of 0.9972 of the watermarked images. Furthermore, the AuSR1 detected the tampered area of the images with a high precision value of 0.9943. In addition, the recovered image achieved a PSNR value of 27.64 dB and an SSIM value of 0.9339 on a 50% tampering rate

Sentiment Analysis and Topic Modeling of Kitabisa Applications using Support Vector Machine (SVM) and Smote-Tomek Links Methods

Kitabisa is an Indonesian application that functions to raise funds online. Users can easily support various types of campaigns and donate funds to various social causes through the app. User reviews of the application are very diverse, and it is not sure whether user reviews of the application tend to be positive, neutral, or negative. This research aimed to analyze the sentiment of the Kitabisa application by modeling topics using Latent Dirichlet Allocation (LDA) and classifying user reviews using a Support Vector Machine (SVM). The scrapped dataset showed imbalanced dataset problems, so the SMOTE-Tomek Links oversampling technique was proposed. The results of this study show that using LDA produces five topics often discussed in 750 reviews. Then, the performance of SVM without using SMOTE-Tomek Links was 72% accuracy, 76% precision, 72% recall, and 64% f1 score. Meanwhile, using SMOTE-Tomek Links could significantly improve the performance, namely 98% accuracy, 98% precision, 98% recall, and 98% f1 score. Based on this research, the application of SVM achieved high performance for user sentiment classification, especially when the dataset was in a balanced state. Therefore, the SMOTE-Tomek Links oversampling technique is recommended for dealing with unbalanced sentiment datasets

A blind recovery technique with integer wavelet transforms in image watermarking

The development of internet technology has simplified the sharing and modification of digital image information. The aim of this study is to propose a new blind recovery technique based on integer wavelets transform (BRIWT) by utilizing their image content. The LSB adjustment technique on the integer wavelet transform is used to embed recovery data into the two least significant bits (LSB) of the image content. Authentication bits are embedded into the current locations of the LSB of the image content, while the recovery information is embedded into different block locations based on the proposed block mapping. The embedded recovery data is securely placed at random locations within the two LSBs using a secret key. A three-layer embedding of authentication bits is used to validate the integrity of the image contents, achieving high precision and accuracy. Tamper localization accuracy is employed to identify recovery bits from the image content. This research also investigates the image inpainting method to enhance recovery from tampered images. The proposed image inpainting is performed by identifying non-tampered pixels in the surrounding tamper localization. The results demonstrate that the proposed scheme can produce highly watermarked images with imperceptibility, with an average SSIM value of 0.9978 and a PSNR value of 46.20 dB. The proposed scheme significantly improves the accuracy of tamper localization, with a precision of 0.9943 and an accuracy of 0.9971. The proposed recovery technique using integer wavelet transforms achieves high-quality blind recovery with an SSIM value of 0.9934 under a tampering rate of 10%. The findings of this study reveal that the proposed scheme improves the quality of blind recovery by 14.2 % under a tampering rate of 80 %

Self-Recovery in Fragile Image Watermarking Using Integer Wavelet Transform

The growth of internet technology makes digital images can be easily distributed and modified to change image information. This research proposes fragile image watermarking based on LSB Adjustment on integer wavelet transform. This study focuses on self-recovery and authenticating the integrity of image contents. The proposed scheme embeds a watermark into the two-LSB by using LSB adjustment. The authentication bits are randomly located in the two-LSB with a secret key. The recovery data is generated based on IWT for the recovery process. The proposed watermarking method uses multi-layer authentication to achieve high precision and accuracy. This research also uses image inpainting techniques to improve the recovery under tamper attacks. The experimental results produce high imperceptibility with PSNR of 45.5 dB and SSIM of 0.997. The proposed scheme produces better self-recovered image quality than the existing scheme with PSNR of 37.98 dB and SSIM of 0.9928 against a tampering rate of 10

Towards effective evacuation procedures in disaster management (Dm): Simulation modelling and governance strategies

Natural catastrophes and disasters may cause the destruction of infrastructure and personal property. In order to reduce the effects of such tragedies, the effectiveness of the evacuation procedures is essential. Effective evacuation procedures, however, also depend on governance issues in addition to technical aspects like infrastructure and communication. This paper intends to review on how governance, and evacuation protocols relate to emergency preparedness and disaster management (DM). Thus, this study explores the use of agent-based and social force theory in developing evacuation simulation models that incorporate evacuation governance strategies. Practitioners and policymakers can better understand the elements that determine the effectiveness of evacuation procedures and create more efficient methods for disaster management and emergency response by modelling human behaviour in disaster circumstances. The policy is an illustration of how governance elements can be integrated into evacuation procedures and guidelines for effective DM. Thus, the expected result for this study emphasises the significance of governance for policymakers and practitioners in the execution of evacuation procedures

Selection of prospective workers using profile matching algorithm on crowdsourcing platform

The use of a crowdsourcing platform is an option to get workers who will help complete the work. Crowdsourcing is the process of gathering work, information, or opinions from a large number of individuals using the internet, social media, or smartphone apps. Whether crowdsourcing is used for programming, design, content creation, or any other task, requesters are putting their trust in individuals who are unfamiliar with their knowledge and have unknown histories and skills. Requesters do not have the time or resources to screen all of the crowd's qualities, unlike employing full-time personnel. In this study, we try to minimize the risks faced by requesters when using a crowdsourcing platform to complete their work, namely by increasing the match between the profile of workers and the jobs offered on the crowdsourcing platform. The researcher implemented the profile matching method using a dataset consisting of several fields that became the criteria for finding a match. The criteria used to find a match between workers and the work offered consist of two parts, core factors and secondary factors. Core Factor Criteria as skill, designation, location, and the secondary factor is the number of years of work experience. These criteria become variables that are used in the profile matching algorithm to find workers who best match the profiles offered. This algorithm is able to select worker profiles from 10,000 datasets, up to 1148 people who are most suitable for the tasks offered. And the results obtained indicate an increase in the match between workers and the needs of the work offered by the requester

Three layer authentications with a spiral block mapping to prove authenticity in medical images

Digital medical image has a potential to be manipulated by unauthorized persons due to advanced communication technology. Verifying integrity and authenticity have become important issues on the medical image. This paper proposed a self-embedding watermark using a spiral block mapping for tamper detection and restoration. The block-based coding with the size of 3x3 was applied to perform selfembedding watermark with two authentication bits and seven recovery bits. The authentication bits are obtained from a set of condition between sub-block and block image, and the parity bits of each sub-block. The authentication bits and the recovery bits are embedded in the least significant bits using the proposed spiral block mapping. The recovery bits are embedded into different sub-blocks based on a spiral block mapping. The watermarked images were tested under various tampered images such as blurred image, unsharp-masking, copy-move, mosaic, noise, removal, and sharpening. The experimental results show that the scheme achieved a PSNR value of about 51.29 dB and a SSIM value of about 0.994 on the watermarked image. The scheme showed tamper localization with accuracy of 93.8%. In addition, the proposed scheme does not require external information to perform recovery bits. The proposed scheme was able to recover the tampered image with a PSNR value of 40.45 dB and a SSIM value of 0.994