Jurnal Bangkit Indonesia

Enhanced Data Security Using 5x5 Hill Cipher with Modular 53

2024-12-21T15:24:40+07:00

This research presents an optimized approach to the Hill Cipher encryption and decryption algorithm using a 5x5 matrix and modular 53 arithmetic. The traditional Hill Cipher, a well-known symmetric key algorithm, typically utilizes smaller matrices and modular arithmetic, which may not provide sufficient security for contemporary applications. By expanding the key matrix to a 5x5 structure and adopting a larger modulus of 53, the complexity and security of the cipher are significantly enhanced. The study details the methodology for constructing and implementing the 5x5 key matrix, as well as the processes for encryption and decryption under the modular 53 system. The computational efficiency and security improvements achieved through this optimization are analyzed. Comparative assessments with the conventional Hill Cipher demonstrate that the enhanced approach offers superior resistance against cryptographic attacks while maintaining manageable computational requirements. The results of this research indicate that the proposed optimized Hill Cipher can serve as a robust encryption method suitable for securing sensitive data in various modern applications. This study contributes to the field of cryptography by providing a more secure and efficient variant of the classical Hill Cipher algorithm

Klasifikasi Stingless Bee Menggunakan Metode Image Classification Berbasis OpenCV

2024-12-21T15:25:03+07:00

Stingless bees play an important role as natural pollinators in ecosystems and as producers of economically valuable products such as honey, propolis, and bee bread, which are utilized in the food and health industries. Identifying stingless bee species remains a challenge due to the many species with similar morphology, requiring more efficient and accurate methods. This study aims to develop an automatic system based on image processing technology for the identification of stingless bee species using Convolutional Neural Networks (CNN), TensorFlow, and the Single Shot MultiBox Detector (SSD) implemented with OpenCV. The test results showed that the developed system was capable of automatically detecting and classifying stingless bee species with an average accuracy of 98%, especially when the object was directly aligned with the camera. Out of 40 tested samples, 31 samples were recognized, and 9 samples were not, resulting in a success rate of 77.5%. Factors influencing detection success include the quality of training data, camera positioning, and morphological similarities between species.

Rancang Bangun Sistem Pembuangan Air Otomatis Pada Kapal Pompong Nelayan Menggunakan Tenaga Surya Berbasis Internet Of Things

2024-12-21T15:24:29+07:00

The automatic water disposal system on fishing boats is an innovative solution to overcome the problems often faced by fishermen related to water leaks and manual water disposal which requires a lot of time and effort. This research aims to design and build an automatic water disposal system on a fishing boat by utilizing solar power as a renewable energy source and based on the Internet of Things (IoT) to enable remote monitoring and control. This system uses a water level sensor to detect the water level inside the ship and activates the water pump automatically when the water level reaches a certain point. Solar power is used as the main energy source to power the system, making it more environmentally friendly and reducing dependence on fossil fuels. Integration with IoT allows fishermen to monitor vessel conditions and control the system via smartphone, thereby increasing safety and operational efficiency. Data collection methods used in this research include interviews with fishermen, field observations, and literature studies related to the technology used. Meanwhile, the system development method uses the Agile Method, which allows fast iteration, close collaboration with end users (fishermen), and adjustment to changes during the development process. The Agile method ensures that the system developed meets the real needs of fishermen and can be adapted to changing field conditions. The research results show that the automatic water disposal system can work effectively, efficiently and safely in removing water that enters the ship. This system helps fishermen save time, energy and operational costs by reducing the need to drain water manually. Apart from that, the use of solar power as an energy source also contributes to efforts to preserve the environment by reducing carbon emissions from burning fossil fuels. Thus, this system offers a profitable solution for fishermen and the environment.

Analisis Klasifikasi Citra Penokohan Topeng Bali Menggunakan Model EfficientnetV2 Dan Xception

2024-12-21T15:25:14+07:00

Abstract— Bali is one of the provinces with quite complex cultural diversity in Indonesia. One of them is the characterization of traditional masks. Traditional masks in Balinese tradition are not only intended as performance accessories, but also as symbols of characterization, social status in indigenous communities, rites, and certain primordial activities. Every detail in the curve of the carving on the Balinese mask indicates an aesthetic richness that is certainly measurable as an ontological entity. In this case, the magnitude of this aesthetic measurability can be assisted by using various computational methods. This study tries to create a machine learning model with supervised learning to create a classification system for Balinese mask characterization. The methods used include: processing mask images into a 3-dimensional vector, each representing the red, green and blue color indices. Then each vector will go through a training process to create a measurability model for each characterization. The models used are EfficientNetV2 and Xception which are developments of convolutional models. The performance measurement metrics used are Accuracy, Precision, Recall & F1-Score. The Xception model produced an accuracy of 97%, while the EfficientNetV2 model produced an accuracy of 99%.

Keywords— Bali, Classification, EfficientNetV2, Mask, Xception

Tata Kelola Evaluasi Teknologi Informasi Menggunakan Framework Cobit 2019 Pada Kantor Wilayah Kementerian Hukum dan Hak Asasi Manusia Provinsi Kepulauan Riau

2024-12-21T15:25:26+07:00

Information technology which is developing rapidly at this time greatly influences the company's business conditions so that information technology governance is needed. COBIT 2019 is an information technology governance framework that has standards for implementing information technology governance. The Regional Office of the Ministry of Law and Human Rights, Riau Islands Province, is a government company that operates in the field of legal and human rights services. The aim of this research is to determine the current level of IT process capability (as-is) and the expected level of IT process capability (to-be) as well as providing recommendations and suggestions on better IT governance for the Regional Office of the Ministry of Law and Human Rights, Riau Islands Province. This research was conducted using standards framework COBIT 2019. From the existing process objectives, 8 objectives were obtained that were in accordance with the research, namely APO04 – Managed Innovation, APO07 – Managed Human Resources, APO13 – Managed Security, BAI02 – Managed Requirements Definitions, BAI03 – Managed Solutions Identification and Build, DSS03 – Managed Problems, DSS05 – Managed Security Services, MEA01 – Managed Performance and Conformance Monitoring, EDM01 – Ensured Governance Framework Setting and Maintenance. The results of this research show that the APO04 and EDM01 process objectives are at the capability level level 4 (as-is) with a capability value of APO04 and EDM01 of 100%, for DSS03 and MEA01 it is at the capability level level 5 (as-is) with a DSS03 and MEA01 capability value of 100%, for APO07 and APO13 it is at the capability level level 2 (as-is), and for domains BAI03 and DSS05 are at the capability level level 1 (as-is).

Sistem Pengelolaan Payroll Dosen Dengan Metode Gross Up ( studi kasus : STMIK bandung)

2024-12-21T15:26:00+07:00

The lecturer payroll management system using the gross up method is a method for calculating lecturer salaries in which the income tax that must be paid by the lecturer is added to the lecturer's gross salary, so that the amount of income tax that must be paid is the responsibility of the university or institution where the lecturer is located. Work. In its application, the gross up system makes it easier to calculate and pay lecturer salaries because the institution where the lecturer works will bear the costs of the lecturer's income tax. In this case, the institution will calculate the lecturer's income tax first, then add the tax amount to the lecturer's gross salary so that the lecturer receives a net salary which has been calculated and includes income tax costs. The system was designed using UML UML which includes use case diagrams, activity diagrams and sequence diagrams, and was built using Larvel version 10 and for the database using MySQL. It is hoped that with this system the tax burden will decrease and lecturers' take home pay will increase.

Sistem Presensi menggunakan Deteksi Objek Wajah Mahasiswa Berbasis YOLO-V5

2024-12-21T15:25:49+07:00

Attendance is a crucial aspect across various sectors, such as corporate, governmental, and educational institutions, for efficient management. The advancement of deep learning technology, particularly in the field of facial recognition, has become a primary focus in enhancing identification accuracy. In this context, visual object detection through computer vision plays a key role, with the You Only Look Once (YOLO) method emerging as a leading choice for real-time object detection across various media, including webcams, due to its speed and efficiency. This research proposes the application of YOLO-V5 in the development of a student attendance system. This approach utilizes deep learning and data augmentation to enhance the accuracy of student identification. YOLO-V5 enables efficient real-time object detection, achieving an accuracy rate of up to 95% on each frame. The implementation of the student attendance system using the YOLO-V5 method successfully detects student attendance in real-time with a high level of accuracy. This demonstrates the potential of this method to improve the efficiency of attendance management and its suitability for integration into student attendance systems. This research represents a significant advancement in the use of deep learning and computer vision to increase the accuracy and efficiency of attendance management

Perancangan Sistem Informasi Akuntansi pada CV. KA

2024-12-21T15:24:52+07:00

Processing accounting data on CV. KA still has problems, because recording the same data in several books can result in writing errors due to employee boredom and physical fatigue. The process of publishing reports still involves copying data and calculations which can also produce inaccurate information. This certainly has a negative impact on the company if the reports used as decision-making material still contain incorrect information. To overcome this obstacle, the researcher proposes creating an accounting application system according to the accounting flow that applies to CV. KA. In the initial stage, the researcher proposed a design for an accounting information system that would be implemented in the form of entity relationship diagrams, data flow diagrams, and use case diagrams, starting with posting the ledger, compiling a work sheet, compiling a balance sheet, compiling profit and loss calculations, and compiling a balance sheet. closing balance.

Pelaporan Dan Pencegahan Kekerasan Seksual Berbasis Web

2024-12-21T15:25:38+07:00

Kekerasan seksual di lingkungan kampus merupakan isu yang membutuhkan penanganan serius dan khusus. STMIK Bandung sebagai institusi pendidikan tinggi berkomitmen untuk menyediakan lingkungan belajar yang aman dan nyaman bagi seluruh civitas akademika, sesuai dengan amanat Permendikbud Ristek No. 30 Tahun 2021 Pasal 6 Ayat (1) yang mewajibkan pembentukan Satuan Tugas Pencegahan dan Penanganan Kekerasan Seksual (Satgas PPKS). Penelitian ini bertujuan untuk mengembangkan platform web yang mendukung pelaporan dan pencegahan kekerasan seksual di STMIK Bandung. Tujuan penelitian meliputi: (1) mempelajari prosedur pelaporan kekerasan seksual yang diterapkan oleh Satgas PPKS, (2) merancang platform web untuk pelaporan dan pencegahan kekerasan seksual, serta (3) menguraikan prosedur tindak lanjut yang dilakukan Satgas PPKS setelah menerima laporan. Pengumpulan data dilakukan melalui observasi, wawancara, dan studi pustaka. Platform web dikembangkan menggunakan framework Laravel dengan metode Scrum, yang terintegrasi dengan basis data untuk memastikan pengelolaan data pelaporan yang efisien dan aman. Hasil penelitian menunjukkan bahwa platform web yang dikembangkan memungkinkan pelaporan kekerasan seksual secara aman dan efektif, serta mendukung pengelolaan laporan oleh Satgas PPKS. Platform ini diharapkan dapat meningkatkan kepercayaan dan keberanian dalam melaporkan kasus kekerasan seksual, sekaligus memperkuat upaya pencegahan dan penanganan di STMIK Bandung.