Journal Sensi: Strategic of Education in Information System

Employee Attendance Optimization Using QR Code Model with Reed Solomon Error Correction for Data Security and Accuracy

Aris Martono, Padeli Padeli, Muhamad Iip Suhaepi — Fri, 28 Feb 2025 00:00:00 +0000

This research aims to determine the process of creating a quick response code (QR code) model with Reed Solomon error correction for employee attendance at the Company. Fingerprint attendance systems, even though they are more sophisticated, still have disadvantages, such as difficulties in use in unhygienic environments, as well as high costs for installing the device. Apart from that, traditional attendance is also less flexible in managing employees who work in the field or employees who do not work in the main office. Companies that have many branches or employees who work outside the main office often have difficulty monitoring absenteeism effectively and accurately. The mechanism of this QR code model is carried out through several steps, namely: coding QR codes based on employee ID numbers, grouping encoder data every 8 bits, converting encoder data to binary format, error correction using the Reed Solomon algorithm, creating error correction codes (EC). ) in polynomial form, calculating error correction data based on the correspondence and index of integer numbers in the Galois Field (GF), calculating the function f′(x) through an iterative division process until completion, determining the remainder of the division in the form of R(x), as well as merging encoder data with error correction code as result end. With this mechanism, the QR code-based attendance system is able to maintain data security and accuracy while minimizing the occurrence of anomalies during the work attendance process.

Use of Residual Network (ResNet) for Disease Classification in Potato Leaves

Ichsan Haikal, David Hasiholan Nadeak, Lukman Hakim — Fri, 28 Feb 2025 00:00:00 +0000

Diseases in potato plants can have serious impacts on crop yield and overall plant health, threatening the sustainability of agricultural production. To enhance the accuracy and efficiency of potato leaf disease detection, this study proposes a new approach utilizing Residual Network architecture, a promising technique in image analysis. The dataset used is sourced from the public Kaggle repository, providing the necessary diversity to effectively train the model. The process of splitting the dataset into training and testing data is essential to optimize the performance of the Residual Network algorithm, ensuring that the model can generalize disease patterns well. The research findings highlight that Scenario 1, which adopts a training-to-testing data ratio of 90:10, emerges as the most optimal choice. In testing, this scenario demonstrated superior performance compared to other scenarios, achieving the highest accuracy rate of 76%, indicating its promising performance in classifying data with high accuracy. These results suggest significant potential for this approach in practical applications for effective and efficient potato leaf disease detection, thereby enhancing agricultural productivity and ensuring food security.

Visual Analysis Of Body Signals In Smoker Data To Understand Health Impacts On Python

Fri, 28 Feb 2025 00:00:00 +0000

In this study, researchers found that 44.4% of people had blood pressure less than 120/80, 58.2% had fasting blood sugar <= 99, 47.7% had hemoglobin > 17.2, and 62% had oral problems and teeth caused by smoking. This research was carried out by visualizing the impact of smoking on blood pressure, fasting blood sugar, hemoglobin and the mouth and teeth in the body using body signal of smoking data obtained from Kaggle which was analyzed and presented in the form of a pie chart using Python.

Implementation of Information Gathering Method in Academic Information System (SIAKAD)

Fifit Alfiah, Ade Setiadi, Marsela Marsela, Devina Syahdan, Sadrina Natasya — Fri, 28 Feb 2025 00:00:00 +0000

With the rapid development of information technology today, we must continue to follow the development of the digital transformation era, where educational institutions need a strong system to manage information efficiently. Academic Information Systems are an important framework that helps educational organizations simplify their functions, improve communication, improve student services, process student and teacher data in schools, and support decision-making processes. The purpose of creating this system at Avicena Rajeg Vocational School is to facilitate the administrative process, especially data management because previously there was no system to help students and teachers manage data. The authors used information gathering methods to conduct their research. This method collects data from the authorities to find out the root cause of the problem, and then analyzes the data. In order to obtain the data, the authors conducted direct observations in schools, the collection and study of documents—documentation that will help with this research—and interviews with relevant parties in schools are necessary. At this point, some problems were found with the management of school data and solutions to these problems. The results of this research will help in the development of a more efficient academic information system. The result is that with a data management system for teachers and students, everything will be more organized and more informed.

Optimizing Workforce Scheduling Using Ant Colony Optimization Algorithm: Case Study PT. Cloud Hosting Indonesia

Gagas Nurfilae Nurfilael, Agung Mulyo Widodo, Nizirwan Anwar, Arief Ichwani — Fri, 28 Feb 2025 00:00:00 +0000

Effective workforce scheduling is crucial for enhancing productivity and maintaining service quality at PT. Cloud Hosting Indonesia. Workforce scheduling is the process of organizing and allocating labor to various tasks and responsibilities within an organization. Ant Colony Optimization (ACO) is a probabilistic technique used to solve computation problems by finding the best path through a graph. Inspired by the behavior of ants, particularly how they find food, Ant Colony Optimization can optimize shift schedules, reduce conflicts, and improve employee performance. However, there are current irregularities, insufficient rest periods, and unpredictable holidays. Ant colony optimization is applied to address these problems. The result of this shows that the Ant Colony Optimization algorithm is capable of producing more optimal schedules with high efficiency, achieving a Best Cost of 100 in 1 minute and 6 seconds. This is better compared to other methods such as Particle Swarm Optimization (PSO), which achieved a Best Cost of 7600 in 4 seconds, and Genetic Algorithm (GA), which achieved a Best Fitness of 8500 in 5 seconds.

Efforts To Increase The Efficiency Of Wireless Power Transfer (Literature Study)

Jawahir Jawahir — Fri, 28 Feb 2025 00:00:00 +0000

One of the important issues in the electric power system is the problem of distributing electrical energy from one place to another which is relatively expensive. In addition to requiring many cables/conductors and a good protection system, the installation is also not easy. Therefore, the cost of installing the distribution channel will be expensive. In addition, the stretch of cables/conductors can interfere with the beauty of the room. For this reason, experts have conducted research for quite a long time to design an electrical energy distribution system that can be used to distribute electrical energy without using cables or wirelessly. With this wireless system, in addition to saving cable material costs and maintenance costs, it can also reduce heavy loads. In addition, the stretch of cables/conductors does not interfere with the beauty of the room.

Wireless Power Transfer System (WPT) is a system for distributing electrical energy from one place to another without using cables. In other words, the system for distributing electrical energy from one device to another without passing through physical media in the form of electrical cable/conductor channels. With the development of WPT technology, the electrical energy distribution system that occurs can be more efficient and easier to install.

Many studies have been conducted by experts to improve the efficiency of the power distributed. Efforts that have been made are for example by adding a barrier (shielding), adding metamaterials, making coil designs in circular and hexagonal shapes, using antennas made of aluminum or copper, and so on.

With the results of this study, it is hoped that one day this wireless electrical energy distribution technology can be implemented with high efficiency.

Data Analysis of Thesis Guidance Students Using Random Forest, Gradient Boosting, and Naïve Bayes Algorithms (Case Study: University of Raharja)

Fajar Nur Iman, Tukiyat Tukiyat, Taswanda Taryo — Fri, 28 Feb 2025 00:00:00 +0000

Thesis guidance is a crucial stage in higher education, as the thesis is one of the primary requirements for earning a bachelor's degree. One of the main challenges in thesis guidance is managing consultation data between students and their supervisors. The application of technology and machine learning approaches offers significant potential in addressing this issue. Machine learning algorithms such as Random Forest, Gradient Boosting, and Naïve Bayes can be utilized to automatically analyze thesis guidance data, thereby assisting supervisors in efficiently monitoring student progress. This research aims not only to provide a solution for supervisors in monitoring the progress of their students but also to offer a valuable tool for university management to evaluate the performance of supervisors in providing guidance. Based on the results and comparisons conducted, it can be concluded that the Gradient Boosting method achieves the highest accuracy, reaching 100%, compared to Random Forest with an accuracy of 98.8% and Naïve Bayes with an accuracy of 97.4%. From the testing data results using the Naïve Bayes, Gradient Boosting, and Random Forest algorithms, different accuracy levels were observed. However, the prediction outcomes were consistent: out of 235 testing data, 25 data points were classified as "Not Eligible," and 210 data points were classified as "Eligible" based on the established criteria.

Development of Mobile Location Based Service Application for Searching for Nearest AC Service

Asep Yayat, Iksan Ramadhan, Riya Widayanti, Adi Widiantono — Fri, 28 Feb 2025 00:00:00 +0000

Air Conditioner (AC) in the current era has become a necessity in everyday life for use in various activities. Over time, the AC can cause damage generally because it is used frequently, so regular maintenance is needed so that the AC continues to run well and optimally. The problem faced when seeking AC maintenance is difficulty in finding the nearest AC service, so a system is needed that can search according to the customer's location. This search uses a location based service by utilizing the Google Maps API and is mobile based to display location data mapping to see the nearest AC service point. Based on the test results using user acceptance testing, a final score of 93.8% was obtained in the "Very Good" category so that the application runs well and as it should.

Implementation of E-Government with the RESTFUL API Method on the Population Data Management System in Pasar Kemis District

Arsi Yulianjani, Gede Dito April Yanto Wijaya, Anthonius Christopher — Fri, 28 Feb 2025 00:00:00 +0000

Pasar Kemis currently uses a manual system for population data, leading to issues like slow data collection and difficulty searching. To improve efficiency, they propose a new web-based system built with PHP and CodeIgniter. This system will use Restful API for data exchange and be tested with Black Box Testing. Researchers gathered information through observation, interviews, and documents. UML will be used for system design, and prototyping with Adobe XD will help analyze advantages and disadvantages. The goal is to replace the traditional system with a computerized one for easier data entry, research, and report generation, ultimately benefitting the district government.

Optimization of Salary System Application for Financial Department Performance Efficiency

Sri Rahayu, Mukti Budiarto, Najalia Malika — Fri, 28 Feb 2025 00:00:00 +0000

Rapid advancements in technology compel individuals and organizations to adapt to the ongoing shifts. One significant example of technological advancement is the increasing adoption of computerized work systems across various companies. PT Aliansi Global Manufaktur, a local shoe manufacturing company, is currently navigating this technological shift. The study originates from the company’s reliance on a manual payroll data management system. Such a manual approach presents several challenges, including susceptibility to errors, time and energy inefficiencies in data processing, and extensive storage space requirements. This study utilizes the PIECES analysis framework, which evaluates aspects such as Performance, Information, Economy, Control, Efficiency, and Service. For the design phase, it employs Unified Modeling Language (UML) alongside PHP programming with the Codeigniter framework for system development and a database for data storage. A proposed solution to address these challenges is the development of a web-based payroll system, aimed at reducing errors in salary calculations and simplifying the payroll process.