Jurnal Penelitian Teknologi Informasi dan Sains

Sistem Informasi Geografis Pemetaan dan Analisis Lahan Pertanian di Kabupaten Deli Serdang

Ali Ikhwan — 2025-01-16

This research aims to develop a Geographic Information System (GIS) for mapping and analyzing agricultural land in Deli Serdang Regency, North Sumatra. The system was designed using the Rapid Application Development (RAD) method to speed up the development process and ensure the system meets user needs. The research results show that GIS is able to provide effective solutions to agricultural data management problems, such as mapping harvest area, potential empty land, and distribution of production results. in real time. With an easy-to-use interface, this system supports efficient crop distribution, data-based policy development, and sustainability of the agricultural sector. This research suggests developing additional features such as predictive analysis, user training, and regular evaluation to optimize the benefits of GIS in supporting sustainable agricultural development.

Analisis Bibliometrika Artikel pada Jurnal Info Bibliotheca Universitas Negeri Padang Tahun 2022 - 2024

Rahma Intan Oktiara — 2025-01-20

This study aims to describe the half-life and obsolescence level of literature used in the Info Bibliotheca Journal articles of Padang State University in 2022-2024. This study was conducted using a quantitative method with a descriptive approach. The entire population was sampled in this study, with a total sample of 48 articles. Data were collected, analyzed using the half-life and obsolescence formulas, and conclusions were drawn. The results showed that the expired citations were 411 citations (50.24%) and the most recent were 407 citations (49.67%). The expiration rate of literature in the Info Bibliotheca Journal articles of Padang State University is 7 years.

Perancangan Prototype Sistem Pendeteksi Stunting dengan Menggunakan Microcontroller Berbasis Sensor Ultrasonic dan Load cell

Fahmi Fadillah — 2025-01-30

Stunting disease describes abnormalities in a child's body caused by impaired physical growth. Research has been carried out on Stunting which produces the causal factors and long-term risks for Stunting sufferers. It is hoped that there will be technology that can detect Stunting growth early on in children, so that it can be treated quickly. Therefore, it is necessary to design a Prototype Stunting Detection System using a Microcontroller Based on Ultrasonic Sensors and Load cells which aims to identify Stunting factors for children in the Posyandu working area of Garut Regency. The methodology used is a Prototype Model and uses a black box testing method. As a result, the existence of this Stunting detection system Prototype contributes to Posyandu officers and children so that they can be detected early so that later prevention can be carried out so that it does not grow until the child is old, so that the percentage of Stunting growth can decrease.

Sistem PPDB Online Berbasis Web di MTs Negeri 3 Purworejo

Imam Tri Suryadin Imam — 2025-01-31

Acceptance of new students is one of the processes that exist in educational institutions such as schools which are useful for screening prospective students who are selected according to the criteria determined by the school to become their students. In general, the process of admitting new students is carried out through the stages of registration, selection tests, and announcement of student acceptance. In this research, its application to MTs Negeri 3 Purworejo, which has been done manually or online so far, but only uses the PPDB link, which allows for a lot of data shortages. The formulation of the problem of this research is how to create an information system for new student admissions at MTs Negeri 3 Purworejo. The methods used are literature, observation, analysis, design, testing and implementation. This new student admissions information system was built using the PHP programming language and utilizes the MySQL database as a database server. The result of this research is a web-based new student admissions information system that has the ability to make it easy for parents of prospective new students to obtain all information about new student admissions and carry out the online registration process.

Analisis Peminjaman Ruangan di Gedung Creative Center Sumedang Menggunakan Metode PIECES

Dipa Arya Pangestu — 2025-02-01

The utilization of information technology can provide benefits that are faster, more accurate, and more transparent. One application is in a room loan system that can avoid schedule clashes, increase user productivity, and make the administration process faster and more efficient. This research was conducted at the Sumedang Regency Tourism, Culture, Youth and Sports Office in the creative economy sector, which manages room loans at the Creative Center Sumedang Building. The current room loan system at the Creative Center Sumedang Building uses Google Form which experiences various obstacles, such as conflicting schedules and inefficient administrative processes. This study aims to evaluate and provide recommendations for a website-based system that is more structured and user-friendly to support room loan management. This research uses the PIECES (Performance, Information, Economy, Control, Efficiency, and Service) analysis method to evaluate the weaknesses of the current system and provide recommendations for website-based improvements with UI/UX design integration. Data was collected through observations and interviews with managers and users of room lending services. The results of the analysis show that a website-based system can improve the efficiency of room loan management, ensure a more organized schedule, and facilitate automatic data management. The proposed solution includes automatic room checking and a simpler interface design. With the implementation of an integrated and user-friendly system, room loan management is expected to become more effective and support optimal service.

Analisis Big Data untuk Prediksi Permintaan Produk dalam E-commerce

Sumita Wardani — 2025-02-22

The rapid development of e-commerce has generated huge volumes of data, opening up opportunities to analyze product demand patterns more accurately. This research aims to develop a product demand prediction model based on big data analysis. The data used includes sales transactions, product searches, customer reviews, and external factors such as seasons and promotions. The main methods used are machine learning techniques such as random forest regression and neural networks to build predictive models, with data extraction, transformation, and analysis processes carried out using big data platforms such as Hadoop and Spark. The resulting model is evaluated using accuracy metrics, such as mean absolute error (MAE) and root mean square error (RMSE), to measure prediction performance. The results show that the use of big data in product demand prediction can increase the accuracy of inventory planning and stock management by up to 25% compared to conventional methods. These findings make a significant contribution to the optimization of e-commerce operations, especially in more efficient and timely data-driven decision-making.

Implementasi Pengujian Kerentanan Windows 10 Menggunakan EternalBlue dan Phising

Muhammad Naufal Hafizh — 2025-03-03

Attacks on Windows can be carried out in various ways, one of which is exploiting SMBv1 vulnerabilities and phishing. Exploitation is an attack technique that takes advantage of system weaknesses. Windows 10 itself has vulnerabilities that can be exploited for hacking, which may include data theft, user data deletion, credential theft, and even damaging the Windows 10 system itself. A possible solution is to conduct penetration testing on the Windows 10 operating system. The testing is carried out based on the Cyber Kill Chain model, utilizing appropriate tools and following the stages outlined in the model. The test results indicate that Windows 10 vulnerabilities can be exploited, particularly through direct system attacks via SMBv1 with CVE-2017, codenamed EternalBlue, and phishing techniques that allow attackers to gain administrator privileges directly or inject malware into the target Windows 10 system.

TOWR Stock Forecasting From 2021-2025 Using Machine Learning

Andy Hermawan — 2025-03-13

Accurate stock price forecasting is a crucial yet challenging task due to the complex and dynamic nature of financial markets. This study employs the Prophet model to predict the stock prices of PT Sarana Menara Nusantara Tbk (TOWR) from 2021 to 2025. The research leverages historical stock data, incorporating dividend distribution dates and Annual General Meeting (AGM) events as external regressors to enhance predictive accuracy. The model was developed using machine learning-based time series forecasting, with hyperparameter tuning applied to optimize performance. The evaluation metrics indicate a Mean Absolute Error (MAE) of Rp49.92 and a Mean Absolute Percentage Error (MAPE) of 6.47%, demonstrating the model’s robustness in capturing long-term stock price trends. The findings suggest that stock prices exhibit significant movements around dividend announcement periods and AGM events, highlighting the impact of corporate actions on market behavior. This study reinforces the importance of incorporating fundamental financial indicators into forecasting models to improve decision-making for investors and financial analysts. The results offer practical implications for investment strategy formulation, risk management, and market trend analysis.

Implementasi Metode Multifactor Evaluation Process Pemilihan Guru Terbaik Pada SMP Darul Ulum Waru Berbasis Web

Kapindho Febriyanto — 2025-03-15

The decision support system for determining the best teachers at SMP Darul Ulum Waru aims to facilitate the selection and assessment of teacher performance. Currently, the selection of the best teachers still involves negotiations or discussions and has not yet been systematic in determining the best teachers. this process results in outcomes that appear subjective, as teacher evaluations are conducted every year in the even semester to boost the work spirit of each teacher in educating their students and to reward them for their achieved performance. To improve efficiency and accuracy, a system for selecting the best teachers is needed using the MFEP (Multifactor Evaluation Process) method, which is more flexible in determining the weight of criteria. In this method, more prioritized criteria receive greater weight and are easier to apply, making data processing faster. In the MFEP process, calculations are made using predetermined criteria, including politeness, work accuracy, orderliness, compliance, and work enthusiasm. Calculations will be conducted for each teacher based on the specified criteria and weighting, which will ultimately result in recommendations for the best teachers.In the MFEP system, the selection of the best teachers that has been created was tested 20 times manually with an accuracy of 85.88%.

Multi-Criteria Decision Support System for Web-Based Credit Approval: A Study of TOPSIS, MABAC, WASPAS, and MAUT Methods

Kadek Indah Permataa — 2025-03-21

The decision-making process in granting credit involves analyzing a series of alternatives using certain criteria.. The goal is to find the best alternative that meets these criteria. One method that can be used in the decision making process is Multi-Criteria Decision Making (MCDM) or Multi-Criteria Decision Analysis (MCDA). There are many MCDM or MCDA methods that can be used for decision making. This research aims to test the MCDM methods, namely TOPSIS, MABAC, WASPAS and MAUT in making decisions regarding credit acceptance. The dataset used in this research is data regarding credit acceptance with 5 criteria and 100 attributes. The method study was carried out by ranking all alternatives based on the best alternative and then comparing the ranking results of the four methods using Spearman and Kendall Tau rank correlations. And carry out sensitivity tests on the four methods to find the most sensitive method. The results of the comparison of the four methods show that there is a strong correlation between the MABAC and WASPAS methods. The sensitivity test results show that the TOPSIS method is the most sensitive method. Based on the correlation results, it can be concluded that the MABAC and WASPAS methods are the methods that produce the most similar rankings. Meanwhile, the most sensitive method is obtained by the TOPSIS method.