JURNAL TEKNOLOGI DAN OPEN SOURCE

Modeling User Interface Design E-Business Applications for Marketing Umkm Products in Payakumbuh City Using Pieces Framework

Rabby Nazli — 2024-11-19

Micro, Small and Medium Enterprises (MSMEs) are productive economic enterprises that make a very significant contribution to the process of spurring the development of Indonesia's economic growth. On the one hand, the development of information technology is also growing very quickly. Therefore, managing micro, small and medium enterprises (MSMEs) businesses by utilizing digital technology is now an important part of increasing the competitiveness of micro ,small and medium enterprises (MSMEs) so that they are able to compete with other industry players. The aim of this research is to design an e-business design that can be used to improve business development performance in order to achieve its competitive targets so that it is able to compete with competitors in Payakumbuh city MSMEs. The framework used to analyze design feasibility tests is the PIECES Framework, which includes performance, information, economics, control, efficiency, and services. This method is used to measure the level of satisfaction with using the e-business system in managing MSME businesses in the city of Payakumbuh. The results of this research are in the range 3.4 – 4.91 = satisfied, so the design of the Payakumbuh City MSME e-business application is suitable for implementation in an application form that can be used by Payakumbuh City MSMEs and later used for testing the developed e-business system.

Recommendations for Selection of Skincare Products Using the Promethee Method

Muhammad Aufa Zaydan Azfar — 2024-12-01

This research aims to implement the Promethee method (Preference Ranking Organization Method for Enrichment Evaluation) in recommending appropriate skincare products based on facial skin type. With so many skincare products on the market, consumers may have difficulty choosing the right product. The Promethee method helps make multi-criteria decisions by considering various relevant factors such as skin type, price, user ratings, product quality, and price suitability based on the preferences of people who have used skincare products before as a reference in recommending skincare products. Recommendations are made based on data from the preferences of students who have used skincare products and provide an assessment of the products they have used. Researchers used the Promethee method as research to see how effective its use is in providing skincare product recommendations. The data used as a basis for manual calculations uses 10 data points for normal skin types. With the highest net flow value for normal skin types of 3.44444444 for Wardah Lightning and Ponds Men products. The highest net flow value for combination skin type is 24.250000, net flow for oily skin type is 14.222222, net flow for sensitive skin type is 14.722222, and net flow for dry skin type is 8.166667. The research results show that the Promethee method can provide appropriate recommendations regarding the selection of skincare products based on facial skin type.

Design of an Android Based Garbage Transport (Angkut's) Application

Muhamad Alda — 2024-12-01

The waste problem in urban areas, such as Belawan, Medan, is exacerbated by population growth and inadequate waste management systems, resulting in environmental degradation. To address this issue, "Angkut's," an Android-based waste transportation application, has been developed. The system aims to optimize waste management through the use of digital technology, allowing users to schedule and monitor waste collection efficiently. This application addresses inefficiencies in the existing waste transportation system by incorporating features like real-time order tracking and notifications for both users and administrators. The prototype for Angkut's was developed using prototyping methodology, which includes stages such as communication, quick planning, quick design modeling, prototype construction, and deployment feedback. The application includes various user-friendly interfaces, such as a splash screen, login, home, and order management pages. Administrators can monitor order statuses and provide updates on waste collection. The system also promotes community empowerment in waste management by using a structured approach to managing inorganic waste. After development, the prototype underwent testing to evaluate user responses and functionality. This application is expected to improve waste transportation efficiency, benefiting both the community and local governments.

Implementation of a Mobile Based Mount Kerinci Climbing E-Ticket Booking System to Optimize Route Quota Management

Dilan Nanda Pratama — 2024-12-01

Mount Kerinci is one of the highest mountains in Indonesia that attracts many climbers every year. Proper management of climbing quotas is needed to maintain a balance between the number of climbers and environmental sustainability. However, the manual system currently used often causes uncertainty in quota availability, overbooking, and errors in calculation. To overcome this problem, this study develops an Android-based mobile application that uses the Rapid Application Development (RAD) method for booking climbing e-tickets. This application is designed to provide transparency and efficiency in managing climbing route quotas, allowing climbers to book tickets in real-time and helping managers manage quotas more effectively. This innovation is expected to optimize climbing quota management and improve the climber experience

Building A Powerfull File Specification Application For Database System Design

Mohammad Syamsul Azis — 2024-12-01

The database is a collection of data that is well organized so that the data is easy to store, access and manipulate. Each database can contain all databases, or it can contain any number of database objects, such as files or tables. The purpose of the database was to organize data/organize data so that it is easy to obtain, accurate, and speedy in data retrieval, so that there was no duplication of data and the data is easy to maintain. Database has an important role to build an application. To build an application, valid data is needed so that the data synchronization of the application made with the designed database can be connected so that the data structure and data manipulation that occurs according to needs. The initial stage in making this program is analysis. The analysis was done by designing the program using diagrams. The method used in this research was the prototyping method. The diagrams used are Use Case Diagrams and Activity Diagrams. The result of this research is the application was made according to the needs of the users. In addition to being easy and practical, users found it very helpful because it saved time in making specification files, which were originally quite complicated and took a long time to make, now with this application file specifications could be made easily and quickly.

Designing UI/UX App for Parents of ASD Children through Social Approach

Anggis Rizky Wiyaringtyas — 2024-12-01

Compared to children’s parents with typical conditions, parents of children with autism spectrum disorder (ASD) experience higher levels of stress. As a result, parents may become more at risk of social stigma and become apart from those who seem can't understand their situation. Parents' stress levels can be reduced by experiencing a positive response like happiness and comfortable. One of the factors that makes parents of children happy and comfort with ASD is social support. In this study, researchers developed a smartphone application that can provide social support—such as groups, information, and emotional support—to parents who have children with ASD. The design thinking approach was implemented in this study, which involved collecting data via surveys, interviews, and observations to designing the UI/UX application during the ideation phase. According to the study's findings, parents nowadays need a parenting app that can make it easier for them to find social support.

Implementation of Python-Based Topsis Method for Best Stock Selection Analysis Using Yahoo Finance

Kristian Gunawan — 2024-12-01

This study developed a web-based application implementing the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method for stock investment analysis and recommendations. The application was built using the Flask framework and integrated with the Yahoo Finance API for real-time stock data retrieval. The TOPSIS method evaluated stock alternatives based on criteria such as closing price, P/E ratio, revenue growth, and dividend per share. Testing included functional evaluation, response time analysis, and simulations of three investor scenarios: High Risk-High Return, Low Risk-Low Return, and Balanced. Results indicate that the application effectively delivers stock recommendations aligned with investor preferences, achieving an average response time of 1–4 seconds per feature. Simulations highlight its adaptability in adjusting criteria weights to match different risk profiles. Despite limitations due to external API dependencies, the application demonstrates effectiveness as a decision support tool for stock investment, offering accessibility and flexibility to investors.

Naive Bayes Algorithm Classification for Predicting Graduation Rate

Pradani Ayu Widya Purnama — 2024-12-03

Classification refers to the process of identifying a model or function that clarifies or differentiates concepts or categories of data, with the goal of predicting the class of an object. Naïve Bayes is a machine learning technique that employs probability computations. In this case study, various algorithms are used for modeling classification, and the naïve bayes algorithm is applied to examine the graduation rate. By utilizing this method, accuracy is assessed, which allows for an analysis based on criteria such as School Major, First Choice of College, Second Choice of College, Average Graduation Value, and Graduation Information. The outcome of the computation utilizing the Naïve Bayes Algorithm (Information Systems | Option 1) > (Information Engineering | Option 2) is 53.32% > 0%, which allows us to infer that the First Option of Information Systems and the Second Option of Informatics Engineering yield an Average Score of 75.00, resulting in a Graduation Information status of PASS, thus, Information Pass (Option 1-Information Systems).

Measuring the Quality of the General Election Commission Website in Central Jakarta Using the WebQual 4.0 Method

Naufal Brilianto — 2024-12-05

This study aims to analyze the application of the Webqual 4.0 method in measuring the quality of the Central Jakarta City General Election Commission (in Indonesia it is abbreviated as KPU) website. This method focuses on three dimensions of usability quality, information quality, and interaction quality. This study uses a quantitative method with primary data. The sample of this study were employees and the general public. The data analysis technique used was multiple linear analysis processed using the SPSS version 26 program. The results of the study showed that the usability variable did not have a significant effect on website quality measurement. The Information Quality variable did not have a significant effect on website quality measurement. And the Interaction Quality variable had a significant effect on website quality measurement.

Analysis of the Impact of Open-Source Software on Reducing the Use of Pirated Software by Educators

Basrul Abdul Majid — 2024-12-13

One of the motivations for using pirated software can be caused by the need for more awareness of the importance of respecting the intellectual property rights of the software. Even in the college environment, there is software piracy. Educators and students freely use illegal software. While mean it is an environment for intellectuals and academics to gather, a place to study up to the highest level of education. This area should become an example for the surrounding community in respecting the copyrights of other things. One alternative to reduce the emergence of acts of using pirated software is to use open-source software. It is a free software version to use at will without pirating it. In this study, we want to know the influence of motivation in using pirated through the presence of open-source software. The data taken is among educators, as many as 86 randomly selected respondents. The data is processed quantitatively with the regression method. The results showed that the motivational factor in pirated software did not tremendously affect the factor of open-source software. It is only 14%, and the rest had no effect.

Application of Deep Learning Algorithm to Detect Fraud in Online Transaction Networks

Ridwan Dwi Irawan — 2024-12-29

Online transaction fraud is a severe problem that may cost businesses and people a lot of money. This paper suggests using deep learning algorithms to detect fraud as a remedy to this issue. These algorithms were chosen based on their ability to handle large amounts of intricate data and identify patterns that are difficult to identify using traditional techniques. Important components of this research include gathering and preprocessing transaction data, creating deep learning models, and assessing model performance. This investigation examines a variety of financial transaction types that may have involved fraud. The deep learning approach uses deep neural network designs, including Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN), to maximize detection accuracy. The study's findings demonstrate that the deep learning models created are excellent at identifying questionable transactions and can lower the false positive rate, which raises the overall effectiveness of fraud detection systems. As a result, deep learning algorithms have demonstrated a high degree of efficacy in identifying fraudulent activity inside internet-based transaction networks, so they play a vital role in fraud prevention.

Development Of Android-Based Applications With An Inquiry Approach On Solubility Material And Solubility Products As A Source Of Independent Learning For High School Students

Jakub Saddam akbar — 2024-12-29

This study aims to develop an Android-based application that uses an inquiry approach on solubility material and solubility products, and assesses its feasibility as an alternative source of independent learning for high school students. The approach used is the development research method, by choosing a development design using the ADDIE model. The result of this study is in the form of an Android-based application. The evaluation of the results of this development is based on the assessment of validators who show very good categories, with ideality reaching 86% according to the assessment of media experts, and 84.75% according to the assessment of material experts. Student responses to Android-based applications with an inquiry approach to solubility material and solubility results obtained a percentage of 93.22%. Based on the expert assessment and student responses, it can be concluded that the Android-based application that has been developed is worthy of being used as an independent learning resource for high school students.

Implementation of the K-Means Clustering Method for Selecting Pencak Silat Athletes at the North Sumatra KONI

Abdi Alamsyah — 2024-12-29

This article discusses the application of the K-Means clustering method in the selection of pencak silat athletes at the North Sumatra Koni. The study aims to improve the efficiency of the selection process, which was previously carried out manually, by classifying athletes based on attributes such as age, weight, and physical ability. K-Means clustering is used to group athletes into three categories: very suitable, suitable, and unsuitable. The methodology includes determining the number of clusters, calculating centroids, and analyzing Euclidean distances for data clustering. The results of the study showed that this method was effective in classifying 394 athletes in the "unsuitable" category, 354 athletes in the "suitable" category, and 376 athletes in the "very suitable" category. This study is expected to support the athlete selection process more systematically and efficiently. Recommendations for further research include the use of additional criteria and exploration of other clustering methods for more optimal results.

Digital Fish Image Segmentation Using U-Net for Shape Feature Extraction

Fathorazi Nur Fajri — 2024-12-29

Segmentation of digital images of fish is an important challenge in image processing in the field of marine biology and aquaculture. Extraction of fish shape features through image segmentation can improve accuracy in species identification and fish population monitoring. The U-Net method, which is based on deep learning, has been proven effective in medical image segmentation and is beginning to be applied in fish image segmentation. This study aims to develop a fish digital image segmentation method using U-Net architecture for accurate and efficient fish shape feature extraction. The dataset used consists of 500 fish images of various shapes and sizes collected from various sources. The fish images were processed using a U-Net artificial neural network, which was trained and tested to obtain the best segmentation results, with evaluation using Intersection over Union (IoU). The segmentation results show that the U-Net method can produce precise segmentation, with a high degree of accuracy in extracting fish shape features. Evaluation of the segmentation metrics resulted in an IoU value of 0.88, indicating excellent performance in distinguishing the fish object from the background and accurately mapping the fish shape. The fish digital image segmentation method using U-Net is effective for fish shape feature extraction and can be applied in fish species identification and aquatic ecosystem monitoring.

Design of Rainfall Intensity Measuring Instrument Using IoT-Based Microcontroller

Nofri Wandi Al-Hafiz — 2024-12-30

The design of a rainfall intensity measuring device utilizing an Internet of Things (IoT)-based microcontroller aims to offer a more precise, efficient, and real-time solution for rainfall measurement compared to the traditional manual systems. While manual systems are still commonly used, they have significant limitations, including reliance on human observation, slow response times, and measurement inaccuracies. In this study, the designed tool incorporates a tipping bucket rain sensor connected to an ESP32 or ESP8266 microcontroller and a Wi-Fi module to transmit real-time data to a cloud-based IoT platform. The collected data is processed and visualized through graphs accessible via web or mobile applications. This system facilitates continuous rainfall monitoring and provides fast, accurate information that can be applied to disaster mitigation, agricultural planning, and natural resource management. By leveraging IoT technology, this system addresses the shortcomings of manual methods, offering considerable benefits for more timely and data-driven decision-making.

Classification Of Rice Plant Diseases Using K-Nearest Neighbor Algorithm Based On Hue Saturation Value Color Extraction And Gray Level Co-Occurrence Matrix Features

Siti Saniah — 2024-12-30

This research aims to classify diseases in rice plants using the K-Nearest Neighbor (K-NN) algorithm based on Hue Saturation Value (HSV) color feature extraction and Gray Level Co-Occurrence Matrix (GLCM) texture. The main problem faced is how to identify the type of disease in rice plants automatically using digital images. Diseases such as Blight, Tungro, and Crackle often attack rice plants and require an accurate early detection system. Lack of understanding in recognizing disease symptoms manually often leads to errors in handling. For this reason, this research develops an image processing-based classification system that can detect diseases such as Blight, Tungro, and Crackle. The method used in this research is image processing which includes RGB to HSV color space conversion, texture feature extraction using GLCM, and classification using K-NN algorithm. The dataset consists of 240 images, divided into training data and testing data, namely 192 training data and 48 testing data. Tests were conducted by calculating accuracy at various values of the K parameter, namely K = 1, K = 3, and K = 5, to determine the effectiveness of the model in classifying plant diseases. The purpose of this study was to evaluate the accuracy of the system in identifying rice diseases and test the combination of HSV and GLCM features in improving classification performance. The results showed that using HSV and GLCM features together resulted in the highest accuracy at K=3 with an accuracy value of 75%. The system is expected to assist farmers in detecting plant diseases quickly and effectively, thus minimizing production losses and supporting agricultural sustainability

Application of the C4.5 Algorithm for Predicting Banana Chips Production Demand (Case Study at UD. Sinar Sejahtera Medan)

M. Teguh wijaya — 2024-12-30

The rapid advancement of science and technology significantly impacts various aspects of life, including business operations. Technology plays a vital role in providing information and simplifying human tasks, addressing challenges faced by growing companies, particularly in managing sales fluctuations. Factors such as market competition, product quality, and consumer interest are critical for evaluating and improving sales strategies. UD. Sinar Sejahtera Medan, a food processing industry specializing in banana chips, faces challenges such as fluctuating raw material supply, impacting production and sales. To address this, a prediction system for raw material demand was developed, leveraging the C4.5 algorithm. The C4.5 algorithm was selected for its ability to generate decision trees from historical data, providing interpretable results and high accuracy in forecasting categorical outcomes. By analyzing past trends in raw material availability and usage, the algorithm predicts future supply needs, optimizing production planning and supporting sustainable business operations. This study's findings are expected to align with previous research, offering insights for better production and sales management.

The Implementation of Data Mining in Measuring Student Satisfaction Levels at IAIN Kerinci

Rian Rafiska — 2024-12-31

Measuring student satisfaction is crucial to consider, given the high level of competition in the education sector alongside the advancement of knowledge and technology. It is essential to ensure that the services expected by students align with what they actually receive. Measuring student satisfaction can significantly assist higher education institutions in improving the quality of services, which in turn can impact the increase in student enrollment. This study employs a quantitative method, utilizing one of the data mining techniques, namely classification with the C4.5 algorithm, to measure student satisfaction levels. The population in this study consists of active students at IAIN Kerinci, with a sample size of 100 respondents. These students act as subjects who provide assessments or opinions on variables characterized by Tangible, Reliability, Responsiveness, Assurance, and Empathy. The data is then processed using data mining classification techniques, and testing is performed with the aid of RapidMiner software. The calculation and testing results demonstrate that data mining successfully classifies the variables in measuring student satisfaction with excellent performance, producing 10 rules from the decision tree with an accuracy rate of 98.22%. These rules are expected to serve as a basis for decision-making to determine actions that need to be taken to enhance student satisfaction.

Memomath: Educational Game Application for Elementary School Children in Special Inclusion Classes for Students with Slow Learner Diagnosis

Trinovita Zuhara Jingga — 2025-02-22

Memomath is a game-based educational application designed to support the learning of children diagnosed as slow learners in elementary school inclusion classes. This application integrates mnemonic-based math, reading, and memory exercises to improve students' academic skills and learning motivation. This research was conducted at SDIT Madani Islam Terpadu Kota Payakumbuh, an inclusive school that provides special programs for students with slow learning needs. The waterfall method was applied in the development of this application, involving the stages of needs analysis, design, implementation, testing, and maintenance. The test results showed that this application was effective in increasing engagement and understanding of concepts in students, especially at the age of 7-12 years. The data also revealed the relationship between age and duration of application use, providing important insights for design optimization. This study shows that a targeted gamification approach can make a significant contribution to the education of children with special needs, especially in helping them overcome learning challenges.