Journal of Dinda : Data Science, Information Technology, and Data Analytics
Journal of Dinda : Data Science, Information Technology, and Data Analytics as a publication media for research results in the fields of Data Science, Information Technology, and Data Analytics, but not implicitly limited. Published 2 times a year in February and August. The journal is managed by the Data Engineering Research Group, Faculty of Informatics, Telkom Purwokerto Institute of Technology. Journal of Dinda is a medium for scientific studies resulting from research, thinking, and critical-analytic studies regarding Data Science, Informatics, and Information Technology. This journal is expected to be a place to foster enthusiasm in education, research, and community service which continues to develop into supporting references for academics. FOCUS AND SCOPE Journal of Dinda : Data Science, Information Technology, and Data Analytics receive scientific articles with the scope of research on: Machine Learning, Deep Learning, Artificial Intelligence, Databases, Statistics, Optimization, Natural Language Processing, Big Data and Cloud Computing, Bioinformatics, Computer Vision, Speech Processing, Information Theory and Models, Data Mining, Mathematical, Probabilistic and Statical Theories, Machine Learning Theories, Models and Systems, Social Science, Information Technology
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<![CDATA[Implementation of TOPSIS in a Decision Support System for Selecting the Ideal Food Menu for GERD Patients ]]>
<![CDATA[Jesica Emarapenta Br Sinulingga]]>;
<![CDATA[Annisaa Utami]]>
<![CDATA[ Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February ]]>
Publisher : <![CDATA[Research Group of Data Engineering, Faculty of Informatics ]]>
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DOI: 10.20895/dinda.v5i1.1784
<![CDATA[Gastroesophageal Reflux Disease (GERD) is a condition characterized by the repeated reflux of stomach acid into the esophagus, causing symptoms such as heartburn and regurgitation. This condition can be triggered by irregular eating habits, including improper portion sizes, frequency, or types of food. Frequent consumption of foods that are excessively hot, spicy, or acidic can exacerbate stomach problems by increasing gastric acid production, leading to GERD recurrence. This study aims to develop a web-based decision support system to determine the ideal food menu for GERD patients. The system utilizes five main criteria protein, carbohydrates, fat, fiber, and calories to analyze ten food menu alternatives. The comparison between the system's results and manual calculations demonstrates consistent outcomes, as both produce identical preference index values. Based on the calculations, Wheat Pasta was determined as the most ideal food menu with the highest preference index value of 0.7415. Other menus, such as Kalasan Fried Chicken, Salmon Fish, and Stir-fried Tempe, also had high preference indexes, while menus such as Stir-fried Chayote, Stir-fried Spinach, and Oatmeal ranked lower.]]>
<![CDATA[Analysis of Bread Sales Patterns at Queen Bakery Stores Using Algorithms Fpgrowth ]]>
<![CDATA[Muhammad Ray Pratama Sembiring]]>;
<![CDATA[Raissa Amanda Putri]]>
<![CDATA[ Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February ]]>
Publisher : <![CDATA[Research Group of Data Engineering, Faculty of Informatics ]]>
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DOI: 10.20895/dinda.v5i1.1787
<![CDATA[The culinary industry, particularly the bakery business, is experiencing rapid growth with increasing competition. Changes in consumer trends, the rising number of market players, and fluctuating market dynamics pose significant challenges in maintaining stable sales. Queen Bakery, a bakery located in Medan, faces issues with fluctuating monthly sales, indicating that certain products are less in demand and that more effective marketing strategies are needed. To address this issue, the utilization of technology in data analysis is essential, particularly through the implementation of data mining techniques. Data mining enables the identification of consumer purchasing patterns more accurately and data-driven. One of the most effective algorithms for sales pattern analysis is FPGrowth, which can identify frequently occurring itemsets in transactions. Unlike the Apriori algorithm, which requires extensive computations, FPGrowth is more efficient in discovering product associations frequently purchased together. This study aims to analyze sales patterns at Queen Bakery using the FPGrowth algorithm to provide strategic insights into inventory management and product marketing. The results of this research are expected to assist Queen Bakery in improving operational efficiency, optimizing product offerings, and formulating more competitive business strategies. By implementing data mining, the bakery can gain a deeper understanding of consumer preferences, ultimately enhancing sales performance and competitiveness in the dynamic culinary market.]]>
<![CDATA[Web-Based Monitoring Information System for Official Travel Letters on Food Security and North Sumatera Horticulture ]]>
<![CDATA[Rafli Bima Sakti]]>;
<![CDATA[Rakhmat Kurniawan]]>
<![CDATA[ Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February ]]>
Publisher : <![CDATA[Research Group of Data Engineering, Faculty of Informatics ]]>
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DOI: 10.20895/dinda.v5i1.1789
<![CDATA[The Food Security and Horticulture Office of North Sumatra faces challenges in the management of Service Travel Letters (SPD), such as submitting letters, making letter notes, operational costs, which are still done manually using manual methods, so it is time consuming. This hampers the effectiveness of document management and data-based decision making. To overcome these problems, this research develops a web-based monitoring information system. This system is designed to manage official travel letters, to minimize the time and recording of letter reports. With the web-based Monitoring Information System, the management of official travel letters becomes more structured and can be accessed in real-time, thus increasing efficiency in carrying out official duties in various regions of North Sumatra. This research uses the Research and Development (R&D) method with stages including needs analysis, system design, prototype development, testing, and evaluation. The results of the system implementation show that the use of this Monitoring Information System is able to speed up the process of submitting and approving official travel letters, as well as reducing errors in data collection and recording of trips.]]>
<![CDATA[Stock Information System for All Smartphone Brands Using Barcode ]]>
<![CDATA[Wini Istya Sari Lubis]]>;
<![CDATA[Rakhmat Kurniawan]]>
<![CDATA[ Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February ]]>
Publisher : <![CDATA[Research Group of Data Engineering, Faculty of Informatics ]]>
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DOI: 10.20895/dinda.v5i1.1790
<![CDATA[In the era of globalization, rapid development in technology that brings convenience and speed in completing human tasks. A barcode is a collection of optical data that is read by a machine. In fact, this barcode collects data in width (lines) and parallel line spacing and can be referred to as a linear or 1D (1-dimensional) barcode or symbology. Stock reports on purchases and sales of a period are useful for helping employees to assess the amount of inequality in purchasing flows, monitor stock/inventory of goods, and provide reports, both purchase reports, sales reports, and stock condition reports. ALL BRAND SMARTPHONE is a company engaged in the sale of electronic equipment. The process of checking stock at ALL BRAND SMARTPHONE has not implemented a barcode application, but is only done by checking stock manually by conducting manual checks between incoming and outgoing goods, then the final stock of goods will be calculated. Manual calculations or checks allow errors to occur in the creation or input of data. The purpose of designing this inventory information system is to be able to build a web-based inventory system that is expected to minimize errors or manipulation of inventory data using barcodes. And assist companies and employees in managing incoming goods data and outgoing goods data. The research method used involves data collection through observation, interviews, and literature studies, system development with a waterfall methodology approach.]]>
<![CDATA[Implementation of the Single Moving Average Method in Forecasting Sales of Motorcycle Spare Parts ]]>
<![CDATA[Dwika Sherliyanda]]>;
<![CDATA[Muhammad Dedi Irawan]]>;
<![CDATA[Adnan Buyung Nasution]]>
<![CDATA[ Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February ]]>
Publisher : <![CDATA[Research Group of Data Engineering, Faculty of Informatics ]]>
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DOI: 10.20895/dinda.v5i1.1791
<![CDATA[Sales forecasting is an important element in inventory management to ensure product availability in accordance with market demand. One method that can be used for forecasting is the Single Moving Average (SMA), which works by calculating the average sales in a certain period to identify future sales trends. This research aims to implement the SMA method in forecasting sales of motorbike spare parts in order to increase stock management efficiency and reduce the risk of excess or shortage of inventory. This research method involves collecting historical data on sales of motorbike spare parts in a certain period, which is then analyzed using the SMA method with various average period lengths to determine the best accuracy. The research results show that the SMA method can provide fairly accurate estimates of future demand patterns. With better forecasting, stores or distributors can optimize procurement strategies and reduce unnecessary carrying costs. Apart from that, implementing this method also contributes to increasing customer satisfaction because product availability can be more guaranteed. The conclusion of this research shows that the Single Moving Average method is a simple but effective forecasting technique in motorcycle spare parts inventory management. Implementation of this method can help business people make more appropriate decisions in stock planning and marketing strategies.]]>
<![CDATA[Shoe Damage Identification System Using the Cosine Method in Web-Based K2n Store ]]>
<![CDATA[Ibnu Faisal]]>;
<![CDATA[Raissa Amanda Putri]]>
<![CDATA[ Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February ]]>
Publisher : <![CDATA[Research Group of Data Engineering, Faculty of Informatics ]]>
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DOI: 10.20895/dinda.v5i1.1795
<![CDATA[This research aims to develop a Web-Based Shoe Damage Identification System in K2N Store using the Rapid Application Development (RAD) methodology and the Cosine Similarity method. This system is designed to help the process of automatically identifying shoe damage based on the description of the symptoms that the user inputs. There are several main menus in this system, namely Login, Damage, Symptoms, and Case Base, each of which supports an effective flow of damage and symptom data management. The Login menu is used for user authorization, while the Crash and Symptoms menu allows for the management of data on crash types and related symptoms. The Case Base menu serves as the main reference in the identification process with the Cosine method, where the system calculates the degree of similarity between the new damage description and the existing reference data. Based on the test results, this system is able to provide accurate damage identification results, taking into account the similarity of the symptom description mathematically. The use of the Cosine method in RAD has proven to be effective in producing a fast and flexible solution for K2N Store Stores. Thus, this system is expected to increase efficiency and accuracy in the process of identifying shoe damage, as well as provide better service to customers.]]>
<![CDATA[Financial Management Information System Design with Business Intelligence Approach ]]>
<![CDATA[Ardiansyah Putra]]>;
<![CDATA[Muhamad Alda]]>
<![CDATA[ Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February ]]>
Publisher : <![CDATA[Research Group of Data Engineering, Faculty of Informatics ]]>
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DOI: 10.20895/dinda.v5i1.1796
<![CDATA[This research aims to design and develop a web-based financial management application for Pabrik Opak Sun Jaya Mandiri, focusing on financial management. Prior to the application’s development, the business used a manual financial management system, which led to various issues, such as unstructured transaction records, difficulties in monitoring cash flow in real-time, and slow financial reporting prone to human errors. These problems could hinder the business owner from making accurate financial and operational decisions.To address these issues, the application was developed using the PHP programming language and MySQL database, designed to automate the recording of rental transactions, income, and expenses in an integrated manner. The application includes features for automatic and real-time financial reporting, enabling the business owner to monitor financial conditions more accurately and efficiently. Additionally, it implements a Business Intelligence (BI) approach, providing analysis of financial data, including income and expense trends, as well as business performance over time.The research results indicate that the application effectively resolves the issues present in the previous financial management system, particularly in terms of efficiency, recording accuracy, and faster, more detailed data presentation. The business owner can better monitor financial developments, and employees find it easier to perform tasks such as report preparation and transaction recording. Continuous evaluation and feature updates are highly recommended to ensure the application evolves in line with the increasingly complex needs of the business. Therefore, this application is expected to have a long-term positive impact on the financial management of Pabrik Opak Sun Jaya Mandiri.]]>
