Journal of Informatics Development
Focus and Scope Journal of Informatics Development cover all topics under the fields of Informatics, Information System, Information Technology, Computer Science, and Computer Engineering. Informatics and Information system IT Audit Software Engineering Big Data and Data Mining Internet Of Thing (IoT) Game Development IT Management Computer Network and Security Mobile Computing Security For Mobile Decision Support System Web and Cloud Computing Accounting Information system Electrical and Computer Engineering Sensors and Trandusers Signal, Image, Audio and Video processing Communication and Networking Robotic, Control and Automation Fuzzy and Neural System Artificial Intelligent
Articles
35 Documents
<![CDATA[The Urgency of Information Technology and Village Administration Services (Study on SILDEKAN) ]]>
<![CDATA[Hidayat, Zainul]]>;
<![CDATA[Maulidah, Ulfa]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i1.1139
<![CDATA[This study aims to determine the urgency of the existence of Information and Communication Technology in various administrative and communication service applications at the village level in particular. This includes the planned presence of SILDEKAN (Digital Technology Application through Information System and Services of Babakan Village), Lumajang district. This is a departure from the various complaints from services that are still not as expected. This research uses the library research method (literature study), looking for relevant literature sources according to the topic discussed, with the aim of finding scientific studies on the use of service and information applications carried out by the village government including the planned use of SILDEKAN. In conclusion, the application of digital technology through the Babakan Village Information and Service System (SILDEKAN) in Babakan village, Padang sub-district, Lumajang, East Java to provide services and information is very urgent and needs to be implemented immediately as part of efforts to improve service quality.]]>
<![CDATA[Decision-Making System for Selecting Alternative Product Purchase Stores in Tokopedia Using A Combination of SAW and TOPSIS ]]>
<![CDATA[Yanuar Nurdiansyah]]>;
<![CDATA[M Zukhrofi Ardi]]>;
<![CDATA[M Arief Hidayat]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i1.1140
<![CDATA[In the era of advancing digital technology enabling online business transactions, e-commerce platforms like Tokopedia have rapidly grown in Indonesia, providing consumers with a wide array of products and services. However, this abundance of choices often leads to consumer confusion when selecting alternative stores for their purchases. Additionally, Tokopedia's search filter feature is limited, merely sorting products based on selected criteria without considering the consumer's specific needs. To address these issues, a decision-making system is essential, aiding consumers in choosing products from alternative stores that best align with their individual preferences and predetermined criteria. This study proposes a combined methodology employing the Simple Additive Weighting (SAW) method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Initially, the SAW method normalizes values (r), which are subsequently ranked using the TOPSIS method to generate recommendations for alternative stores based on input criteria and weights. The adoption of this decision-making system is poised to enhance the online shopping experience for Tokopedia users by providing well-informed recommendations, improving overall satisfaction, and streamlining the purchasing process. In conclusion, this research offers a promising approach to addressing the challenges posed by the abundance of choices in online retail, ultimately benefiting both consumers and online businesses.]]>
<![CDATA[Pengelompokkan Kabupaten dan Kota Berdasarkan Kondisi Infrastruktur Jalan Menggunakan Hierarchical Clustering ]]>
<![CDATA[Qori’atunnadyah, Marita]]>;
<![CDATA[Rahmawati, Febriane Devi]]>
<![CDATA[ Journal of Informatics Development Vol. 1 No. 1 (2022): Oktober 2022 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v1i1.1143
<![CDATA[Infrastruktur memiliki peranan penting bagi suatu wilayah, salah satunya infrastruktur jalan. Oleh karena itu, pemerintah perlu untuk memperhatikan kondisi jalan. Penelitian ini berfokus pada pengelompokkan wilayah berdasarkan kondisi jalan di Provinsi Jawa Timur tahun 2021. Hasil yang didapatkan menunjukkan bahwa pengelompokkan wilayah terbagi menjadi 3 cluster dengan menggunakan metode single linkage. Cluster 1 merupakan cluster kabupaten dengan kondisi jalan sedang yang memiliki 1 anggota kabupaten. Kemudian cluster 2 merupakan cluster kabupaten/kota dengan kondisi jalan baik yang memiliki anggota sebanyak 27 kabupaten/kota. Selanjutnya, cluster 3 merupakan cluster kabupaten dengan kondisi banyak jalan rusak yang memiliki 1 anggota. Berdasarkan hasil pengelompokkan tersebut, mayoritas kabupaten/kota yang ada di Provinsi Jawa Timur memiliki kondisi jalan yang baik. Namun, Pemerintah Provinsi Jawa Timur tetap perlu memperhatikan kabupaten yang terdapat pada cluster 3 karena cluster tersebut memiliki kondisi banyak jalan yang rusak, sehingga diharapkan kedepannya kondisi jalan pada kabupaten tersebut lebih baik.]]>
<![CDATA[Analysis Influence Segmentation Image on Classification Image X-raylungs with Method Convolutional Neural ]]>
<![CDATA[Fathur Rahman]]>;
<![CDATA[Nuzul Hikmah]]>;
<![CDATA[Misdiyanto Misdiyanto]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i1.1159
<![CDATA[The impact of image segmentation on the classification of lung X-ray images using Convolutional Neural Networks (CNNs) has been scrutinized in this study. The dataset used in this research comprises 150 lung X-ray images, distributed as 78 for training, 30 for validation, and 42 for testing. Initially, image data undergoes preprocessing to enhance image quality, employing adaptive histogram equalization to augment contrast and enhance image details. The evaluation of segmentation's influence is based on a comparison between image classification with and without the segmentation process. Segmentation involves the delineation of lung regions through techniques like thresholding, accompanied by various morphological operations such as hole filling, area opening, and labeling. The image classification process employs a CNN featuring 5 convolution layers, the Adam optimizer, and a training period of 30 epochs. The results of this study indicate that the X-ray image dataset achieved a classification accuracy of 59.52% in network testing without segmentation. In contrast, when segmentation was applied to the X-ray image dataset, the accuracy significantly improved to 73.81%. This underscores the segmentation process's ability to enhance network performance, as it simplifies the classification of segmented image patterns.]]>
<![CDATA[The Impact of TikTok Technology Transformation in the Digitalization Era Using SmartPLS ]]>
<![CDATA[Murni, Cahyasari Kartika]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i1.1191
<![CDATA[The utilization of technology has become the foundation for many businesses striving to remain competitive in the current digital era, where online shopping is increasingly dominant. TikTok, as a popular social media platform, has been employed as a marketing tool to reach a wider audience by offline businesses. This research seeks to understand the impact of TikTok technology utilization on online purchasing decisions. The sustainability of offline businesses depends on adapting to the changing consumer behavior, which is increasingly inclined towards online shopping. This study highlights the importance of using TikTok as a creative and innovative marketing tool to reach online customers. The research results indicate that the more intensive the use of TikTok technology, the more likely customers are to opt for online shopping. Subsequently, the ease of shopping on TikTok mediates the influence of technology utilization on online purchasing decisions. However, online product prices do not play a significant mediating role in purchase decision-making. In order to compete in an increasingly interconnected digital era, offline businesses need to consider more innovative marketing strategies and focus on providing a better user experience. The utilization of technology and creativity in TikTok content becomes the key to influencing online purchase decisions by digitally connected customers.]]>
<![CDATA[Statistical Application Using Visual Basic For Application (VBA) Excel ]]>
<![CDATA[Subandi, Subandi]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 2 (2024): April 2024 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i2.1299
<![CDATA[BandiStats, a statistical application, was developed with the aim of being a simple and easy-to-use statistical analysis tool thanks to its base on Microsoft Excel, a well-known platform. The development method used the Visual Basic for Application (VBA) programming language. The application test results showed the success of all implemented menus. This research produced an application that can facilitate users in analyzing statistical data. It is hoped that this application can be a useful tool for those who need statistical analysis in their daily work without having to have in-depth knowledge of statistics or computer programming. With its easy-to-use interface and comprehensive features, BandiStats provides an efficient and effective solution for statistical data analysis.]]>
<![CDATA[Classification of Chili Fruit Diseases Using Deep Convolutional Neural Network Transfer Learning ]]>
<![CDATA[Anwar, Masrur]]>;
<![CDATA[Abdillah, David Fahmi]]>;
<![CDATA[Basri, Ilham]]>;
<![CDATA[Galahartlambang, Yanuangga]]>;
<![CDATA[Khotiah, Titik]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 2 (2024): April 2024 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i2.1335
<![CDATA[Chili peppers are among the highest-value agricultural commodities, often experiencing significant price fluctuations due to supply constraints. The rainy season frequently leads to crop failures caused by diseases affecting chili plants. Existing methods often struggle to accurately differentiate between similar symptoms on leaves and fruits, leading to misdiagnosis and ineffective disease management strategies. Early detection of these diseases, which manifest as symptoms on the leaves and fruits, is crucial for effective pest management. Common diseases include anthracnose, characterized by dry brown spots on the fruit, and fruit rot, where the interior of the fruit decays while the skin remains intact. Identifying these diseases promptly is essential for applying appropriate treatments to ensure optimal yields.In this study, a comprehensive approach is taken to classify diseases in chili pepper plants (Capsicum annuum L.) by incorporating both leaf and fruit segmentation. The research employs Deep Convolutional Neural Networks with Transfer Learning (DCNN) to enhance detection capabilities. The findings reveal that for leaf disease classification, fewer neurons in additional layers yield better accuracy and reduced loss, while for fruit disease classification, a more complex model with additional neurons is necessary. This underscores the need for balancing model complexity to achieve optimal performance and prevent overfitting, particularly in distinguishing between leaf and fruit diseases.]]>
<![CDATA[Fuzzy Logic Algorithm Optimization for Safe Distance Control on Arduino-Based Reverse Parking System and SRF04 Sensor ]]>
<![CDATA[Choiri, Achmad Firman]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 2 (2024): April 2024 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i2.1336
<![CDATA[This research aims to develop a smart parking system that can accurately control the distance between vehicles and obstacles during reverse parking maneuvers. By integrating fuzzy logic algorithms into the system, this study seeks to improve the precision and reliability of distance control, thereby improving the overall safety of parking operations. The utilization of the Arduino platform and the SRF04 sensor allows real-time data processing and accurate distance measurement, i.e. this research contributes to the effectiveness of the proposed system. The application of fuzzy logic optimization in this context is expected to provide a powerful solution for safe reverse parking, offering potential benefits in terms of comfort and accident prevention in parking scenarios, especially for cars that still do not have obstacle detection sensors at the rear of the car]]>
<![CDATA[Using Machine Learning Techniques to Predict Financial Distress in Rural Banks in Indonesia ]]>
<![CDATA[Urrochman, Maysas Yafi]]>;
<![CDATA[Asy’ari, Hasyim]]>;
<![CDATA[Ro’uf, Abdur]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 2 (2024): April 2024 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i2.1341
<![CDATA[LPS liquidated about 100 people's Rural Banks between 2015 and 2019, indicating that these banks are facing significant issues, particularly financial distress. This study seeks to forecast financial distress through a two-stage classification and regression approach. Researchers used financial report data from Rural Banks in Indonesia from 2015 to 2019, covering a total of 150 banks, with 50 financial ratios from bankrupt banks and 100 from those that remained operational. Data was analyzed for two consecutive years prior to any bankruptcy declarations. The classification targets are categorized into five classes: very healthy, healthy, quite healthy, unhealthy, and distressed. The study results demonstrate that the two-stage classification and regression method can effectively predict the onset of financial distress. This is validated by the classification outcomes using the Decision Tree Algorithm, which achieved an f1-score accuracy of 88%. The evaluation of timing predictions using Random Forest Regression revealed a mean absolute error of 1.2 months and a mean absolute percentage error of 3%. These predictions can assist regulators, bank management, and investors in making better-informed decisions to address financial distress risks in Rural Banks. The superior performance of the Decision Tree Algorithm over Naïve Bayes in classifying financial distress highlights the potential of machine learning techniques in providing robust tools for early warning systems, aiding stakeholders in making informed decisions to mitigate risks.]]>
<![CDATA[Monitoring System Indoor Mushroom Cultivation via Telegram Bot ]]>
<![CDATA[Sandikyawan, Rio Ridho]]>;
<![CDATA[Arifin, Samsul]]>
<![CDATA[ Journal of Informatics Development Vol. 2 No. 2 (2024): April 2024 ]]>
Publisher : <![CDATA[Institut Teknologi dan Bisnis Widya Gama Lumajang ]]>
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DOI: 10.30741/jid.v2i2.1348
<![CDATA[Mushroom cultivation in Indonesia has significant potential due to its tropical climate, which is ideal for growing various types of mushrooms. However, maintaining optimal environmental conditions, such as temperature and humidity, is crucial for successful cultivation. This study aims to design and develop an Internet of Things (IoT)-based monitoring system for indoor mushroom farming, utilizing NodeMCU and Telegram Bot for real-time data management. IoT is used in mushroom cultivation to monitor and manage environmental conditions in real-time, considering that mushroom growth is very sensitive to changes in temperature and humidity. The main challenges faced are ensuring the stability of environmental conditions and reducing communication delays in data transmission to maintain the quality and quantity of mushroom production. The system employs a DHT11 sensor connected to a NodeMCU 8266 microcontroller to monitor temperature and humidity. Data is transmitted to farmers via the Telegram app, allowing for remote monitoring and early warning alerts when environmental parameters exceed safe limits. Field testing and performance evaluations were conducted, comparing mushroom growth between crops cultivated with and without the monitoring system. The results show that mushrooms grown under the IoT-based system achieved better growth, with the system maintaining optimal conditions between 24°C to 27°C for temperature and 80% to 90% for humidity. Communication delays averaged 9 seconds, which impacted the successful rate of real-time monitoring. Overall, the system improved the control of environmental conditions and supported enhanced mushroom growth, demonstrating its effectiveness in optimizing cultivation practices. transmission rates and maintaining environmental parameters to further improve cultivation results.]]>
