https://ejournal.itbwigalumajang.ac.id/index.php/jid/issue/feedJournal of Informatics Development2025-01-20T14:11:09+07:00Marita Qori'atunnadyah | 082310411048[email protected]Open Journal Systems<div class="flex flex-grow flex-col gap-3 max-w-full"> <div class="min-h-[20px] flex flex-col items-start gap-3 whitespace-pre-wrap break-words overflow-x-auto"> <div class="markdown prose w-full break-words dark:prose-invert dark"> <p>The Journal of Informatics Development is a scientific journal in the field of informatics published by the Informatics study program at the Widya Gama Institute of Technology and Business in Lumajang. This journal aims to publish original research works and high-quality articles in the field of engineering and is an annual journal published since 2022. The journal is issued twice a year in October and April.</p> </div> </div> </div>https://ejournal.itbwigalumajang.ac.id/index.php/jid/article/view/1399Sentiment Analysis of Ijen Crater Reviews using Decision Tree Classification and Oversampling Optimization2024-11-01T18:28:18+07:00Fadhel Akhmad Hizham[email protected]Hasyim Asyari[email protected]Maysas Yafi Urrochman[email protected]<p>Sentiment analysis is a text mining technique that classifies content as positive, negative, or neutral polarity in each sentence or document. These lines or papers may be user reviews assessing the quality of a product or material supplied to them. The purpose of this study is to better understand the function of sentiment analysis in assessing evaluations of the Ijen Crater tourist destination based on Google Maps user comments. This study is conducted in four steps, beginning with data gathering in the form of Google Maps evaluations obtained by data scraping. Following data collection, text preparation includes case folding, tokenization, stopword elimination, and stemming. Following text preprocessing, the next stage is imbalaced data optimization, which involves modifying the minority class samples to be nearly equal to the majority class by randomly duplicating minority class samples. Then, each review is categorized according to sentiment using the Decision Tree (DT) method. Testing has done by comparing DT without optimization and DT with SMOTE-ENN and ADASYN optimization. The result shown DT with SMOTE-ENN optimization has the best accuracy improvement with 1.62%, from 96.94% to 98.56%.</p>2024-10-31T00:00:00+07:00Copyright (c) 2024 Fadhel Akhmad Hizham, Hasyim Asyari, Maysas Yafi Urrochmanhttps://ejournal.itbwigalumajang.ac.id/index.php/jid/article/view/1418Detection of Diabetes in Pregnant Women Using Machine Learning as an Effort Towards Golden Indonesia 20452024-11-01T19:27:42+07:00Agung Muliawan[email protected]Muhamat Abdul Rohim[email protected]Difari Afreyna Fauziah[email protected]Hamzah Fansuri Yusuf[email protected]<p>One of the goals of the Golden Indonesia 2045 program is to utilize health technology to enhance public health, with diabetes being a prominent concern. This research aims to employ ensemble classifier optimization techniques in machine learning for the early detection of diabetes among pregnant women. The study uses physiological data, including variables such as glucose levels, number of pregnancies, skin thickness, blood pressure, insulin levels, body weight, family history, and age. By combining multiple models, ensemble classifiers can enhance prediction accuracy, stability, and overall model performance. This research utilizes an open Kaggle dataset on pregnant women to train and test machine learning models, specifically Support Vector Machine (SVM) and Deep Learning, incorporating ensemble techniques such as bagging and boosting. Experimental results indicate that the ensemble classifier approach significantly enhances diabetes classification, with SVM using bagging achieving the highest accuracy at 76.95%. These findings suggest that ensemble classifier methods could be a valuable tool for early diabetes detection, providing timely intervention and improved risk management during pregnancy, which supports the objectives of improving public health under the Golden Indonesia 2045 initiative.</p>2024-10-31T00:00:00+07:00Copyright (c) 2024 Agung Muliawan, Muhamat Abdul Rohim, Difari Afreyna Fauziah, Hamzah Fansuri Yusufhttps://ejournal.itbwigalumajang.ac.id/index.php/jid/article/view/1419Implementation Of Arima Model In The Analysis Of City Temperature Averag2024-11-01T19:54:13+07:00Muhamat Abdul Rohim[email protected]Agung Muliawan[email protected]Ferry Wiranto[email protected]<p>This study analyzes the daily average temperature data of Delhi city from 2013 to 2017 using the Autoregressive Integrated Moving Average (ARIMA) model to model and predict temperature trends. The temperature data processed in this study is non-stationary, so differentiation is applied to achieve stationarity. Two ARIMA models were evaluated: ARIMA (1,1,1) and ARIMA (1,1,1)(1,0,1). The ARIMA (1,1,1) model is effective in capturing short-term patterns, while the ARIMA (1,1,1)(1,0,1) model performs better in handling seasonal components. The findings show that the ARIMA (1,1,1)(1,0,1) model provides more accurate prediction results by accounting for seasonal fluctuations in temperature data. This research is expected to serve as a reference for preventive measures related to temperature changes, as temperature variations can affect public health, infrastructure, and quality of life in rapidly growing cities like Delhi. Understanding temperature trends and making accurate predictions helps in city planning, resource management, and developing adaptation strategies for climate change, which is crucial for mitigating negative impacts and planning for a more sustainable future.</p>2024-10-31T00:00:00+07:00Copyright (c) 2024 Muhamat Abdul Rohim, Agung Muliawan, Ferry Wirantohttps://ejournal.itbwigalumajang.ac.id/index.php/jid/article/view/1430Clustering of Lecturer Performance Using K-Means2024-11-19T10:19:20+07:00Abdur Rouf[email protected]Marita Qoritunnadyah[email protected]Hasyim Asyari[email protected]Maysas Yafi Urrohman[email protected]<p>Lecturers serve as professional educators and scientists whose primary roles are knowledge transformation, development, and dissemination in fields such as science, technology, and the arts through education, research, and community service. They play a critical role in fostering an educated generation, and as such, must maintain high levels of integrity in their work. The academic position of a lecturer often reflects their involvement in research, community service, and scientific publications, indicating a broad scope of expertise. This study aims to cluster lecturers based on their academic positions, research activities, community service, and number of publications, using secondary data from the Community Service Research Institute, UPT Academic Positions and Lecturer Certification, and UPT Publications. The clustering was conducted using a non-hierarchical k-means method, which resulted in three clusters: Cluster 1 with 26 members showing minimal productivity in the tridharma tasks, Cluster 2 with 6 members demonstrating high engagement, and Cluster 3 with 20 members with moderate involvement. These findings suggest that universities need to monitor and support lecturers in Cluster 1 to improve their contributions to education, research, and community service. This clustering provides insights that can guide universities in promoting a balanced and active academic environment.</p>2024-10-31T00:00:00+07:00Copyright (c) 2024 Abdur Rouf, Marita Qoritunnadyah, Hasyim Asyari, Maysas Yafi Urrohmanhttps://ejournal.itbwigalumajang.ac.id/index.php/jid/article/view/1498Design and Development of an Exhibition Management System for Final Project Products of Practicum Using the Prototyping Method2025-01-20T14:11:09+07:00David Juli Ariyadi[email protected]Bety Etikasari[email protected]<p>This study focuses on the design and development of the Exhibition Management System (EMS) through the Prototyping Method exemplifies a workable solution to the challenges of organizing exhibitions aimed at showcasing products developed from Project Based Learning (PBL) in practicum activities. By integrating features such as participant registration, product submission, feedback collection, and archive management, this system presents an organized platform that boosts user interaction and streamlines operations. Requirement prototype technique of prototyping is utilized because the developer builds the system by outlining its functions and processes, especially when the user or owner of the system is unable to accurately. The system is built using the Laravel framework and MySQL as data storage. This system is not only a digital platform in exhibition management, but also serves as a reference that can be implemented for other educational institutions that want to increase public engagement in the institution's activities to improve the experience through digital solutions. The successful implementation of this system as a benchmark shows its potential to increase innovation, teamwork, and effective results in project-based learning.</p>2024-10-29T00:00:00+07:00Copyright (c) 2025