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Modem : Jurnal Informatika dan Sains Teknologi
Published by Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia
ISSN : 30467217     EISSN : 30467209     DOI : 10.62951
Core Subject : Science,
Computer Science & IT
Modem : Jurnal Informatika dan Sains Teknologi memuat hasil-hasil penelitian di bidang Ilmu Informatika dan Teknologi
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 111 Documents
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Rancang Bangun Aplikasi form online untuk pemesanan dan pengadaan barang internal pada Puskesmas Cogreg Duta Agung Pramana; Farizi Ilham; Mohammad Hadi Purnomo; Zacky Nurfaqih Permana
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.889

Abstract

The rapid growth of information technology has driven healthcare institutions to modernize their data management and administrative workflows. Puskesmas Cogreg, a primary healthcare facility, still depends on manual procedures for internal goods ordering and procurement. This practice generates recurring operational problems: records remain disorganized, documents are prone to loss, and approval workflows frequently experience delays due to the lack of a centralized digital system. To resolve these issues, this study designs and builds a web-based online form application using the Waterfall method, which progresses sequentially through five stages: requirements analysis, system design, implementation, testing, and maintenance. The application equips medical staff with a digital request submission feature, enables warehouse heads to verify and approve requests, and provides real-time procurement status tracking for all authorized users. System validation used black-box testing across 24 functional scenarios, all returning results consistent with expected outputs. The application demonstrably improves procurement efficiency, reduces recording errors, accelerates approval decisions, and produces a more structured, transparent, and accountable administrative process at Puskesmas Cogreg.
Pengembangan Fitur Notifikasi WhatsApp sebagai Pendukung Sistem CRM dalam Optimalisasi Layanan Pelanggan Melfika Sheylawatin; Moh. Anshori Aris Widya
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.919

Abstract

Communication management and task coordination are crucial elements in the operational performance of the garment manufacturing industry. Tariz Konveksi, a medium-sized garment business in Jombang, still relies on conventional communication systems, resulting in miscommunication between departments, production delays, and decreased customer satisfaction. This study aims to design and develop a web-based task management system integrated with WhatsApp Notifications to improve operational effectiveness and customer service based on Customer Relationship Management (CRM) principles. The research employed the Research and Development (R&D) method using the ADDIE approach, which consists of Analysis, Design, Development, Implementation, and Evaluation stages. Data were collected through interviews, observations, and direct documentation. The system was developed using Node.js, MySQL, and the WhatsApp API. System testing was conducted through black-box testing and pre- and post-implementation surveys. The results indicate that the proposed system is capable of delivering real-time automated notifications to employees regarding assigned tasks and deadlines, as well as providing customers with updates on their order status. The implementation of the system is expected to reduce communication errors, shorten manual response times, and enhance customer satisfaction. This research contributes by providing a model for integrating WhatsApp Notifications into a task management system that can be adopted by medium-scale garment industries as a digital communication solution based on CRM principles.
Perancangan Sistem Informasi Pengarsipan Digital Data Pelanggan pada PT. Jambi Independent Press Berbasis Web Miranda Miranda; Ronald Naibaho; Gunardi Gunardi
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.923

Abstract

PT. Jambi Independent Press is one of the companies engaged in publishing newspapers in its data processing using Microsoft Excel, but there are still many obstacles in data processing, such as the difficulty of recording customer data archiving data, planning previously planned activities because the data search process is valued slow, data does not appear automatically so you have to input it repeatedly, and data cannot be integrated with each other because there is no database. The purpose of this study is to analyze the system that is currently running, in order to overcome the problems faced at PT. Jambi Independent Press, by designing a Customer Data Digital Archiving Information System Design at PT. Web-Based Jambi Independent Press. The research framework that will be carried out in solving the problems discussed is identifying, conducting information searches based on theoretical foundations, collecting data using observation and interview methods, analyzing to find solutions to problems faced by PT. Jambi Independent Press. The system development method uses the waterfall model, the implementation of this research uses the PHP Programming Language and MySQL DBMS, to produce data processing applications that are expected to facilitate data processing and report generation.
Analisis Sentimen Polemik Kebijakan Pemerintah Makan Siang Gratis pada Twitter Menggunakan Metode Neural Network Classification Dandy Tri Prasetyo; Deni Arifianto; Reni Umilasari
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.924

Abstract

This study aims to investigate public sentiment toward the Indonesian government's free lunch program by analyzing discussions on the X social media platform. A total of 1,500 tweets were collected through a web scraping process using relevant keywords and hashtags. The research workflow consisted of text preprocessing, including data cleaning, case folding, tokenization, stop-word removal, and stemming. The processed text was then transformed into numerical features using the Term Frequency–Inverse Document Frequency (TF-IDF) weighting method, followed by sentiment classification using the Neural Network Classification algorithm. Model performance was evaluated through K-Fold Cross Validation and a Confusion Matrix based on accuracy, precision, recall, and F1-score metrics. To address the issue of class imbalance, Random Over Sampling (ROS) was applied before the classification stage. The experimental results indicate that incorporating ROS improved the classification performance compared with the model trained on the original imbalanced dataset. Furthermore, the Neural Network Classification model effectively categorized public opinions into positive, negative, and neutral sentiments. The findings of this study are expected to provide valuable insights for policymakers in understanding public perceptions of the free lunch program and supporting future policy evaluation.
Perancangan dan Implementasi Arsitektur Data Pipeline Otomatis untuk Analisis Sentimen Ulasan Aplikasi E-Commerce menggunakan Apache Airflow, Docker, dan Ensemble Learning Agustian, M. Shandy; Supriadi, Fidi; Setiadi, David
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.937

Abstract

The growth of user reviews on e-commerce platforms in Indonesia is growing much faster than conventional analysis capacity that relies on manual review. This study designs and implements an automated data pipeline based on an ETL (Extract, Transform, Load) architecture that integrates data acquisition through dynamic web scraping (Selenium), Indonesian text preprocessing, sentiment classification using Ensemble Learning models (Multinomial Naive Bayes and Random Forest), workflow orchestration using Apache Airflow, containerization with Docker, and storage of results in a PostgreSQL database. The system is tested using a case study of reviews of three popular e-commerce applications in Indonesia (Shopee, Tokopedia, and Blibli) with a total of more than 30,000 rows of raw review data. The test results show that the pipeline runs successfully end-to-end and automatically, with an idempotency mechanism that successfully maintains data integrity from the risk of duplication. The Ensemble model achieves an overall accuracy of 77.94% using the SMOTE (Synthetic Minority Over-sampling Technique) technique to address class imbalance. However, a per-class evaluation analysis revealed that SMOTE was only effective in improving performance on minority classes with relatively sufficient source data, while failing to provide significant improvements on classes with extreme imbalance. This finding provides a methodological contribution regarding the limitations of oversampling techniques' effectiveness in very limited data and emphasizes the importance of evaluating per-class metrics rather than relying solely on overall accuracy.
Analisis Komparasi Sentimen Ulasan Pembaruan BRImo 2024 Menggunakan Algoritma SVM Luthfi Firmansyah
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.939

Abstract

Significant transformations in the user interface and features of the BRImo application throughout 2024 have generated diverse responses from users. Monitoring changes in customer perceptions is essential for developers to evaluate the effectiveness of these updates and maintain the quality of digital banking services. This study aims to compare user sentiment before and after the BRImo application update using a text mining approach with the Support Vector Machine (SVM) algorithm. User reviews were collected from the Google Play Store through a web scraping technique. The collected data were processed through several text preprocessing stages, including cleaning, case folding, tokenization, stopword removal, and stemming. Furthermore, the Term Frequency–Inverse Document Frequency (TF-IDF) method was applied for feature weighting before classification using the SVM algorithm. The experimental results show that the SVM model achieved an accuracy, precision, recall, and F1-score of 92%, indicating its effectiveness in sentiment classification. Comparative analysis revealed an increase in negative sentiment after the application update, mainly related to login issues, authentication problems, adaptation to the new interface, and system stability. In contrast, positive sentiment remained associated with the application's comprehensive features and transaction convenience. In conclusion, technical stability after system updates has a significant influence on user satisfaction, while the SVM algorithm provides an effective automated approach for evaluating user feedback and supporting future application improvements.
Etika Desain Antarmuka: Praktik Manipulatif (Dark Patterns) pada Platform Digital Jihaan Adzanishaafiya Anwar; Evy Nurmiati
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.943

Abstract

On contemporary digital platforms, user interface (UI) design plays a dual role: it eases how services are used while also nudging the way people act. Design choices that are deliberately built to deceive, pressure, or steer users toward options favoring providers rather than the users themselves are what scholars label dark patterns. This article frames such patterns as an ethical concern within interface design and interprets their consequences through the lens of professional ethics. Methodologically, it relies on a systematic literature review (SLR) spanning 20 peer-reviewed works released between 2021 and 2026, compiled from well-regarded databases as well as national journals and filtered using predefined inclusion and exclusion criteria. The evidence indicates that dark patterns are widespread, surfacing across most e-commerce, mobile, and social-media services, and typically taking the shape of forced action, obstruction, sneaking, urgency, and confirmshaming. Ethically, they conflict with the foundational values of the IT profession, namely respect for user autonomy, honesty, transparency, and the duty to prevent harm. The study argues that curbing dark patterns demands a blend of ethical design (bright patterns), responsive regulation, and stronger digital literacy, thereby reinforcing professional design ethics within Indonesia's digital ecosystem.  
Komparasi Algoritma Machine Learning dengan Hyperparameter Tuning pada Prediksi Level Obesitas Dwi Utami; Fathoni Dwiatmoko; Alinsa Novsagita
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.955

Abstract

Obesity has become a growing global health concern due to its association with various chronic diseases, including diabetes mellitus, hypertension, and cardiovascular disorders. This study investigates the performance of Support Vector Machine (SVM), Random Forest, and Gradient Boosting algorithms enhanced through hyperparameter tuning for obesity level prediction. The study utilized the Obesity Level dataset, which contains 2,111 instances, 16 input features, and one target class. Following the data preprocessing stage, 2,087 instances were included in the analysis. Correlation analysis was conducted to identify the nine most relevant features used for model development. Experimental results demonstrate that the Random Forest model achieved the best predictive performance compared to SVM and Gradient Boosting, with an accuracy of 90.91%, precision of 91.19%, recall of 90.91%, and an F1-score of 90.94%. The dataset was partitioned into training and testing subsets using an 80:20 split. Furthermore, the optimal model was deployed in a Streamlit-based web application to facilitate obesity level prediction. These findings suggest that Random Forest, when optimized through hyperparameter tuning, provides a reliable and effective approach for multiclass obesity classification.
Perancangan Protocol TCP/IP pada Jaringan Topologi Star dengan Metode Experimen pada Cisco Packet Tracer Versi 8.2.2 Ira Zulfa; Rahmadi Asri; Kurnia Azmi
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.954

Abstract

This research discusses the design and implementation of the TCP/IP protocol on a star topology network using Cisco Packet Tracer version 8.2.2. The main objective of this study is to analyze network performance and demonstrate that the star topology provides greater stability, easier management, and more efficient data communication compared to the bus topology previously used in the Faculty of Engineering Laboratory at Gajah Putih University. The research method applied is a simulation experiment by designing and configuring a network model consisting of virtual PCs, laptops, servers, and switches to represent the actual laboratory network environment. The testing process focuses on communication performance, connectivity, packet transmission, and network efficiency using the TCP/IP protocol. The experimental results show that host-to-host communication runs effectively, with a very low packet loss rate and acceptable delay levels. Furthermore, the star topology successfully minimizes data collisions, improves network reliability, and simplifies troubleshooting processes compared to the bus topology. In conclusion, the implementation of TCP/IP on a star topology network can serve as an effective alternative for improving network quality, stability, and management efficiency in educational laboratory environments.
Sistem Pendukung Keputusan Pencarian Bakat Pemain E-Sport Mobile Legends menggunakan Metode Moora Berbasis Web Gayuh Destanto; Muhamad Meky Frindo
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 4 No. 3 (2026): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v4i3.957

Abstract

Along with the rapid growth of the e-sports industry, particularly in the game Mobile Legends: Bang Bang, significant opportunities have emerged for young players to pursue professional careers. However, in e-sports communities such as Sharing Gils Blog, the talent scouting process is still conducted subjectively without the support of a structured and data-driven system. This study aims to develop a web-based Decision Support System (DSS) as a tool to assist the e-sports player selection process so that it can be carried out objectively, efficiently, and accurately. The MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) method is applied as a multi-criteria decision-making technique due to its ability to process various evaluation criteria that have been weighted according to their respective levels of importance. The criteria used include both mechanical and non-mechanical aspects relevant to player performance, such as in-game statistics, strategic ability, team communication, and performance consistency. The research stages consist of data collection through interviews, observations, and literature studies, followed by system requirements analysis, determination of evaluation criteria, system design and development using the Rapid Application Development (RAD) approach, and system testing using black box and white box methods. With appropriately assigned weights, the system is able to perform objective calculations and generate measurable recommendations for selecting the best players. The testing results indicate that the system operates as expected and is capable of supporting a more transparent and fair decision-making process in the selection of talented players within e-sports communities.

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