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All Journal Jurnal of Applied Multimedia and Networking Bulletin of Computer Science Research Journal of Community Service International Journal of Artificial Intelligence in Medical Issues
Purnamasari, Dwi Amalia
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Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Evaluating Thresholding-Based Segmentation and Humoment Feature Extraction in Acute Lymphoblastic Leukemia Classification using Gaussian Naive Bayes Rismayanti, Nurul; Naswin, Ahmad; Zaky, Umar; Zakariyah, Muhammad; Purnamasari, Dwi Amalia
International Journal of Artificial Intelligence in Medical Issues Vol. 1 No. 2 (2023): International Journal of Artificial Intelligence in Medical Issues
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijaimi.v1i2.99

Abstract

This study, titled "Evaluating Thresholding-Based Segmentation and HuMoment Feature Extraction in Acute Lymphoblastic Leukemia Classification using Gaussian Naive Bayes," investigates the application of image processing and machine learning techniques in the classification of Acute Lymphoblastic Leukemia (ALL). Utilizing a dataset of microscopic blood smear images, the research focuses on the efficacy of thresholding-based segmentation and Hu moment feature extraction in distinguishing between benign and malignant cases of ALL. Gaussian Naive Bayes, known for its simplicity and effectiveness, is employed as the classification algorithm. The study adopts a 5-fold cross-validation approach to evaluate the model's performance, with particular emphasis on metrics such as accuracy, precision, recall, and F1-score. Results indicate a high precision rate across all folds, averaging approximately 84.13%, while exhibiting variability in accuracy, recall, and F1-scores. These findings suggest that while the model is effective in identifying malignant cases, further refinements are necessary for improving overall accuracy and consistency. This research contributes to the field of medical image analysis by demonstrating the potential of combining simple yet efficient techniques for the automated diagnosis of hepatological diseases. It highlights the importance of integrating image processing with machine learning to enhance diagnostic accuracy in medical applications.
PENGEMBANGAN DAN IMPLEMENTASI SISTEM INFORMASI ORGANISASI PADA PIMPINAN CABANG MUHAMMADIYAH KECAMATAN BATAM KOTA Irmansyah Lubis, Ahmadi; Riyadi, Agung; Purnamasari, Dwi Amalia; Ardi, Noper; Mu'minin, Amirul; Suwarno, Suwarno; Ramadhan, Gilang Bagus
Journal of Community Service Vol 6 No 2 (2024): JCS, December 2024
Publisher : Ikatan Dosen Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56670/jcs.v6i2.275

Abstract

The management of an organization often has many obstacles such as less optimal management of organizational documents, news portals, financial reports, correspondence documentation, activity documentation or data collection of members of the organization. Therefore, a reliable management system is needed so that management in the organization can be carried out more optimally. Likewise with the management in the Muhammadiyah Branch Executive, Batam Kota District, a reliable system is also needed to support the movement of various activities in the organization. The website-based information system developed is an answer to this problem. This system can be used to manage various activities and monitor their progress as well as make it easier for administrators to collect data on their members. This system can also display various institutional news so that the public is more familiar with the Muhammadiyah Branch Executive of Batam Kota District as a community organization with Islamic nuances that also carries out da'wah activities to spread goodness. So this is an agenda in this community service activity for the development of information systems and assistance in the implementation of the system both for managers and users of the system, as well as as a concrete step for the contribution of Higher Education in empowering the community by applying scientific principles that are useful for the benefit of the community.
Sistem Pendukung Keputusan Berbasis Web Dalam Penentuan Susunan Personalia Organisasi Menggunakan Metode TOPSIS Irmansyah Lubis, Ahmadi; Purnamasari, Dwi Amalia; Ardi, Noper
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.560

Abstract

The determination of the composition of personnel in an organization, especially in the activities of the Branch Conference (Musran) of the Muhammadiyah Branch Executive of Belian Village, is still done manually and tends to be subjective. This has the potential to cause inefficiencies and internal conflicts in the decision-making process. This research aims to develop a web-based decision support system (SPK) that can help the management selection process objectively by using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The TOPSIS method was chosen because it is able to provide the best alternative ratings based on its proximity to positive and negative ideal solutions. The five main criteria used in decision-making include: organizational experience, level of education, loyalty to the organization, leadership, and availability of time. The system is designed using the PHP programming language and MySQL database. The results of the implementation show that the system is able to produce recommendations for a more systematic, transparent, and accountable management structure. With this TOPSIS-based SPK, the deliberation process can run faster and more efficiently without eliminating the principle of democracy in the organization. This research is expected to be an innovative solution in adaptive and sustainable information technology-based organizational governance.
Evaluasi User Experience Game Aaron Lost in the Jungle Menggunakan Metode Game Experience Questionnaire (GEQ) Muhammad Iffaturrahman; Purnamasari, Dwi Amalia
JOURNAL OF APPLIED MULTIMEDIA AND NETWORKING Vol 9 No 1 (2025): Journal of Applied Multimedia and Networking
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jamn.v9i1.10242

Abstract

User experience is a crucial indicator in triggering the quality of interaction in digital games. This study aims to provide user experience in the game Aaron Lost in the Jungle using the Game Experience Questionnaire (GEQ) method. The GEQ instrument consists of four modules: the Core Module, the In-game Module, the Post-game Module, and the Social Presence Module. However, due to the single-player nature of the game, the Social Presence module was not implemented in this study. This study uses a quantitative descriptive approach, with data collection through a questionnaire and structured observations of 30 participants who have completed the game. Analysis was conducted on the mean and standard deviation of each experience dimension measured by each GEQ module. The analysis results show that the Tension/Annoyance dimension (3.250) and Negative Experience (2.961) obtained the highest scores, while Flow consistently showed the lowest scores across the two modules, namely 2.540 and 2.300. These findings indicate that although the game successfully elicits emotional engagement, there are still obstacles in building an optimal gaming experience. Several factors are thought to have contributed to this, including the lack of interactive tutorials, linear level design, and a lack of narrative elements. Therefore, further development focused on improving the instructional aspects and storyline is recommended to enhance the overall user experience.
Co-Authors Agung Riyadi Ardi, Noper Irmansyah Lubis, Ahmadi Mu'minin, Amirul Muhammad Iffaturrahman Naswin, Ahmad Ramadhan, Gilang Bagus Rismayanti, Nurul Suwarno Suwarno Umar Zaky