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All Journal Indonesian Journal of Data and Science Kharisma Tech Journal of Technology Research in Information System and Engineering International Journal of Artificial Intelligence in Medical Issues
Angriani, Husni
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Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Engineering Health Professions Mathematics Medicine & Pharmacology Public Health

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Enhancing Disease Management in Mango Cultivation: A Machine Learning Approach to Classifying Leaf Diseases Mastrika Giri, Gst. Ayu Vida; Musdar, Izmy Alwiah; Angriani, Husni; Taruk, Medi
Indonesian Journal of Data and Science Vol. 4 No. 3 (2023): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v4i3.111

Abstract

This study explores the application of machine learning techniques in the agricultural domain, focusing on the classification of two common diseases in mango leaves: Powdery Mildew and Sooty Mould. Utilizing the MangoLeafBD dataset, the research employs a Gradient Boosting Classifier, enhanced with mean shift image segmentation and Hu moments for feature extraction. The performance of the model was rigorously evaluated through 5-fold cross-validation, yielding insights into its accuracy, precision, recall, and F1-score. The results demonstrate moderate success, with the highest accuracy and precision observed in the initial fold, indicating the model's potential for reliable disease identification. The study addresses the challenge of distinguishing between diseases with similar symptomatic appearances, offering a novel, data-driven approach for disease management in mango cultivation. This research contributes to the growing field of precision agriculture, highlighting the potential of machine learning in enhancing disease diagnosis and treatment strategies, thus supporting sustainable agricultural practices.
Optimizing Neurodegenerative Disease Classification with Canny Segmentation and Voting Classifier: An Imbalanced Dataset Study Sinra, A.; Waluyo Poetro, Bagus Satrio; Angriani, Husni; Zein, Hamada; Musdar, Izmy Alwiah; Taruk, Medi
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.v1i2.97

Abstract

This study explores the efficacy of a Voting Classifier, combining Logistic Regression, Random Forest, and Gaussian Naive Bayes, in the classification of neurodegenerative diseases, focusing on Alzheimer's Disease (AD), Parkinson’s Disease (PD), and control groups. Utilizing a dataset pre-processed with Canny segmentation and Hu Moments feature extraction, the research aimed to address the challenges posed by imbalanced datasets in medical image classification. The classifier's performance was evaluated through a 5-fold cross-validation approach, with metrics including accuracy, precision, recall, and F1-Score. The results revealed a consistent recall rate of approximately 46% across all folds, indicating the model's effectiveness in identifying cases of neurodegenerative diseases. However, the precision and F1-Score were notably lower, averaging around 22% and 29%, respectively, underscoring the difficulties in achieving accurate classification in imbalanced datasets. The study contributes to the understanding of machine learning applications in medical diagnostics, specifically in the challenging context of neurodegenerative disease classification. It highlights the potential of using advanced image processing techniques combined with machine learning ensembles in enhancing diagnostic accuracy. However, it also draws attention to the inherent challenges in such approaches, particularly regarding precision in imbalanced datasets. Recommendations for future research include exploring data balancing techniques, alternative feature extraction methods, and different machine learning algorithms to improve the precision and overall performance. Additionally, applying the model to a broader and more diverse dataset could provide more generalizable and robust findings. This study is significant for researchers and practitioners in medical imaging and machine learning, offering insights into the complexities and potential of automated disease classification
DESAIN PENGEMBANGAN MODUL UNTUK PENJAHIT PADA APLIKASI JAHITKU MENGGUNAKAN USER CENTERED DESIGN Phoandy, Frederica; Angriani, Husni; Pontoh, Zaenab
KHARISMA Tech Vol 20 No 1 (2025): KHARISMATech Journal
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/kharismatech.v20i1.543

Abstract

Penelitian ini bertujuan untuk merancang User Interface (UI) pada website jahitkumenggunakan metode User Centered Design (UCD) yang dapat memudahkan penjahit dalammelakukan proses pendaftaran diri dan mengelola pesanan secara mandiri dengan desainyang user-friendly, intuitif dan sesuai dengan preferensi penjahit. Adanya keterbatasan fiturpada website jahitku dimana penjahit masih memerlukan admin untuk proses pendaftaransehingga menghanmbat efisiensi dan pertisipasi penajhit terkhusus penajhit kecil atauindividu. Penerapan metode User Centered Design (UCD) digunakan sebagai landasan untukmemberikan kemudahan bagi pengguna. User Centered Design (UCD) merupakan metodeyang berfokus pada kebutuhan pengguna yang dilakukan dengan cara membangun ataumerancang sistem yang melibatkan langsung pengguna dalam proses perancangannya. Hasilpengujian dari metode UCD memberikan kemudahan bagi pengguna dalam melakukanpendaftaran secara mandiri, menginput desain, membalas ulasan, membuat pesanan, danmelihat riwayat pesanan. Penerapan metode UCD mampu mengatasi masalah kesulitan yangdialami oleh penjahit pada website jahitku, serta menambah fitur untuk penjahit agar penjahitjuga dapat mudah menggunakan website.
REDESIGN UI/UX BANK PLASTIK MENGGUNAKAN METODE USER CENTERED DESIGN Aziza, Fakhita Nur; Angriani, Husni; Thayf, Mohammad Sofyan S.
JTRISTE Vol 12 No 1 (2025): JTRISTE
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/jtriste.v12i1.568

Abstract

"Bank Plastik" is an application that facilitates the exchange of plastic waste for money. The results of a user experience survey for the Bank Plastik application indicated several areas that require improvement, one of which is the UI/UX design. To validate the survey results, a first-stage testing was conducted to determine whether a redesign of the Bank Plastik application is necessary. Based on the first-stage testing, the original design received a score of 50.8, indicating that the score falls in the "poor" category and is below the standard SUS (System Usability Scale) score of 53. Therefore, a redesign of the UI/UX of the Bank Plastik application is deemed necessary. The User Centered Design method was employed to carry out the redesign of the Bank Plastik UI/UX to enhance the user experience when using the application. The results of the User Centered Design implementation, using the task success metric, revealed issues with tasks 1 and 2. The findings from the time on task metric showed that respondents were able to complete all tasks but faced challenges with the slide slogan page. Respondents two and five experienced delays more frequently compared to other respondents. The testing of the error metric yielded an average error rate for each task of 16% across all respondents. The results of the second stage testing demonstrated that the satisfaction score for the redesign was higher than that of the original design in the first stage, with a redesign score of 75.5, indicating an "excellent" level of satisfaction. In conclusion, based on the survey and testing results, it is clear that a redesign of the Bank Plastik application's UI/UX has been successful in improving the user experience.
ANALISIS DAN OPTIMASI KINERJA APLIKASI POTIO MENGGUNAKAN LOAD TESTING JMETER Garjitno, Meike; Angriani, Husni; Saharaeni, Yeni
JTRISTE Vol 12 No 2 (2025): JTRISTE
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/jtriste.v12i2.625

Abstract

Optimasi database dan kode terbukti menurunkan error hingga 0% serta meningkatkan throughput dan waktu respon aplikasi Potio meskipun beban pengguna tinggi. Potio merupakan aplikasi pengingat konsumsi obat bagi penderita penyakit kronis. Pengujian kinerja dilakukan menggunakan uji beban (load testing) dengan Apache JMeter pada enam titik layanan utama (endpoint) dengan skenario 50, 100, dan 150 pengguna serentak. Hasil awal menunjukkan penurunan performa pada 150 pengguna, ditandai dengan meningkatnya waktu respon, turunnya throughput, dan munculnya error. Dua eksperimen dilakukan, yaitu peningkatan kecepatan jaringan internet serta optimasi database dan kode. Hasil menunjukkan bahwa meskipun peningkatan jaringan memberi dampak positif, optimasi database dan kode lebih konsisten memperbaiki performa, terbukti dari penurunan error hingga 0%. Kesimpulannya, perbaikan sisi sistem lebih efektif dibanding hanya mengandalkan peningkatan jaringan.
REKOMENDASI LAPTOP TERHADAP CALON PEMBELI PT. GENIUS COMPUTER CENTRE MENGGUNAKAN SIMPLE ADDITIVE WEIGHTING Ursipuny, Natasha; Angriani, Husni; Pontoh, Zaenab
JTRISTE Vol 11 No 1 (2024): JTRISTE
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/jtriste.v11i1.512

Abstract

This research aims to implement the Simple Additive Weighting (SAW) method in providing recommendations to potential laptop buyers at PT.Genius Computer Centre. Various laptop variants with different brands and specifications make it difficult for potential buyers to choose a laptop that suits their needs. The implementation of the SAW method is used as a basis for recommending laptops based on user requirements. SAW is a commonly used method in decision-making and involves assessments based on predefined criteria weights. The results of the SAW calculations provide recommendations for laptops that meet the user's needs, helping potential buyers choose a laptop that fits their requirements. The implementation of the SAW method in the decision support system can address the difficulties faced by potential laptop buyers at PT. Genius Computer Centre in choosing a suitable laptop and provide recommendations that can enhance their understanding of the required laptop specifications. This research has the potential to significantly improve the laptop shopping experience for potential buyers.
Co-Authors Aziza, Fakhita Nur Garjitno, Meike Gst. Ayu Vida Mastrika Giri Hamada Zein izmy alwiah musdar Mohammad Sofyan S. Thayf Phoandy, Frederica Poetro, Bagus Satrio Waluyo Saharaeni, Yeni Sinra, A. Taruk, Medi Ursipuny, Natasha Zaenab Pontoh, Zaenab