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All Journal Perfecting a Video Game with Game Metrics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Edukasi dan Penelitian Informatika (JEPIN) Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Esti Suryani
Universitas Sebelas Maret
Computer Science & IT Education Electrical & Electronics Engineering Engineering Medicine & Pharmacology Social Sciences Other

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Classification of blast cell type on acute myeloid leukemia (AML) based on image morphology of white blood cells Wiharto Wiharto; Esti Suryani; Yuda Rizki Putra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.8666

Abstract

AML is one type of cancer of the blood and spinal cord. AML has a number of subtypes including M0 and M1. Both subtypes are distinguished by the dominant blast cell type in the WBC, the myeloblast cells, promyelocyte, and myelocyte. This makes the diagnosis process of leukemia subtype requires identification of blast cells in WBC. Automatic blast cell identification is widely developed but is constrained by the lack of data availability, and uneven distribution for each type of blast cell, resulting in problems of data imbalance. This makes the system developed has poor performance. This study aims to classify blast cell types in WBC identified AML-M0 and AML-M1. The method used is divided into two stages, first pre-processing, image segmentation and feature extraction. The second stage, perform resample, which is continued over sampling with SMOTE. The process is done until the amount of data obtained is relatively the same for each blast cell, then the process of elimination of data duplication, randomize, classification and performance measurement. The validation method used is k-fold cross-validation with k=10. Performance parameters used are sensitivity, specifyicity, accuracy, and AUC. The average performance resulting from classification of cell types in AML with Random Forest algorithm obtained 82.9% sensitivity, 92.1% specificity, 89.6% accuracy and 87.5% AUC. These results indicate a significant improvement compared to the system model without using SMOTE. The performance generated by reference to the AUC value, the proposed system model belongs to either category, so it can be used for further stages of leukemia subtype AML-M0 and AML-M1.
The Segmentation Analysis of Retinal Image Based on K-means Algorithm for Computer-Aided Diagnosis of Hypertensive Retinopathy Wiharto Wiharto; Esti Suryani
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 2: June 2020
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.838 KB) | DOI: 10.52549/ijeei.v8i2.1287

Abstract

Computer-aided diagnosis of hypertensive retinopathy (CAD-HR) is performed by analyzing the retinal image. The analysis is carried out in several stages, one of which is image segmentation. The segmentation carried out so far generally uses a region-based and threshold-based approach. There is not yet a clustering-based approach, and there has been no previous analysis of why clustering-based is not yet widely used. This study aims to conduct clustering-based Segmentation analysis, specifically k-means clustering in CAD-HR. The research method used is divided into four stages, namely preprocessing, segmentation, feature extraction using fractal dimensions, statistical analysis for classification, and classification. Testing is done using the DRIVE and STARE datasets. The results of statistical tests showed that the number of clusters 3 was able to provide a significant difference between the fractal positive and negative dimensions of hypertensive retinopathy. The model of CAD-RH using the k-means algorithm for segmentation method is able to provide 80% sensitivity performance. The k-mean algorithm can be used as an alternative to segmenting retinal blood vessels.
Design System for Education & Health Counseling (E-Pedakos) Posyandu in Indonesia Based E-Learning W Wiharto; Esti Suryani; Siti Fatimah
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2015: Proceeding ISETH (International Conference on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

The model system of education and maternal and child health counseling at the Posyandu has been done with the direct model, namely Posyandu. The increasing number of women working population affects the lessening number of participants as well as the effectiveness of this activity. This study proposed a model of maternal and child health education and counseling based on e-learning with a reference of electronic education and health counseling (e-pedakos). This study was conducted in several stages. The first stage was the establishment and development of e-pedakos systems and infrastructure. Subsequently, it was examined related to the public’s attendance and responses, which was preceded by the training on how to use E-pedakos. The last stage was the survey on system effectiveness. This counseling model counseling of e-pedakos provides an alternative to resolve the weaknesses of conventional posyandu. It promotes maternal education and counseling which can be done anytime and anywhere.
Rekomendasi Makanan Pasien Hiperlipidiemia Berdasarkan Hasil Klasifikasi Menggunakan Metode Naïve Bayes dan Decision Tree Wafirotul Laila; Wisnu Widiarto; Ardhi Wijayanto; Esti Suryani
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 8, No 2 (2022): Volume 8 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v8i2.56386

Abstract

Makanan merupakan kebutuhan manusia untuk memenuhi nutrisi dalam keberlangsungan hidup. Namun setiap orang perlu memperhatikan makanan yang dikonsumsi karena akan memengaruhi kondisi tubuh. Salah satu zat dalam tubuh manusia yang perlu diperhatikan ketika mengonsumsi makanan adalah lemak. Penelitian terkait konsumsi makanan dengan kadar lemak dalam tubuh sudah banyak dilakukan. Terbukti terdapat jenis makanan yang dapat memengaruhi kesehatan tubuh karena menyebabkan zat lemak yang berlebihan. Penelitian yang dilakukan kali ini adalah klasifikasi data kebutuhan gizi dengan membandingkan algoritma naïve bayes dan decision tree. Hasil klasifikasi antara kedua algoritma tersebut digunakan untuk memberikan rekomendasi makanan yang sesuai untuk dikonsumsi oleh orang yang menderita hiperlipidemia, yakni kondisi di mana kadar lemak dalam tubuh berlebihan. Penelitian dimulai dari pengumpulan data, pra-proses data dengan normalisasi, klasifikasi dengan beberapa model naïve bayes dan algoritma decision tree, menganalisis hasil klasifikasi dengan confusion matrix, dan melakukan implementasi rekomendasi makanan berdasarkan hasil model klasifikasi yang paling optimal. Pada penelitian ini diperoleh hasil bahwa model ComplementNB memiliki akurasi tinggi dibanding model lain namun secara keseluruhan algoritma decision tree lebih stabil dibanding naïve bayes.
Co-Authors Ardhi Wijayanto Siti Fatimah W Wiharto Wafirotul Laila Wiharto Wiharto Wisnu Widiarto Yuda Rizki Putra