Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Komputer dan Informasi Prosiding University Research Colloquium
Putri Ayu Pramesti, Putri Ayu
Bogor Agricultural University
Humanities Computer Science & IT Environmental Science Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Parameter Estimation Robust Regression Method of Moment (MM) in Cases of Maternal Death in Indonesia Pramesti, Putri Ayu; Susanti, Yuliana; Pratiwi, Hasih
Prosiding University Research Colloquium Proceeding of The 15th University Research Colloquium 2022: Bidang MIPA dan Kesehatan
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Regression analysis is used to determine the relationship between the dependent and independent variables with a parameter estimator. The parameter estimator that is usually used is the Least Squares Method (LSM), this requires a classical assumption test. Some cases have normality assumptions that are unfulfilled because there are outliers so the result regression parameter estimates are not accurate so that robust regression is used in the analysis. Robust regression is a regression analysis method that can withstand outliers. The purpose of this study is the application of robust regression estimation Method of Moment (MM) with Tukey Bisquare weighting in the case of data on the number of maternal deaths in Indonesia 2020 with the number of maternal deaths as a dependent variable, and with independent variables such as the number of pregnant women who experience bleeding, the number of diabetics in pregnancy, and the number of HIV positive in pregnancy. The result showed that every one unit increase of three independent variables had a positive effect on the number of cases of maternal deaths, each of which was 2,8064; 2,5014; 1,1577.
Classification of Clove Leaf Blister Blight Disease Severity Using Pre-trained Model VGG16, InceptionV3, and ResNet Pramesti, Putri Ayu; Supriyadi, Muhamad Rodhi; Alfin, Muhammad Reza; Noveriza, Rita; Wahyuno, Dono; Manohara, Dyah; Melati; Miftakhurohmah; Warman, Riki; Hardiyanti, Siti; Asnawi
Jurnal Ilmu Komputer dan Informasi Vol. 17 No. 2 (2024): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Informatio
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jiki.v17i2.1237

Abstract

Clove is one of the precious plants produced in Indonesia. Clove has many benefits for humans, but clove cultivation often experiences problems due to disease attacks, including Leaf Blister Blight Disease(CDC). The handling of CDC disease is carried out based on the severity of the symptoms that can be seen on the affected leaves. This research was conducted to obtain a CDC disease classification model, so appropriate treatment can be carried out. This study used the pre-trained VGG16, InceptionV3, and ResNet models for classification. VGG16 got the highest average accuracy of 96.7%. Aside from that, k-fold cross validation improved the model's accuracy.
Co-Authors Alfin, Muhammad Reza ASNAWI Dono Wahyuno Dyah Manohara Melati Miftakhurohmah pratiwi, hasih Rita Noveriza Siti Hardiyanti Supriyadi, Muhamad Rodhi Warman, Riki Yuliana Susanti, Yuliana