Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Dunia Kesmas Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE)
Melisah Melisah
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Environmental Science Public Health

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

Found 2 Documents
Search

 1 
HUBUNGAN KEBIASAAN KELUAR PADA MALAM HARI DAN MEMAKAI OBAT NYAMUK DENGAN KEJADIAN MALARIA DI DESA LEMPASING KECAMATAN TELUK PANDAN KABUPATEN PESAWARAN 2015 Melisah Melisah; Dina Dwi Nuryani
JURNAL DUNIA KESMAS Vol 5, No 2 (2016): Volume 5 Nomor 2
Publisher : Fakultas Kesehatan Masyarakat Universitas Malahayati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jdk.v5i2.462

Abstract

Kabupaten Pesawaran merupakan daerah endmis malaria. Kasus di Kecamatan Hanura 2013 sebanyak 1.988, Padang Cermin 63 kasus, dan Pedada 262 kasus. Lempasing salah satu desa di Wilayah kerja Kecamatan Teluk Pandan merupakan salah satu desa endemis malaria, Tahun 2014 Lempasing terjadi kasus malaria Teriana, Tropica dan Mix Malaria. Tujuan penelitian diketahui hubungan kebiasaan keluar pada malam hari dan memakai obat nyamuk dengan kejadian malaria di Desa Lempasing Kecamatan Teluk Pandan Kabupaten Pesawaran.Rancangan penelitian kuantitatif dengan pendekatan cross sectional. Jumlah sampel 92 orang dipilih dengan random sampling sederhana. Analisis menggunakan uji Chi-square dengan derajat kepercayaan 95%.Hasil Penelitian ini memunjukkan bahwa ada hubungan kebiasaan keluar pada malam hari dengan kejadian malaria (p=0,000), kebiasaan memakai obat nyamuk (p=0,000) dengan kejadian malaria. Disarankan bagi masyarakat desa Lempasing jika harus ada kegiatan di luar rumah pada malam hari harus menggunakan obat anti nyamuk atau menggunakan pakaian yang menutup badan.Kata Kunci : Malaria, keluar, obat nyamuk.
Performance Comparison of Boosting Algorithms in Spices Classification Using Histogram of Oriented Gradient Feature Extraction Muhathir Muhathir; Reydo Trisno Pangestu; Ira Safira; Melisah Melisah
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v4i1.13710

Abstract

Spice classification is an important task in the food industry to ensure food safety and quality. This study focuses on the classification of spices using the HoG feature extraction method and boosting algorithms. The objective of this research is to compare the performance of four different models of boosting algorithms, namely Adaboost Classifier, Gradient Boosting Classifier, XGB Classifier, and Light GBM Classifier, in classifying spices. The evaluation metrics used in this research are Precision, Recall, F1-Score, F2-Score, Jaccard Score, and Accuracy. The results show that the XGB Classifier model achieved the best performance, with a precision of 0.811, recall of 0.809, and F1-score of 0.809, while the Adaboost Classifier model had the lowest performance, with a precision of 0.709, recall of 0.689, and F1-score of 0.682. Overall, the results indicate a fairly good success rate in classifying spices using the HoG feature extraction method and boosting algorithms. However, further evaluation is needed to improve the accuracy of the classification results, such as increasing the number of training data or considering the use of other feature extraction methods
Co-Authors Dina Dwi Nuryani Ira Safira Muhathir, Muhathir Reydo Trisno Pangestu