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All Journal Jurnal Pendidikan Geografi Undiksha Sinkron : Jurnal dan Penelitian Teknik Informatika Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding
Febrianti, Lusi
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Public Health Social Sciences

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Classification of the Human Development Index in Indonesia Using the Bootstrap Aggregating Method Goldameir, Noor Ell; Yolanda, Anne Mudya; Adnan, Arisman; Febrianti, Lusi
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11173

Abstract

Successful development of the quality of human life in a region is determined by the Human Development Index (HDI). Human development performance based on the HDI can be measured: long and healthy life, knowledge, and a decent standard of living. The HDI is usually grouped into several categories to facilitate the classification of the HDI level of each region. This study aimed to determine the ability of the bootstrap aggregating (bagging) method to classify the HDI by district/city. Bagging is a stochastic machine learning approach that can eliminate the variance of the classifier by producing a bootstrap ensemble to obtain better accuracy results. The dependent variable in this study was the HDI by district/city in 2020. In contrast, life expectancy at birth, expected years of schooling, mean years of schooling, and real expenditure per capita are adjusted as independent variables. Bagging was applied to the high and low categories of HDI data. The bagging method demonstrated good classification performance due to only eight classification errors, namely the HDI data which should be in the high category but classified into the low category by the bagging method. Based on the results of calculations with 25 replications, it can be concluded that the bagging method has a very good performance, with an accuracy value of 92.3%, the sensitivity of 100%, and specificity of 83.33%. The bagging method is considered very good for the classifying the HDI by district/city in Indonesia in 2020 because it has a balanced accuracy of 91.67%.
Microblog dan Mobile Learning: Inovasi Metode Pembelajaran dalam Meningkatkan Creativity Skill Dewi, Kusuma; Indahwati, Kristin; Febrianti, Lusi
Jurnal Pendidikan Geografi Undiksha Vol 9, No 3 (2021): Jurnal Pendidikan Geografi Undiksha
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jjpg.v9i3.36250

Abstract

Kreativitas adalah keterampilan yang penting dimiliki siswa dalam mencapai kesuksesan pembelajaran abad 21. Keterampilan ini dapat dicapai melalui pemanfaatan microblog. Microblog menumbuhkan minat dan mempersiapkan siswa menjadi kreator dalam kehidupan sehari-hari. Pemanfaatan microblog di era digital dapat melalui penerapan mobile learning. Mobile learning mendukung pembentukan keterampilan siswa melalui perangkat mobile. Penelitian ini bertujuan untuk mengajukan inovasi metode pembelajaran daring untuk mencapai kreativitas siswa. Penelitian ini menggunakan pendekatan deskriptif kualitatif. Subjek penelitian adalah siswa kelas XI IPS di SMA Negeri 7 Malang. Metode pembelajaran yang digunakan yaitu mobile learning dengan platform Google Meet dan Google Classroom. Selain itu penelitian ini menggunakan learning tools yaitu Instagram. Hasil penelitian menunjukkan bahwa penggunaan microblog dalam pembelajaran mobile learning dapat membantu pencapaian kreativitas siswa. Hal tersebut dapat dibuktikan dari hasil ketuntasan belajar siswa yang mencapai angka 79% dengan rata-rata nilai yang diperoleh adalah 87,7 dari nilai ketuntasan produk. Inovasi pembelajaran proyek melalui microblog ini dapat menjadi alternatif pembelajaran online.
RESISTANCE EXERCISE TO IMPROVE IMMUNE OF ELDERLY IN NEWNORMAL ERA: REVIEW LITERATURE Cahyaningsih, Andika Nur; Widyastuti, Zulanda Indah; Febrianti, Lusi; Ramadhani, Alinda Nur
Proceedings of Universitas Muhammadiyah Yogyakarta Graduate Conference Vol. 1 No. 2 (2022): Engaging Youth in Community Development to Strengthen Nation's Welfare
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.128 KB)

Abstract

Introduction – The high rate of transmission of Covid-19 in Indonesia has brought enormous changes to society, especially with the applied of new normal regulation. New normal regulation requires the public to continue carrying out their usual activities by implementing health protocols. The elderly are a population with high risk of covid-19 transmission. Various efforts can be made to maintain the immune system in the new normal era, one of them is by doing exercise. One of the exercises that can be done by the elderly is resistance exercise. Purpose – The purpose of this study was to identify the effect of resistance exercise to increase immunity in the elderly based on evidence based. Methodology/Approach – This study is a literature study that summarizes some relevant literature on the same theme. Literature search using 3 databases: Pubmed, Pedro and BMC Central. Key words used in the literature search included: "immune system", "resistance exercise" and "elderly". Findings – Based on the results of the literature review, it was found that resistance exercise can increase immunity in the elderly. The form of resistance exercise are: horizontal leg press, knee extension, knee flexion, horizontal supine, triceps extension pulley, biceps curl, sitting row, plantar flexion, shoulder press, hip flexion-extension. Originality/ Value/ Implication – The elderly can perform resistance exercise regularly to increase immune system during new normal era.
Co-Authors Alinda Nur Ramadhani Arisman Adnan Cahyaningsih, Andika Nur Dewi, Kusuma Goldameir, Noor Ell Indahwati, Kristin Widyastuti, Zulanda Indah Yolanda, Anne Mudya