<span class="fontstyle0">The study was aimed to introduce a new model construction regarding the transmission of Coronavirus Disease (henceforth, COVID-19) in human population. The mathematical model was constructed by taking into consideration several epidemiology parameters that are closely identical with the real condition. The study further conducted an analysis on the model by identifying the endemicity parameters of COVID-19, i.e., the presence of disease-free equilibrium (DFE) point and basic reproduction number. The next step was to carry out sensitivity analysis to find out which parameter is the most dominant to affect the diseaseโs endemicity. The results revealed that the parameters </span><span class="fontstyle2">๐, ๐</span><span class="fontstyle2">๐ ๐</span><span class="fontstyle2">, ๐ผ,, </span><span class="fontstyle0">and </span><span class="fontstyle2">๐ </span><span class="fontstyle0">in sequence showed the most dominant sensitivity index towards the basic reproduction number. Moreover, the results indicated positive index in parameters </span><span class="fontstyle2">๐ </span><span class="fontstyle0">and </span><span class="fontstyle2">๐</span><span class="fontstyle2">๐ ๐ </span><span class="fontstyle0">that represented transmission chances during contact as well as contact rate between vulnerable individuals and exposed individual. This suggests that an<br />increase in the previous parameter value could potentially enlarge the endemicity of COVID-19. On the other hand, parameters </span><span class="fontstyle2">๐ผ </span><span class="fontstyle0">and </span><span class="fontstyle2">๐</span><span class="fontstyle0">, </span><span class="fontstyle0">representing movement rate of exposed<br />individuals to the quarantine class and proportion of quarantined exposed individuals, showed negative index. The numbers indicate that an increase in the parameter value could decrease the diseaseโs endemicity. All in all, the study concludes that treatments for COVID-19 should focus on<br />restriction of interaction between individuals and optimization of quarantine.</span> <br /><br />
Tulisan ini bertujuan untuk mengetahui perbedaan hasil belajar siswa yang mendapatkan pembelajaran dengan menggunakan media berbasis ICT dengan siswa yang mendapatkan pembelajaran menggunakan model pembelajaran konvensional pada materi dimensi tiga. Metode penelitian yang digunakan dalam penelitian ini adalah metode eksperimen dengan menggunakan Posttest-Only Control Group Design. Hasil penelitian menunjukkan bahwa rata-rata hasil belajar siswa yang mendapatkan pembelajaran dengan menggunakan media ICT lebih tinggi dari rata-rata hasil belajar siswa yang mendapatkan pembelajaran dengan menggunakan model pembelajaran konvensional pada materi dimensi tiga. ABSTRACTThese paper have purposed to know the difference of result between the students that have learned by using IT and the students who had subject follow by using conventional learning method in dimension three subject. The research method used in this study is an experimental method using Posttest-Only Control Group Design. The results showed that the average learning outcomes of students who get learning by using ICT media is higher than the average learning outcomes of students who get learning by using conventional learning models on the three dimensional material.
Suatu graf dikatakan terhubung pelangi jika terdapat lintasan antara dua titik yang setiap sisi-sisinya memiliki warna berbeda. Misalkan terdapat suatu graf G tak trivial dengan definisi warna c:E(G)->{1,2,3,...}, maka bilangan terhubung pelangi dari graf G yaitu minimum k dari pewarnaan-kย pelangi yang digunakan untuk mewarnai graf G dan dinotasikan dengan rc(G). Tujuan dari penelitian ini yaitu untuk menentukan bilangan terhubung pelangi pada graf salju (Sn_m). Metode yang digunakan pada penelitian ini yaitu metode studi literatur dengan prosedur sebagai berikut; menggambar graf salju, mencari pola bilangan terhubung pelangi, dan membuktikan teorema bilangan terhubung pelangi pada graf salju (Sn_m). Sehingga diperoleh rc(Sn_m)=m+1 untuk 3<=m<=7 dan m={9,10} dan rc(Sn_m)=m untuk m=8 dan m>=11.
This paper discusses the dynamics of COVID-19 transmission by involving quarantine interventions. The model was constructed by involving three classes of infectious causes, namely the exposed human class, asymptotically infected human class, and symptomatic infected human class. Variables were representing quarantine interventions to suppress infection growth were also considered in the model. Furthermore, model analysis is focused on the existence of equilibrium points and numerical simulations to visually showed population dynamics. The constructed model forms the SEAQIR model which has two equilibrium points, namely a disease-free equilibrium point and an endemic equilibrium point. The stability analysis showed that the disease-free equilibrium point was locally asymptotically stable at R0<1 and unstable at R0>1. Numerical simulations showed that increasing interventions in the form of quarantine could contribute to slowing the transmission of COVID-19 so that it is hoped that it can prevent outbreaks in the population.
ABSTRAKMakalah ini membahas dinamika transmisi COVID-19 dengan melibatkan intervensi karantina. Model dikonstruksi dengan melibatkan tiga kelas penyebab infeksi, yaitu kelas manusia terpapar, kelas manusia terinfeksi tanpa gejala klinis, dan kelas manusia terinfeksi disertai gejala klinis. Variabel yang merepresentasikan intervensi karantina untuk menekan pertumbuhan infeksi juga dipertimbangkan pada model. Selanjutnya, analisis model difokuskan pada eksistensi titik kesetimbangan dan simulasi numerik untuk menunjukkan dinamika populasi secara visual. Model yang dikonstruksi membentuk model SEAQIR yang memiliki dua titik kesetimbangan, yaitu titik kesetimbangan bebas penyakit dan titik kesetimbangan endemik. Analisis kestabilan menunjukkan bahwa titik kesetimbangan bebas penyakit bersifat stabil asimtotik lokal pada saat R01 dan tidak stabil pada saat R01. Simulasi numerik menunjukkan bahwa peningkatan intervensi berupa karantina dapat berkontribusi memperlambat transmisi COVID-19 sehingga diharapkan dapat mencegah terjadinya wabah pada populasi.ABSTRACTThis paper discusses the dynamics of COVID-19 transmission by involving quarantine interventions. The model was constructed by involving three classes of infectious causes, namely the exposed human class, asymptotically infected human class, and symptomatic infected human class. Variables were representing quarantine interventions to suppress infection growth were also considered in the model. Furthermore, model analysis is focused on the existence of equilibrium points and numerical simulations to visually showed population dynamics. The constructed model forms the SEAQIR model which has two equilibrium points, namely a disease-free equilibrium point and an endemic equilibrium point. The stability analysis showed that the disease-free equilibrium point was locally asymptotically stable at R01 and unstable at R01. Numerical simulations showed that increasing interventions in the form of quarantine could contribute to slowing the transmission of COVID-19 so that it is hoped that it can prevent outbreaks in the population.
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