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All Journal BIMASTER ComTech: Computer, Mathematics and Engineering Applications GERVASI: Jurnal Pengabdian kepada Masyarakat JUDIKA (JURNAL PENDIDIKAN UNSIKA) Jurnal Matematika UNAND Jurnal Pengabdian kepada Masyarakat Nusantara Tensor: Pure and Applied Mathematics Journal Jurnal Abdimas Bina Bangsa Jurnal Eurekamatika
NUR’AINUL MIFTAHUL HUDA
Universitas Tanjungpura
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Journal : Jurnal Matematika UNAND

 1 
ANALISIS KEBIJAKAN PEMERINTAH TERHADAP KASUS COVID-19 DI BALI MENGGUNAKAN MODEL DERET WAKTU DENGAN FAKTOR INTERVENSI NURFITRI IMRO’AH; NUR’AINUL MIFTAHUL HUDA
Jurnal Matematika UNAND Vol 10, No 3 (2021)
Publisher : Jurusan Matematika FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmu.10.3.369-378.2021

Abstract

Kebijakan mengenai kewajiban pelaku perjalanan domestik yang datang ke Bali untuk menunjukkan hasil negatif tes swab Polymerase Chain Reaction (PCR) merupakan salah satu bentuk intervensi dalam menekan banyaknya penambahan kasus positif Coronavirus Disease 2019 (Covid-19) di Bali. Penelitian ini menggunakan model deret waktu dengan faktor intervensi dalam menganalisis dampak setelah dikeluarkannya kebijakan tersebut. Selain itu, penelitian ini juga memprediksi banyaknya kasus Covid-19 di Bali mulai 29 - 31 Maret 2021. Hasil dari penelitian ini menunjukkan bahwa kebijakan yang dikeluarkan oleh Pemerintah Provinsi Bali merupakan salah satu langkah tepat dalam menangani penambahan kasus harian positif Covid-19 di Bali. Hal itu terlihat dari penurunan banyaknya kasus positif di Bali hingga akhir Maret 2021.Kata Kunci: Covid-19, Kebijakan, Deret waktu, Intervensi
ANALISIS SPASIAL MODEL INVERSE DISTANCE WEIGHTING PADA PENYEBARAN KASUS POSITIF COVID-19 PER KABUPATEN DI PULAU JAWA Nur'ainul Miftahul Huda; Nurfitri Imro'ah
Jurnal Matematika UNAND Vol 11, No 1 (2022)
Publisher : Jurusan Matematika FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmu.11.1.64-73.2022

Abstract

Suatu lokasi saling berhubungan satu dengan yang lainnya dan sesuatu yang berjarak dekat memiliki pengaruh yang lebih dibandingkan dengan lokasi yang jauh. Hal ini yang mendasari adanya keterkaitan suatu kejadian antar lokasi atau disebut autokorelasi spasial. Salah satu metode yang dapat digunakan untuk melihat pola keterkaitan tersebut adalah metode Inverse Distance Weighting (IDW). Metode ini menggunakan faktor parameter pengaruh yaitu power (p) dalam melihat pengaruh lokal antar titik lokasi. Semakin besar niai p berarti nilai titik tak tersampel menjadi lebih terlokalisasi dan sebaliknya. Input yang digunakan pada model ini adalah koordinat titik untuk titik tersampel beserta nilai dari setiap titik yang akan diestimasi. Pada penelitian ini kasus yang digunakan adalah kasus terkonfirmasi positif virus Covid-19 per 76 kabupaten/kota di Pulau Jawa hingga tanggal 26 Februari 2022. Penelitian ini bertujuan untuk melihat pemetaan kasus terkonfirmasi positif di Pulau Jawa per kabupaten melalui peta kontur menggunakan model IDW. Kabupaten/kota yang tidak dijadikan lokasi tersampel dapat diestimasi melalui model ini. Langkah pertama adalah membuat peta grid, kemudian menghitung jarak antar lokasi tersampel. Selanjutnya jarak tersebut digunakan untuk menghitung bobot setiap lokasi tersampel. Langkah berikutnya adalah estimasi nilai di lokasi tak tersampel menggunakan nilai power. Nilai power yang digunakan pada penelitian ini adalah 0,5;1;2;3;4;5. Pemilihan nilai power yang tepat didasarkan pada nilai RMSE terkecil. Hasilnya diperoleh nilai power yang optimal adalah saat p=2 dan diperoleh estimasi kasus positif Covid-19 di lokasi tak tersampel sehingga diperoleh peta kontur.
AN ANALYSIS OF CLUSTER TIMES SERIES FOR THE NUMBER OF COVID-19 CASES IN WEST JAVA Nurfitri Imro'ah; Nur'ainul Miftahul Huda
Jurnal Matematika UNAND Vol 12, No 3 (2023)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.12.3.203-212.2023

Abstract

The government may be able to develop more effective strategies for dealing with COVID-19 cases if it groups districts and cities according to the features of the number of Covid-19 cases being reported in each district or city. The data can be more easily summarized with the help of cluster analysis, which organizes items into groups according to the degree of similarity between members. Since it is possible to group more than one period together, the generation of clusters based on time series is a more efficient method than clusters that are created for each individual unit. Using a time series cluster hierarchical technique that has complete linkage, the purpose of this study is to categorize the number of instances of Covid-19 that have been found in West Java by district or city. The data that was used comes from monthly reports of Covid-19 instances compiled by West Java districts from 2020 to 2022. The Autocorrelation Function (ACF) distance cluster was utilized in this investigation to determine how closely cluster members are related to one another. According to the findings, there could be as many as seven separate clusters, each including a unique assortment of districts and cities. Cluster 3, which is comprised of three different cities and regencies, including Bandung City, West Bandung Regency, and Sumedang Regency, has an average number of cases that is 66, making it the cluster with the highest number of cases overall. A value of 0.2787590 is obtained for the silhouette coefficient as a result of the established grouping. This value suggests that the structure of the newly created cluster is quite fragile.The government may be able to develop more eective strategies fordealing with COVID-19 cases if it groups districts and cities according to the featuresof the number of Covid-19 cases being reported in each district or city. The data canbe more easily summarized with the help of cluster analysis, which organizes items intogroups according to the degree of similarity between members. Since it is possible togroup more than one period together, the generation of clusters based on time series isa more ecient method than clusters that are created for each individual unit. Using atime series cluster hierarchical technique that has complete linkage, the purpose of thisstudy is to categorize the number of instances of Covid-19 that have been found in WestJava by district or city. The data that was used comes from monthly reports of Covid-19 instances compiled by West Java districts from 2020 to 2022. The AutocorrelationFunction (ACF) distance cluster was utilized in this investigation to determine howclosely cluster members are related to one another. According to the ndings, there couldbe as many as seven separate clusters, each including a unique assortment of districtsand cities. Cluster 3, which is comprised of three dierent cities and regencies, includingBandung City, West Bandung Regency, and Sumedang Regency, has an average numberof cases that is 66, making it the cluster with the highest number of cases overall. Avalue of 0.2787590 is obtained for the silhouette coecient as a result of the establishedgrouping. This value suggests that the structure of the newly created cluster is quitefragile.
Co-Authors Abang Yogi Pratama Ahmad Fernanda Arini, Nani Fitria Bayu Prihandono Dadan Kusnandar Daniel Happy Putra Dea Rizki Darmawanti Eligia Helvianti Tri Lina P ERNA YULIANTI Evi Novian Evi Noviani Fahiza Syanaya Fansiskus Fran Fransiskus Fran Fransiskus Fran Helmi Helmi Helmi Imro'ah, Nurfitri Laurens Paskhia Dirda Rusanditia Mariatul Kiftiah Meliana Pasaribu Mudinillah, Adam Muhammad Septian Nani Fitria Arini Naomi Nessyana Debataraja Nilamsari Kusumastuti Nurfitri Imro'ah Nurfitri Imro'ah Nurfitri Imroah NURFITRI IMRO’AH Nurfitri Imro’ah Rika Mailanda Sari Devi Asri Shantika Martha Theresia Resi Trydini Umairah, Tarisa Utami, Dewi Setyo Wirda Andani Yudhi Yundari, Yundari Yusi Sania