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Analisis Spasial Persebaran Jumlah Kasus Malaria di Kalimantan Timur Menggunakan Indeks Moran dan Local Indicator Spatial of Autocorrelation Hadisti, Zahrah Dhafina; Hayati, Memi Nor; Fauziyah, Meirinda
EKSPONENSIAL Vol 15 No 1 (2024): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v15i1.1232

Spatial analysis is an analysis that considers the location and distance of an object in the research data. Moran’s index is one of the spatial methods used to analyze spatial autocorrelation globally. Furthermore, there is the Local Indicator of Spatial Autocorrelation (LISA) method which is used to analyze spatial autocorrelation locally. This study aims to determine whether there is spatial autocorrelation and determine the distribution pattern formed in the data on the average number of malaria cases in East Kalimantan based on the regency/city during 2018-2022. The results showed that based on the Moran index globally, there was no spatial autocorrelation in the average number of malaria cases in East Kalimantan in 2018-2022. The type of spatial pattern in the distribution of malaria cases in East Kalimantan is a clustering pattern indicated by the clustering of malaria cases in each district/city in East Kalimantan. Furthermore, the results of spatial autocorrelation using LISA show that locally there is spatial autocorrelation in several districts/cities in East Kalimantan, namely Paser, Kutai Timur, Kutai Barat and Penajam Paser Utara.

FLEXIBLY SHAPED SPATIAL SCAN STATISTIC FOR MAPPING INDONESIAN STUNTING INCIDENTS Fauziyah, Meirinda; Asnita, Asnita; Hayati, Memi Nor; Hadistii, Zahrah Dhafiinia
MAp (Mathematics and Applications) Journal Vol 5, No 2 (2023)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v5i2.7083

The early stages of toddler growth are vulnerable to the environment around them. The growth of toddlers can be influenced by the nutritional intake they receive. One of the poor nutritional statuses that often occurs in toddlers is stunting. Toddlers who experience stunting are at risk of decreasing intellectual abilities, productivity, and increasing the risk of degenerative diseases in the future. The research variables used are the percentage of the poor population and the prevalence of stunting in Indonesia in 2021 using the Flexibly Shaped Spatial Scan Statistic (FSSS) analysis method. The results of the research show that there are areas in hotspot 1 which are areas potentially prone to stunting prevalence. Provinces that are potentially vulnerable are Aceh, North Sumatra, West Sumatra, Riau, Jambi, Bengkulu.

Klasterisasi Prevalensi Stunting Menggunakan K-Prototype pada Data Campuran Marsandy, Aldwin Falah Hasan; Hayati, Memi Nor; Fauziyah, Meirinda
METIK JURNAL Vol 8 No 2 (2024): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v8i2.824

Cluster analysis is a statistical method for grouping objects based on the similar characteristics of each object. One of the algorithms used in cluster analysis is K-Prototype, which was developed to handle mixed data, namely numerical and categorical data. The validation method used to determine the optimal number of clusters in K-Prototype cluster analysis is the Elbow method. The aim of the research is to determine the optimal number of clusters and optimal cluster results on the prevalence of stunting and indicators that influence the prevalence of stunting in Indonesia in 2022. The results of the research show that the optimal number of clusters produced is 4 clusters, using the Elbow graph the WCSS (Within Cluster Sum Square) value is obtained. optimal is 65.83. Cluster 1 consists of 2 provinces, cluster 2 consists of 7 provinces, cluster 3 consists of 10 provinces, and cluster 4 consists of 15 provinces.

Digitalisasi Desa Dondang: Transformasi Layanan Publik Melalui Optimasi Website sebagai Katalis Perubahan Darnah, Darnah; Fauziyah, Meirinda; Dani, Andrea Tri Rian
Journal of Research Applications in Community Service Vol. 3 No. 4 (2024): Journal of Research Applications in Community Service
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/jarcoms.v3i4.3430

Optimalisasi website Kelurahan Dondang merupakan salah satu program big77 yang lahir dari suatu permasalahan yaitu perlunya lebih memanfaatkan website sebagai media informasi dan akses layanan terpadu untuk meningkatkan aksesibilitas informasi dan efektivitas pelayanan publik. Program ini dilaksanakan selama 40 hari sejak 8 Juli 2024 hingga 12 Agustus 2024 dengan melibatkan pihak Desa Dondang sebagai Mitra Pengabdian. Metode yang digunakan dalam pelaksanaan program meliputi perencanaan, observasi data kependudukan, validasi data, dan input data ke dalam sistem. Pada tahap awal, disusun alur kerja sebagai peta jalan pelaksanaan program optimasi website. Observasi terhadap data kependudukan mengungkapkan adanya banyak data yang memerlukan validasi akibat kesalahan manusia (human error). Proses selanjutnya adalah validasi data yang diikuti dengan penginputan data ke dalam sistem untuk membangun database informasi yang akurat. Hasil dari program ini adalah tersedianya website Kelurahan Dondang yang lengkap dengan fitur pengelolaan data administrasi, layanan informasi online, dan transparansi kegiatan pemerintah. Website ini mempermudah aparat kelurahan dalam pelayanan publik, meningkatkan kecepatan dan akurasi administrasi, serta mendukung keterbukaan informasi bagi masyarakat. Dengan optimalisasi ini, pemerintah dapat mengidentifikasi permasalahan lokal dan membuat kebijakan pembangunan yang lebih terfokus.

ANALISIS DINAMIK MODEL MATEMATIKA PENYEBARAN PENYAKIT KECANDUAN GAME ONLINE DENGAN MEMPERHATIKAN FAKTOR EDUKASI Wigantono, Sri; A'yun, Qonita Qurrota; Sandariria, Hardina; Dani, Andrea Tri Rian; Fauziyah, Meirinda
MAp (Mathematics and Applications) Journal Vol 6, No 2 (2024)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v6i2.10065

Kecanduan bermain game online adalah bentuk penggunaan aplikasi permainan yang kurang bijak. Dampak buruk dan banyak masalah sosial muncul akibat dari kecanduan bermain game online. Pada penelitian ini dibahas model matematika penyebaran penyakit kecanduan bermain game online dengan memperhatikan faktor edukasi. Model ini bertipe SEAR yang terdiri atas empat kompartemen, yaitu Susceptible (rentan), Exposed (terpapar), Addicted (kecanduan), dan Recovered (sembuh). Kemudian, pada penelitian ini ditentukan titik setimbang, bilangan reproduksi dasar, dan dilakukan analisis kestabilan titik setimbang yang sudah diperoleh. Berdasarkan hasil analisis kestabilan titik setimbang, didapat bahwa titik setimbang bebas penyakit model bersifat stabil asimtotis jika bilangan reproduksi dasar bernilai kurang dari satu dan titik setimbang endemik bersifat stabil asimtotis jika bilangan reproduksi dasar bernilai lebih dari satu. Berdasarkan hasil simulasi numerik didapat bahwa ilustrasi kestabilan lokal titik setimbang sesuai dengan hasil analisis yaitu konvergen ke titik setimbangnya. Selain itu, dari hasil numerik juga menunjukkan keefektivitasan faktor edukasi pada model yaitu semakin tinggi tingkat edukasi, maka akan menurunkan populasi yang terpapar dan populasi kecanduan bermain game online.

Comparison of Value at Risk (VaR) in Risk Analysis: Historical, Variance Covariance and Monte Carlo Methods Fauziyah, Meirinda; Dani, Andrea Tri Rian; Koirudin, Hadi; Budi, Ennesya Estya; Avrilia, Khairunnisa; Watika, Noor Hikmah
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 3 (2024): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v2i3.3778

Value at Risk (VaR) is a method used to measure financial risk in a company. VaR calculations are often used to calculate the level of loss from shares in a company, such as bank shares. The aim of this research is to determine the level of losses in Bank Central Asia shares using the historical method, the Variance-covariance method, and the Monte Carlo method. the results showed that with an initial investment of $50 and using the Historical method at a significant level of 95%, the VaR value was obtained at $16.42 or IDR. 267.301 and at the 90% significant level, the VaR value was obtained at $12.41 or IDR. 202.022. Based on the Variance-covariance method with an initial investment of 50$ at the 95% significant level, the VaR value is obtained at $16.42 or IDR. 267,301 and at the 90% significant level, the VaR value is obtained at $12.79 or IDR. 208.208. Meanwhile, based on the Monte Carlo method with an initial investment of $50, at a significant level of 95%, the VaR value is obtained at $16.46 or IDR. 267,952 and at the 90% significance level, the VaR value is obtained at $12.84 or IDR. 209.022. Based on the three methods used, it was concluded that the Monte Carlo method gave greater results compared to the other two methods.

Analysis the Effect of Inflation, Gold Prices in Dollars, Rupiah Exchange to Bank Indonesia Monthly Rates After the COVID 19 Seputro, Dimas Nugroho Dwi; Dani, Andrea Tri Rian; Fauziyah, Meirinda; Adrianingsih, Narita Yuri; Putra, Fachrian Bimantoro
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 3 (2024): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v2i3.3767

The Covid-19 pandemic has caused economic turmoil to become uncertain, affecting all aspects of Indonesian society's lives. This research aims to determine the relationship between the inflation rate, the transaction price of the last issuer of gold and the rupiah exchange rate that occurred in the period after the Covid-19 pandemic on the monthly interest rate of Bank Indonesia, both together and each variable on the monthly interest rate of Bank Indonesia. This research details the research steps starting from classical assumption test analysis, multiple linear regression, coefficient of determination to hypothesis testing. The research results show that from the inflation rate, the price of gold in dollars together has a significant influence on the dependent variable, namely the Bank Indonesia monthly interest rate. Inflation and gold prices in dollars partially have a significant influence on Bank Indonesia's monthly interest rate, while the rupiah exchange rate variable partially does not have a significant influence on Bank Indonesia's monthly interest rate. Inflation is the most dominant variable in Bank Indonesia's monthly interest rate after the Covid-19 pandemic.

Klasterisasi Prevalensi Stunting Menggunakan K-Prototype pada Data Campuran Marsandy, Aldwin Falah Hasan; Hayati, Memi Nor; Fauziyah, Meirinda
METIK JURNAL (AKREDITASI SINTA 3) Vol. 8 No. 2 (2024): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v8i2.824

Cluster analysis is a statistical method for grouping objects based on the similar characteristics of each object. One of the algorithms used in cluster analysis is K-Prototype, which was developed to handle mixed data, namely numerical and categorical data. The validation method used to determine the optimal number of clusters in K-Prototype cluster analysis is the Elbow method. The aim of the research is to determine the optimal number of clusters and optimal cluster results on the prevalence of stunting and indicators that influence the prevalence of stunting in Indonesia in 2022. The results of the research show that the optimal number of clusters produced is 4 clusters, using the Elbow graph the WCSS (Within Cluster Sum Square) value is obtained. optimal is 65.83. Cluster 1 consists of 2 provinces, cluster 2 consists of 7 provinces, cluster 3 consists of 10 provinces, and cluster 4 consists of 15 provinces.

Pemodelan GWR Menggunakan Fungsi Pembobot Adaptive Box-Car Pada Angka Kesakitan DBD di Pulau Kalimantan Tahun 2023 Candra Dewi, Ni Luh Ayu; Hayati, Memi Nor; Fauziyah, Meirinda
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 01 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm355

Demam Berdarah Dengue (DBD) merupakan penyakit yang disebabkan oleh penyebaran virus dengue yang berkaitan dengan karakteristik suatu wilayah yang berbeda-beda. GWR merupakan pemodelan yang mempertimbangkan adanya aspek lokasi yang berbeda-beda sehingga akan menghasilkan penduga parameter yang bersifat lokal di setiap lokasi pengamatan. Penelitian ini bertujuan untuk mendapatkan model GWR dan faktor-faktor yang berpengaruh signifikan terhadap angka kesakitan DBD di kabupaten/kota di Pulau Kalimantan Tahun 2023. Penaksiran parameter model GWR menggunakan metode Weighted Least Square (WLS) dengan fungsi kernel adaptive box-car sebagai pembobot spasial dan nilai bandwidth optimum ditentukan menggunakan kriteria Cross-Validation (CV). Hasil penelitian mendapatkan nilai koefisien determinasi model GWR sebesar 51,04%, yang nilai koefisien determinasinya lebih besar dibandingkan regresi linier berganda. Hasil estimasi parameter model GWR didapatkan model yang nilai koefisien determinasinya berbeda-beda di setiap lokasi pengamatan. Faktor-faktor yang berpengaruh signifikan adalah ketinggian di atas permukaan laut, ketidaktersediaan fasilitas buang air besar, dan jarak ke Ibu Kota Provinsi

MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS Sifriyani, Sifriyani; Dani, Andrea Tri Rian; Fauziyah, Meirinda; Mar’ah, Zakiyah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2023-2032

Research on innovations in the statistics and statistical computing program systems implemented in the health sector. The development of a mixed estimator model is an innovation of nonparametric regression analysis by combining two approaches in nonparametric regression, namely the truncated spline estimator and the Epanechnikov kernel. The urgency of this study is that there are often cases where there are different data patterns from each predictor variable. In addition, by using only one form of the estimator in estimating a multivariable regression curve, the result is that the estimator obtained will not match the data pattern. The research objective was to find a mixed estimator between the truncated spline and the Epanechnikov kernel and the estimator results were applied to Dengue Hemorrhagic Fever case data. The unit of observation is a province in Indonesia and This study relied on secondary data received from the Central Statistical Agency (BPS) and the Health Office. Based on the analysis results, it was found that the best model of nonparametric regression with a mixed estimator of the truncated spline and Epanechnikov Kernel is a model with 3 knots with a combination of variables. The coefficient of determination (R2) is 98.11%. We can conclude that the mixed estimator tends to follow actual data and represents a nonparametric regression model with a mixed estimator that can predict the number of Dengue Hemorrhagic Fever Cases in Indonesia

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