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Modeling of Gross Domestic Product Growth in Indonesia by Using Multi-Input Intervention Model Chandrawati, Chandrawati; Kertanah, Kertanah; Ramli, Tri Juliantin; Chintyana, Alissa; Hirzi, Ristu Haiban
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.27949

Abstract

The Gross Domestic Product (GDP) Growth of Indonesia has fluctuated over time due to established policies, economic crises, changes in political direction, and natural disasters. In 1998, due to the fall of the New Order regime, the Indonesian economy contracted by -13.13 percent, leading to hyperinflation. In 2020 the COVID-19 pandemic occurred which caused Indonesia's GDP Growth to contract again. Accurate forecasting of GDP Growth is crucial for government to formulate effective future policy strategies to maintain the stability of Indonesia's economy. There are several outliers in Indonesia's GDP Growth data, so the proper analysis is a multi-input intervention. The best model analysis is ARIMA (1,0,0) with non-zero mean using the first order intervention b=0, r=0, s=0 and the second order intervention b=0, r=0, and s=0 which resulted in a Mean Absolute Percentage Error (MAPE) of 23.47 percent. The outlier effect on Indonesia's GDP Growth data is both direct and temporary.
Pemetaan Kasus DBD di Pulau Lombok menggunakan Regresi Binomial Negatif berbasis Geografis Ayundasari, Dita Septiana; Hastuti, Siti Hariati; Kertanah, Kertanah
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 2 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i2.27460

Abstract

According to the Indonesia Health Profile Report 2022, NTB Province is among the 11 provinces with the highest incidence rate of dengue hemorrhagic fever (DHF). On Lombok Island, there were 2,074 cases with 4 deaths in 2022. DHF remains a serious threat in Lombok, so this study aims to map sub-districts based on significant factors for the spread of DHF in 54 sub-districts throughout Lombok Island. This study used quantitative analysis with one response variable, the number of DHF cases, and three predictor variables: the ratio of medical personnel (nurses) (X1), the percentage of proper sanitation facilities (healthy latrines) (X2) and the percentage of standard drinking water facilities (X3) in 54 sub-districts. Data were obtained from the Health Office throughout Lombok Island. Analysis techniques include descriptive analysis, GWNBR modeling, and significant variable mapping. The mapping results showed six groups of sub-districts with a combination of significant variables, which included variables X1, X2, and X3. The findings suggest the need for additional studies or prevention policies that are more focused on hygiene to reduce the risk of DHF spread. Related parties also need to be informed to take strategic steps based on these findings.
Penerapan Algoritma Self Organizing Maps (SOM) Dan K-Means Untuk Mengelompokkan Akseptor KB Di NTB Yahya, Lalu Muhammad; Kertanah, Kertanah; Hidayaturrohman, Umam
Jurnal Statistika dan Komputasi Vol. 3 No. 1 (2024): Jurnal Statistika dan Komputasi
Publisher : Universitas Nahdlatul Ulama Sunan Giri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/statkom.v3i1.2960

Abstract

Latar Belakang: Salah satu permasalahan utama terkait penggunaan KB yaitu berhubungan dengan ketersediaan layanan kesehatan, sehingga untuk memberikan akses yang lebih baik kepada masyarakat terhadap informasi dan layanan dapat dilakuakn analsis clustering yang membantu mengidentifikasi wilayah-wilayah di NTB yang memiliki akses terbatas terhadap layanan kesehatan reproduksi. Tujuan: Tujuan penelitian ini, pertama adalah untuk mengetahui gambaran umum akseptor keluarga berencana seluruh kecamatan di NTB. Kedua adalah untuk mengetahui hasil cluster akseptor keluarga berencana di kecamatan seluruh NTB 2022 dengan algoritma SOM dan K-means serta mengetahui algoritma terbaik pada data akseptor keluarga berencana di kecamatan seluruh NTB ditinjau dari nilai validasi internal. Metode: Algoritma clustering yang digunakan pada penelitian ini yaitu SOM dan K-means. Hasil: Berdasarkan hasil analisis didapatkan bahwa suntik merupakan akseptor tertinggi di NTB sebanyak 299.344. Sedangkan akseptor terendah adalah kondom sebanyak 7.333. Hasil penelitian dengan algoritma SOM memiliki 2 cluster yaitu cluster 1 terdapat 103 kecamatan dan cluster 2 terdapat 14 kecamatan. Algoritma K-means memiliki 2 cluster yaitu cluster 1 terdapat 84 kecamatan dan cluster 2 terdapat 33 kecamatan. Kesimpulan: Algoritma terbaik untuk pengelompokan akseptor keluarga berencana di kecamatan seluruh Provinsi NTB adalah algoritma SOM.