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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat BAREKENG: Jurnal Ilmu Matematika dan Terapan JURNAL SILOGISME : Kajian Ilmu Matematika dan Pembelajarannya Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Jurnal Matematika UNAND Jurnal Abdi Masyarakat Indonesia Journal of Mathematics: Theory and Applications Jurnal Pengabdian Papua Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat STATISTIKA Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) EBAMUKAI; JURNAL PENGABDIAN ILMU PENGETAHUAN DAN TEKNOLOGI
FEBY SERU
Prodi Matematika, Fakultas MIPA, Universitas Cenderawasih, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Journal : STATISTIKA

 1 
Analysis of Stunting Data in Indonesia Using K-Means and Self Organizing Map (SOM) Allo, Caecilia Bintang Girik; Nicea Roona Paranoan; Winda Ade Fitriya B; Bobi Frans Kuddi; Feby Seru
Statistika Vol. 25 No. 2 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i2.7778

Abstract

Abstract. Stunting is a global public health concern, including in Indonesia. The Indonesian government establishes a target for stunting prevalence reduction every year. The government is aiming for a stunting prevalence of 18% in 2025. The government certainly requires policy recommendations to achieve this target. Clustering analysis can be used to identify provinces with similar characteristics or those that still require special attention based on stunting related indicators. There are several clustering methods, including K-Means and Self-Organizing Map (SOM). This study aims to classify provinces in Indonesia based on indicators related to stunting and to compare the performance of two clustering methods. Based on the obtained data, it was found that the data contains outliers. The best clustering method can be determined using the Silhouette Coefficient (SC) and Davies Bouldin Index (DBI). The results showed that the highest SC value, 0.62, was obtained using the SOM method and the lowest DBI, 0.75, was obtained also using SOM method. Two clusters were formed using the SOM method. Cluster 1 consisted of 36 provinces in Indonesia. Cluster 2 consisted of 2 provinces, namely Highland Papua and Central Papua.
Comparison of the Claim Ratio Method and the Bornhuetter-Ferguson Chain Ladder Method in Claim Reserve Calculation Paranoan, Nicea Roona; Seru, Feby; Gultom, Ayub Sahala
Statistika Vol. 25 No. 2 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i2.7934

Abstract

Abstract. Uncertainty in life brings risks that can threaten financial stability, making the existence of insurance crucial for managing such risks. One of the key elements in insurance is the management of claim reserves, which are funds allocated to meet outstanding claim obligations. This study aims to analyze and compare two claim reserve estimation methods, namely the Claim Ratio Method and the Bornhuetter-Ferguson Method, to assess the accuracy of each. The analysis is conducted by calculating claim reserve estimates using both methods based on historical claim data. The data used in this study are simulated data obtained through random sampling using Microsoft Excel. The results show that the Claim Ratio Method produced an estimate of 204,691,130, while the Bornhuetter-Ferguson Method yielded an estimate of 211,097,953. Compared to the Claim Ratio Method, the Bornhuetter-Ferguson Method provides results that are closer to reality, as it takes into account the claim development pattern in more detail, particularly for data with high variability. The study concludes that the choice of estimation method has significant implications for the financial stability of insurance companies. More accurate reserve calculations not only strengthen the solvency and operational efficiency of insurers but also reinforce policyholder trust and confidence in insurance protection. Consequently, the adoption of more robust methods such as the Bornhuetter-Ferguson is recommended, while future research is encouraged to explore alternative or hybrid models that may further improve estimation accuracy in diverse contexts.
Co-Authors Agung Dwi Saputro Allo, Caecilia Bintang Girik Angelika, Venthy Asghar Nazal, Muhammad Ayub Sahala Gultom Azizah Azizah Bobi Frans Kuddi Caecilia Bintang Girik Allo Christian Dwi Suhendra Christian Dwi Suhendra, Christian Dwi Deppa Ringgi’ F. B., Winda Ade Frans Augusthinus Asmuruf Gautam Makwana H Elizabeth Herlina Datu Wetipo Joko Harianto Langowuyo, Agustinus Lolita Tuhumen Miftachul Jannah Modokh, Meidianti A. Muhammad Hisyam Nada Pertiwi Papriani Nazal, Muhammad Asghar Nicea Roona Paranoan Pawan, Elvis Radian Januari Situmeang Rahmadhan, Richardo Valentino Santinia Andiva Pramesti Saputra, Agung Dwi Saputro, Agung Dwi Saputro, Agung Dwi Sari, Nur Nilam Sitti Rosnafi’an Sumardi Suarni. S Tiku Tandiangnga Venthy Angelika Winda Ade Fitriya B Yosina Arni Sihombing