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All Journal Academia Open PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Hariyanti, Fitri
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Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Physics Social Sciences Other

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Reducing Pending BPJS Claims Through Risk Management Hariyanti, Fitri; Cholifah, Cholifah
Academia Open Vol 9 No 1 (2024): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.9.2024.6771

Abstract

Pending BPJS claims delay hospital payments, with the guarantee unit playing a crucial role. This study analyzes risk management in the guarantee unit regarding pending inpatient claims using a qualitative approach and the FMEA method. Data from interviews, questionnaires, and BPJS claim confirmation sheets revealed four potential risks causing pending claims, with readmission potential as the highest priority (RPN score of 75). The proposed improvements include coordinating, socializing, and educating related units on the readmission concept. Implementing these strategies can reduce pending claims, ensuring timely BPJS payments to hospitals. Highlight: Identified four risks causing pending claims. Readmission risk prioritized (RPN score 75). Education and coordination proposed to reduce claims. Keyword: BPJS claims, risk management, guarantee unit, FMEA, readmission
A Multi-Temporal Remote Sensing Approach to Quantify Land Cover Change and its Impact on Ecosystem Sustainability in Riau, Indonesia Purba, Novrian Maria; Hariyanti, Fitri; Saputra, Andriansyah Muqiit Wardoyo
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.691

Abstract

This study analyzes land cover change in Riau Province from 2015 to 2024, focusingon deforestation and degradation as indicators of ecosystem sustainability. Landsat 8 OLI/TIRSand Landsat 9 OLI-2 imagery processed in Google Earth Engine (GEE), combined with MODIShotspot data (MOD14A1) and socioeconomic indicators—Gross Regional Domestic Product(GRDP) and Open Unemployment Rate (OUR) from Statistics Indonesia (BPS)—were used toassess spatiotemporal patterns. The Normalized Difference Vegetation Index (NDVI) wasapplied with thresholds for deforestation (NDVI < –0.3) and degradation (–0.3 ? NDVI ? –0.1).Results show that 2015 was the most severe period, dominated by peatland fires, while 2019recorded forest loss at a lower intensity and 2020–2024 indicated partial vegetation recoverylinked to restoration efforts. Pelalawan, Indragiri Hilir, and Kampar were the most affecteddistricts. Correlation analysis revealed that fire hotspots had the strongest association with landcover change, while economic and social indicators showed weaker relationships. Peatland firesremain the main driver of land degradation, emphasizing the need to strengthen fire management,peatland protection, and sustainable plantation governance to support Sustainable DevelopmentGoal (SDG) 15 on Life on Land, particularly the target of Land Degradation Neutrality (15.3.1)by 2030.
Determination of Inflation Sistercity in Riau Province by Using K-Means Clustering Method Kesuma, M Nata; Yufa, Pedro Rahmat; Hariyanti, Fitri
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.711

Abstract

At the present time, the government is placing a significant emphasis on the regulation of inflationary pressures. The government's approach is multifaceted, ranging from the Minister of Home Affairs' direct leadership of coordination meetings on Monday mornings to providing fiscal incentives for regions that can control inflation and removing local government officials who cannot. However, note that BPS-Statistics Indonesia (BPS) does not calculate inflation in all Indonesian regencies and cities. The calculation of inflation only includes four out of the 12 regencies/cities in Riau Province. Therefore, we must establish an inflation sister city to allow regencies/cities not included in BPS's calculations to independently calculate the inflation rate. This study is pioneering in its analysis of Sister City Inflation in Riau Province. The k-means cluster analysis indicates that the city of Pekanbaru and the city of Tembilahan form distinct clusters, with no regencies or cities within their respective clusters that are associated with either of the two cities. Subsequently, the Dumai cluster forms a cluster with Bengkalis, Siak, and Pelalawan. Conversely, Kampar Regency formed a cluster with Kuantan Singingi, Indragiri Hilir, Indragiri Hulu, Rokan Hulu, Rokan Hilir, and the Meranti Islands. Consequently, regions that are not included in the inflation calculation may utilize the data from the cost of living survey in inflation regencies/cities within the same cluster to perform their calculations. Furthermore, if the local government requires the inflation rate as a reference for determining the regional minimum wage, it may employ it from the sister cities that have been established.
Co-Authors Cholifah, Cholifah Kesuma, M Nata Purba, Novrian Maria Saputra, Andriansyah Muqiit Wardoyo Yufa, Pedro Rahmat