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All Journal Indonesian Journal of Energy East Java Economic Journal Prosiding Seminar Nasional Official Statistics
Nurkarim, Wahidya
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Humanities Computer Science & IT Economics, Econometrics & Finance Energy Social Sciences

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Development of Green Economy Index (GEI) with Remote Sensing to Support Sustainable Economy in East Java Nurkarim, Wahidya
East Java Economic Journal Vol. 8 No. 2 (2024)
Publisher : Kantor Perwakilan Bank Indonesia Provinsi Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53572/ejavec.v8i2.124

Abstract

The green economy concept is now widely used by many countries as a development concept that supports economic growth by ensuring that natural aspects are maintained. The green economy index (GEI) was formed to provide an evaluation of the achievements of the transformation of a greener economic development. The availability of Remote Sensing data has the potential to complement data that is not available at the regional level. This study builds the GEI Index in the province of East Java using indicators that have been studied literacy. The results obtained are that the green economy index in East Java has increased over the last five years. The city of Surabaya is the center of economic development which can be seen from many indicators. This indicates that spatial effects affect sustainable development that is environmentally friendly in East Java. Regional grouping analysis gives the result that there are groups that really need special attention because of the low scores on almost all indicators. Not only the regency government but also the policy from the East Java provincial government is needed to participate in developing this green economy practice.
Analisis Spasial Determinan Kasus Demam Berdarah Dengue (DBD) di Kota Bandung: Studi Komparatif Model SAR, SEM, dan SARMA Kamal, Shafnanda Aulia; Nurkarim, Wahidya
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2456

Abstract

Dengue Hemorrhagic Fever (DHF) is the third leading cause of death from infectious diseases in Indonesia. West Java Province, as the second most populous province in the country, and Bandung City, the most densely populated city in the province, have recorded the highest number of DHF cases from 2021 to 2024. This study aims to analyze the determinants of DHF and compare the performance of three spatial models—SAR, SEM, and SARMA—in explaining the distribution of DHF cases at the sub-district level in Bandung City. The data used include the number of DHF cases and socio-demographic variables such as the number of households in slum settlements, total population, and population density, analyzed spatially. The results show that the SEM model is the most optimal, with the lowest AIC value (320.881) and statistically significant spatial dependence in the residuals (p-value = 0.00352). Significant variables in the model include the number of households in slum areas, total population (log-transformed), and population density. These findings highlight the importance of spatial approaches in addressing DHF and support area-based health policies through coordinated cross-sub-district interventions.
Pengaruh Investasi Publik dalam Sektor Kesehatan, Pendidikan, dan Infrastruktur terhadap Pertumbuhan Ekonomi Indonesia : Analisis ARDL Tahun 2002-2023 Nurfadia, Atikah; Nurkarim, Wahidya
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2580

Abstract

Indonesia's Gross Domestic Product (GDP) has steadily increased in the past two decades to reach US$1.4 trillion. This growth is driven by various factors including domestic consumption, investment, and labor. This study aims to analyze the impact of government spending in the health, education, and gross fixed capital formation sectors on Indonesia's economic growth. Annual data from 2002 to 2023 were analyzed using the Autoregressive Distributed Lag (ARDL) approach to examine both short-term and long-term relationships among the variables. The results show that, in the long run, health expenditure and gross fixed capital formation have a positive and significant effect on gross domestic product (GDP) per capita. Conversely, education expenditure exhibits a negative and statistically insignificant effect. In the short run, only health expenditure has a significant influence on economic growth. Diagnostic tests indicate that the ARDL model used satisfies statistical assumptions and is structurally stable. These findings highlight the importance of optimizing education spending and maintaining as well as enhancing investments in the health and infrastructure sectors to support sustainable economic growth.
Monetizing Carbon Emissions: Advanced Strategies for Optimizing Carbon Economic Value Using Machine Learning and Geospatial Analysis Briantiko, Zenda O.; Nurkarim, Wahidya; Wahyuddin, Eko P.; Zulkarnain, Muhammad
Indonesian Journal of Energy Vol. 9 No. 1 (2026): Indonesian Journal of Energy
Publisher : Purnomo Yusgiantoro Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33116/ije.v9i1.296

Abstract

The transition to cleaner energy sources requires appropriate financial policies and regulations. One mechanism that supports this transition is carbon pricing, which encourages emissions reduction and creates economic opportunities through the carbon market. With its vast tropical forests, peatlands, and mangroves, Indonesia has significant potential for terrestrial carbon storage. However, using carbon revenue as a financial instrument to support the energy transition remains underexplored. Therefore, a quantitative analysis is needed to assess the potential carbon revenue under various pricing scenarios and its impact on clean energy investments and regional development. This study aims to (i) measure the potential economic value of carbon in East Java with greater precision and spatial detail using geospatial approaches and remote sensing technology, (ii) model predictions of carbon economic value for the forthcoming years by leveraging machine learning algorithms, aiming to obtain accurate, data-driven projections adaptable to land cover changes and policy shifts, and (iii) examine the relationship between carbon economic potential and social welfare such as poverty. The methods used in this research include remote sensing analysis to calculate Net Primary Productivity (NPP); machine learning techniques, such as LSTM and Neural Network, to forecast Carbon Economic Value (CEV) for future years; and clustering analysis to categorize regions based on socioeconomic conditions and CEV levels. From the results of this study, we found that the East Java government can utilize the economic value of carbon to reduce poverty from 9.79 percent to 5.75 percent. In addition, three regional clusters allow for the formulation more targeted policies for each regional group.
Co-Authors Briantiko, Zenda O. Kamal, Shafnanda Aulia Muhammad Zulkarnain Nurfadia, Atikah Wahyuddin, Eko P.