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Pengaruh Kepatuhan Wajib Pajak dan Sanksi Pajak Terhadap Penerimaan Pajak Bumi dan Bangunan di Kota Tangerang Selatan Tahun 2019-2023 Putri, Anthiana Meilia; Ngatimin, Ngatimin
Jurnal Portofolio : Jurnal Manajemen dan Bisnis Vol. 4 No. 2 (2025): Integrasi Teknologi Informasi dan Manajemen Operasional Kerja Lembaga
Publisher : Prisani Cendekia

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Abstract

This study aims to analyze the effect of taxpayer compliance and tax sanctions on Land and Building Tax (PBB) revenue in South Tangerang City during the 2019–2023 period. The independent variables in this study are taxpayer compliance and tax sanctions, while the dependent variable is Land and Building Tax revenue. The research employed a quantitative method with panel data regression analysis. The sample was determined using purposive sampling, consisting of 5 districts that met the criteria over 5 years, resulting in 25 observations. The data used are secondary data obtained from the Regional Revenue Agency of South Tangerang City. The findings reveal that taxpayer compliance does not have a significant effect on Land and Building Tax revenue. On the other hand, tax sanctions have a significant effect on Land and Building Tax revenue. Simultaneously, taxpayer compliance and tax sanctions significantly influence Land and Building Tax revenue in South Tangerang City. This study highlights that tax sanctions play an important role in enhancing actual taxpayer compliance, thereby contributing to the increase in Land and Building Tax revenue.
CARBON EMISSION DISCLOSURE STUDY: STUDY OF OWNERSHIP CONCENTRATION FACTORS WITH THE MEDIATING EFFECT OF CSR DEPARTMENT AND COMPANY AGE Ngatimin, Ngatimin
Jurnal Akuntansi Dan Bisnis Indonesia (JABISI) Vol. 5 No. 1 (2024): Jurnal Akuntansi Dan Bisnis Indonesia (JABISI)
Publisher : Program Studi Akuntansi Institut Bisnis dan Informatika (IBI) Kosgoro 1957

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55122/jabisi.v5i1.1275

Abstract

This study aims to investigate the factors that influence carbon emissions disclosure in mining companies in Indonesia by considering the role of ownership concentration, the existence of a CSR Department, and company age as mediators. Data was collected from audited financial reports of mining companies listed on the Indonesia Stock Exchange during 2017-2021. The analysis method used is Path Regression with the AMOS 23.00 software tool. The research results show that ownership concentration does not significantly affect the disclosure of carbon emissions. This finding is based on agency theory, highlighting interest differences between managers and shareholders. The existence of a CSR Department has a positive and significant influence on carbon emissions disclosure. However, the CSR Department cannot mediate the relationship between ownership concentration and carbon emissions disclosure. Furthermore, company age plays a vital role as a mediator in the relationship between ownership concentration and carbon emissions disclosure, showing that the older the company, the higher the level of carbon emissions disclosure carried out, reflecting experience, deep understanding of stakeholder needs, and commitment company towards sustainable practices.
Optimization-Based Geospatial Clustering Using Fuzzy Geographically Weighted Clustering and Flower Pollination Algorithm for Stunting Risk Mapping Ngatimin, Ngatimin; Istiawan, Deden; Ustyannie, Windyaning; Riansyah, Rahmat; Sholicah, Ameliatus
ILKOM Jurnal Ilmiah Vol 18, No 1 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i1.3130.151-164

Abstract

Stunting remains a major public health challenge in Indonesia, characterized by significant regional disparities and complex multidimensional determinants. Effective intervention strategies therefore require analytical approaches that are capable of capturing spatial heterogeneity and identifying region-specific vulnerability patterns. This study applies Fuzzy Geographically Weighted Clustering (FGWC) optimized using the Flower Pollination Algorithm (FPA) to map district-level stunting vulnerability and identify priority intervention areas. The analysis covers 514 districts using 21 multidimensional indicators representing health, nutrition, housing conditions, food security, social protection, and demographic characteristics derived from the Central Statistics Agency. The integration of FGWC with FPA enhances clustering performance by incorporating spatial dependence and metaheuristic optimization, enabling the algorithm to produce more stable and geographically sensitive clusters. Cluster validity indices confirm that a four-cluster solution provides the most optimal segmentation of stunting vulnerability. The results reveal distinct regional structures, socioeconomic-driven vulnerability associated with limited asset ownership, high dependence on social assistance and large household size, multidimensional deprivation concentrated primarily in eastern Indonesia, and nutrition-related vulnerability linked to breastfeeding duration and food security. These findings demonstrate that stunting patterns in Indonesia are spatially heterogeneous and influenced by diverse structural factors. The proposed FGWC–FPA framework offers a robust geospatial optimization approach that can support more precise, evidence-based, and region-specific strategies for accelerating stunting reduction.