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All Journal Riset Akuntansi dan Keuangan Indonesia Journal of Mathematics, Computation and Statistics (JMATHCOS)
Millati, Nabila Fida
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Economics, Econometrics & Finance Mathematics

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Between Strategy and Governance: Which Matters More in Driving Tax Disclosure? Ulynnuha, Ovi Itsnaini; Millati, Nabila Fida; Mujiyati; Aris, Muhammad Abdul; A'zizah, Laila Oshiana Fitria
Riset Akuntansi dan Keuangan Indonesia Vol. 10 No. 2 (2025): Riset Akuntansi dan Keuangan Indonesia
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/reaksi.v10i2.13146

Abstract

This study aims to examine the effect of tax planning, board of commissioners size, and independent commissioners on tax disclosure among manufacturing firms in Indonesia. The research employed a quantitative approach using panel data regression with 38 firm-year observations from 19 listed companies that recently listed their IPOs since the period 2022–2023. The analysis was conducted by estimating the Common Effect, Fixed Effect, and Random Effect models, followed by specification tests such as Chow and Hausman. The Random Effect Model was identified as the most appropriate model. The empirical results indicate that tax planning has a positive effect on tax disclosure at the 10% significance level, while the size of the board of commissioners has a positive and significant impact at the 5% level. In contrast, the presence of independent commissioners does not show a significant influence. These findings highlight the importance of board size and tax strategies in improving corporate transparency, while also suggesting that the effectiveness of independent commissioners requires further attention in the Indonesian context.  
Clustering of Central Java Districts Based on Educational Indicators: A Comparison of K-Means and Hierarchical Methods Syafiq, Muhammad; Millati, Nabila Fida; Idris, Muh Akbar; Fitrianto, Anwar; Alifviansyah, Kevin; Erfiani, Erfiani
Journal of Mathematics, Computations and Statistics Vol. 9 No. 1 (2026): Volume 09 Issue 01 (March 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/xen35m31

Abstract

This study aims to cluster districts and municipalities in Central Java based on educational indicators and to compare the clustering performance of K-Means and Hierarchical methods. The analysis uses secondary data from the Statistical Publication of Education in Central Java Province 2024, covering eight indicators related to educational facilities, participation, and attainment. The data were standardized, explored using descriptive statistics, and analyzed using K-Means and Hierarchical clustering methods. The evaluation results show that both methods produced broadly comparable clustering structures. However, Hierarchical Clustering demonstrated slightly stronger performance in terms of cluster separation and compactness, with a higher Silhouette Index (0,591) and Dunn Index (0,320) and a lower Davies–Bouldin Index (0,501) compared with K-Means (SI 0,584, Dunn 0,225, DBI 0,562). Meanwhile, K-Means produced a more balanced partition and a higher Calinski–Harabasz Index (48,63) than Hierarchical Clustering (44,30). The clustering results reveal a clear pattern of educational disparities across the region. A small group consisting of Sukoharjo Regency and the cities of Semarang, Surakarta, Salatiga, and Magelang forms a higher-performing cluster characterized by stronger educational indicators, while most rural districts belong to a lower-performing group. These findings indicate that educational disparities in Central Java remain spatially concentrated and highlight the need for targeted policies to strengthen educational investment and improve progression to higher levels of education in less developed districts.
Co-Authors Alifviansyah, Kevin Erfiani Erfiani Fitrianto, Anwar Idris, Muh Akbar Laila Oshiana Fitria A’zizah Muhammad Abdul Aris MUHAMMAD SYAFIQ Mujiyati Ovi Itsnaini Ulynnuha