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All Journal Jurnal Pamator : Jurnal Ilmiah Universitas Trunojoyo Madura Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Bisnis dan Pembangunan
Ahmadi Marta
Politeknik Hasnur
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Social Sciences

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Peran Digital Marketing, Word Of Mouth dan Brand Awareness dalam Mempengaruhi Keputusan Siswa Bersekolah Di GIBS Ahmadi Marta; Hairudinor; Marhusin
JURNAL BISNIS DAN PEMBANGUNAN Vol. 14 No. 1 (2025): Jurnal Bisnis dan Pembangunan
Publisher : Program Magister Ilmu Administrasi Bisnis FISIP Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jbp.1414i1.66

Abstract

Abstract: This research tries to analyze the role of Digital Marketing, Word of Mouth and Brand Awareness on students' decisions in choosing a school. The samples taken were 113 students at SMA Global Islamic Boarding School (GIBS) classes X and X1. By using a quantitative approach with Structural Equation Modeling (SEM) analysis, the data is then processed using the Smart PLS version 3 application. The research results state that Brand Awareness has a significant effect on choosing decisions. Digital Marketing has no significant effect on Brand Awareness. Digital Marketing has no significant effect on the decision to choose a school. Digital Marketing has a significant influence on WOM. WOM has a significant effect on Brand Awareness. WOM has a significant influence on choosing decisions. Digital Marketing has a significant indirect influence  on the decision to choose a school mediated by WOM. Then Finally, Digital Marketing has a significant indirect influence on the Brand Awareness mediated by WOM
Leverage, Scale, and Firm Age as Determinants of Corporate Financial Distress: A Cox Proportional Hazard Analysis of Cyclical Sector Firms on the Indonesia Stock Exchange Ahmadi Marta; Amiratu Zakiah
Jurnal Pamator : Jurnal Ilmiah Universitas Trunojoyo Vol 19, No 1: January - April 2026
Publisher : Universitas Trunodjoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/pamator.v19i1.33713

Abstract

Financial distress prediction in emerging markets demands methodologies that address both the probability and the timing of corporate financial failure. This study applies the Cox Proportional Hazard (Cox PH) model to examine survival time until financial distress among 166 companies listed on the Indonesia Stock Exchange (BEI) across three cyclical sectors (Basic Materials, Non-Primary Consumer Goods, and Energy) over the 2016–2024 observation period. Financial distress is operationalised using a multidimensional definition requiring at least two of three conditions simultaneously: Interest Coverage Ratio below unity, negative Operating Cash Flow, and negative Retained Earnings. Kaplan-Meier estimates indicate a cumulative distress incidence of 54.2%, with overall survival declining to S(t=9) = 0.46 (95% CI: 0.39–0.54). The log-rank test finds no significant difference across sectors (chi-square = 1.76, p = 0.416). The Cox PH model achieves strong fit (LR chi-square = 89.18, p less than 0.001) and excellent discriminatory ability (C-index = 0.807). Three covariates are statistically significant: Debt-to-Asset Ratio (HR = 2.05, p less than 0.001), Firm Size (HR = 0.64, p less than 0.001), and Firm Age (HR = 0.94, p less than 0.001). All proportional hazard assumptions are confirmed through Grambsch-Therneau diagnostics. Findings are consistent with Trade-off Theory, Agency Theory, the too-big-to-fail hypothesis, and the Liability of Newness framework, and are robust across parametric alternatives. Time-invariant covariates at a single lag constitute the principal limitation. These results offer empirical grounding for leverage-based financial distress early warning in the Indonesian market context, though sector-level heterogeneity in the leverage–distress mechanism warrants consideration in practice.
K-Means and Decision Tree Models for Analysis Students Perception of Digital Marketing Tesdiq Prigel Kaloka; Ahmadi Marta; Mariyam Mariyam; Nadila Deryza Syofrin
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 2 (2026): MALCOM April 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i2.2360

Abstract

Amid intensifying competition among educational institutions and the rapid expansion of digital platforms, schools must adopt effective digital marketing strategies to attract prospective students. This research examines students’ perceptions of the implementation of digital marketing at the Global Islamic Boarding School (GIBS) in Barito Kuala Regency, South Kalimantan, Indonesia. Data were collected from 95 students using a structured questionnaire comprising 20 variables related to digital marketing and word-of-mouth communication. A hybrid analytical framework integrating K-Means Clustering and Decision Tree analysis was employed to identify perception-based segments and determine key differentiating indicators. The Elbow method indicated an optimal three-cluster solution, resulting in highly positive, negative, and moderate perception groups. Decision Tree results revealed that engaging content (B7), social media stability (B12), and invitation to attend school (C19) were the most influential variables distinguishing clusters, with satisfactory classification performance supporting the robustness of the segmentation. The findings suggest that emotionally engaging and experientially rich content plays a more decisive role in shaping student perceptions than purely technical aspects of digital media management. Accordingly, schools should optimize their digital marketing strategies by emphasizing authentic student experiences, maintaining consistent, stable online communication, and incorporating persuasive calls to action to enhance prospective students’ interest.
Co-Authors Amiratu Zakiah Hairudinor Marhusin , Mariyam Mariyam Nadila Deryza Syofrin Tesdiq Prigel Kaloka