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Safitri, Mella
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Profile Matching in Python to Identify Tourist Destinations for The Development of National Tourism Utami, Meinarini Catur; Aini, Qurrotul; Fetrina, Elvi; Tsauri, Muhammad Shofian; Safitri, Mella
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46683

Abstract

Tourism has emerged as a key contributor to state revenue and has played a crucial role in national economic recovery following the Covid-19 pandemic, establishing itself as a new engine for the country’s economic growth. In response to this, the government—through the Ministry of Tourism and Creative Economy—is actively promoting development in the tourism sector to enhance numerous tourist attractions in Indonesia, which are renowned for their beauty and recognized globally. However, the Ministry faces several challenges, including the need for technological advancements and the expansion of infrastructure. Addressing these needs will require substantial financial investment to optimize all tourism sites. This study aims to identify 22 tourist attractions across Indonesia using the Profile Matching method in Python programming, based on seven established criteria. The uniqueness about this study is that this research implemented  a simple Python script and the tourist attractions are spread across all regions of Indonesia. The results of the study highlight three tourist destinations that warrant government attention for optimization: Lake Maninjau, Rantepao, and Seminyak. To facilitate improvement, several areas require focus, including upgrading access roads, enhancing basic facilities, fostering community participation, developing human resources, and leveraging technology. The analysis using Python demonstrates that the software performs efficiently, processing 22 data points with seven criteria in a mere 0.06 seconds.
PENGARUH CAPITAL INTENSITY RATIO, RECEIVABLE TURNOVER RATIO DAN EFFECTIVE TAX RATE TERHADAP STOCK RETURN PADA PT WASKITA KARYA (PERSERO) TBK PERIODE 2015–2024 Safitri, Mella; Jamaludin, Jamaludin
Journal Economics Technology And Entrepreneur Vol 5 No 01 (2026): ECOTECHNOPRENEUR : JOURNAL ECONOMICS, TECHNOLOGY AND ENTREPRENEUR
Publisher : Pusat Studi Ekonomi, Publikasi Ilmiah dan Pengembangan SDM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/ecotechnopreneur.v5i01.2240

Abstract

This study aims to analyze the effect of Capital Intensity Ratio, Receivable Turnover Ratio, and Effective Tax Rate on the stock return of PT Waskita Karya (Persero) Tbk during the 2015–2024 period. The research adopts a quantitative approach with various analytical methods, including descriptive statistics, classical assumption tests, multiple linear regression, hypothesis testing, and coefficient of determination analysis to measure the model’s ability to explain the dependent variable. The results show that the Capital Intensity Ratio has a negative and significant effect on stock return (t = -4.817; sig. 0.003 < 0.05). In addition, the Receivable Turnover Ratio also has a negative and significant effect on stock return (t = -4.591; sig. 0.004 < 0.05). On the other hand, the Effective Tax Rate has a negative but insignificant effect on stock return (t = -2.066; sig. 0.084 > 0.05). Simultaneously, all independent variables have a significant effect on stock return (F = 10.201; sig. 0.009 < 0.05). The coefficient of determination of 83.6% indicates strong explanatory power, while the remaining 16.4% is influenced by other factors outside this study.
Co-Authors Elvi Fetrina Jamaludin . Meinarini Catur Utami Tsauri, Muhammad Shofian