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All Journal Jurnal Teknologi Informasi MURA Jurnal E-Komtek Jurnal Teknologi Informasi Mura
Nurhaeka Tou
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Other

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Causal Modeling of Factors Causing Toddler Stunting Using the Peter-Clark Algorithm Nurhaeka Tou; Putri Mentari Endraswari; Syafiranur Iftizam
Jurnal E-Komtek Vol 9 No 2 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i2.2692

Abstract

Stunting is a growth disorder in toddlers that can result in a height that is not proportionate to their age. Between 2016 and 2024, many studies have discussed factors related to stunting. However, these studies generally only use correlation analysis, which indicates the level of closeness of the relationship between variables. Correlation analysis can indeed describe the existence of an association, but cannot explain the causal relationship. Therefore, the causal mechanisms underlying these factors have not been fully revealed. This study aims to model the causal relationship of the factors that cause stunting. This study uses the Peter-Clark algorithm to obtain the direction of the causal relationship. The results of this study show a relationship between Height(TB.U)/Weight(BB.U), Integrated Health Post Visits/Height(TB.U), Height(TB.U)/Mother's Education, Age of Marriage/Mother's Education, Immunization/Family Members Smoking in the Home, and Exclusive Breastfeeding/ Integrated Health Post Visits. The Peter-Clark algorithm in this study successfully identified a causal relationship based on a comparison of performance using directional and causal density of 67%. These results are quite informative, but 34% of the relationships remain undirected. Therefore, additional data, domain assumptions, or advanced algorithms, such as FCI or GES, are needed to determine their direction.
PENERAPAN METODE ARAS DALAM PEMILIHAN LOKASI REHABILITASI TAMBANG TIMAH DI KEPULAUAN BANGKA BELITUNG Nurhaeka Tou; Putri Mentari Endraswari; Iski Zaliman; A. Taqwa Martadinata; Marhasi Putri
Jurnal Teknologi Informasi Mura (JTI) Vol. 18 No. 2 (2026): Jurnal Teknologi Informasi Mura JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v18i1.3116

Abstract

Determining the priority for the rehabilitation of former tin-mining land is still done manually, so the assessment process is time-consuming and can introduce subjectivity into decision-making. Differences in land conditions based on several criteria make the process of determining rehabilitation priorities more complex, so a system capable of providing objective and structured recommendations is needed. This study aims to develop a Decision Support System (DSS) using the ARAS (Additive Ratio Assessment) method to determine rehabilitation priorities for former tin mining land. The ARAS method is used through the stages of determining criteria and weights, normalizing the decision matrix, calculating utility values, and ranking alternative land areas. The results show that the system is able to generate rehabilitation priority recommendations in accordance with the results of manual calculations, and helps the decision-making process become more effective and efficient. Testing using the Mean Absolute Percentage Error (MAPE) method yielded an error of 13.3%, which falls within the good category. These results indicate that the system has a fairly high level of accuracy in supporting the determination of rehabilitation priorities for former tin mining land.
PENERAPAN METODE ARAS DALAM PEMILIHAN LOKASI REHABILITASI TAMBANG TIMAH DI KEPULAUAN BANGKA BELITUNG Nurhaeka Tou; Putri Mentari Endraswari; Iski Zaliman; A. Taqwa Martadinata; Marhasi Putri
Jurnal Teknologi Informasi Mura (JTI) Vol. 18 No. 2 (2026): Jurnal Teknologi Informasi Mura JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v18i1.3116

Abstract

Determining the priority for the rehabilitation of former tin-mining land is still done manually, so the assessment process is time-consuming and can introduce subjectivity into decision-making. Differences in land conditions based on several criteria make the process of determining rehabilitation priorities more complex, so a system capable of providing objective and structured recommendations is needed. This study aims to develop a Decision Support System (DSS) using the ARAS (Additive Ratio Assessment) method to determine rehabilitation priorities for former tin mining land. The ARAS method is used through the stages of determining criteria and weights, normalizing the decision matrix, calculating utility values, and ranking alternative land areas. The results show that the system is able to generate rehabilitation priority recommendations in accordance with the results of manual calculations, and helps the decision-making process become more effective and efficient. Testing using the Mean Absolute Percentage Error (MAPE) method yielded an error of 13.3%, which falls within the good category. These results indicate that the system has a fairly high level of accuracy in supporting the determination of rehabilitation priorities for former tin mining land.
Co-Authors A. Taqwa Martadinata Iski Zaliman Marhasi Putri Putri Mentari Endraswari Putri Mentari Endraswari Syafiranur Iftizam