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All Journal Jurnal Nasional Holistic Science EduMatika: Jurnal MIPA EDUCTUM: Journal Research AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Economic: Journal Economic and Business
Triana, Dinie
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Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Physics Social Sciences Other

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Application of Lagrange Interpolation Method in Predicting the Number of HVS Orders in Printing Triana, Dinie; Putri, Amelia; Faradhilah, Anatasia; Sitorus, Yolanda Angelina
Holistic Science Vol. 4 No. 3 (2024): Jurnal Nasional Holistic Science
Publisher : Lembaga Riset Mutiara Akbar NOMOR AHU-0003295.AH.01.07 TAHUN 2021

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/hs.v4i3.791

Abstract

The research entitled “Application of the Lagrange Interpolation Method in Predicting the Number of HVS Orders in Printing” aims to develop an accurate forecasting model for the number of HVS orders in the printing industry. In this study, the Lagrange interpolation method was chosen because it can provide estimates by considering limited historical data. The analyzed data ranges from January 2021 to November 2022 and is processed to build a forecasting model. The results showed that the interpolation model built was able to capture well the fluctuation pattern of the order quantity. Model evaluation is carried out using Mean Absolute Percentage Error, which reads <=10%, indicating high prediction accuracy. In addition, sensitivity analysis to data variations showed consistent results of the prediction, thus strengthening the validity of the method. These findings suggest that Lagrange interpolation is an effective tool in forecasting HVS demand, providing advantages in inventory management and production planning in printing houses.
Protection and Education of Street Children in Islam: A Study of Their Life Experiences Triana, Dinie; Nurmayani, Nurmayani; Putri, Amelia; Daulay, Nurfitri Humayro; Hani, Aulia
EDUCTUM: Journal Research Vol. 4 No. 2 (2025): Eductum: Journal Research
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ejr.v4i2.962

Abstract

The phenomenon of street children is one of the complex social issues in Indonesia. Many factors contribute to children living on the streets, such as poverty, family instability, lack of access to education, and exploitation by certain parties. This study aims to analyze the protection and education of street children from an Islamic perspective, as well as the challenges they face in their daily lives. The research employs a qualitative method using interviews and observations of several street children. The findings indicate that these children encounter various obstacles, including social stigma, lack of family attention, and limited access to education and healthcare. From an Islamic perspective, children have the right to receive protection, affection, and proper education. Therefore, collaboration between families, communities, religious institutions, and the government is necessary to provide sustainable solutions for street children.
The Influence of Financial Ratios and Company Size on Bond Ratings of Banking Companies Listed on the Indonesia Stock Exchange in 2019-2024 Triana, Dinie; Putri, Amelia; Faradhilla, Anatasia; Putri, Alya Nabila
Economic: Journal Economic and Business Vol. 4 No. 2 (2025): ECONOMIC: Journal Economic and Business
Publisher : Lembaga Riset Mutiara Akbar (LARISMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ejeb.v4i2.961

Abstract

This study analyzes the influence of financial ratios and firm size on bond ratings of banking companies listed on the Indonesia Stock Exchange (IDX) for the 2019-2024 period. The independent variables include liquidity (Current Ratio), leverage (Debt to Equity Ratio), profitability (Return on Assets), and firm size (Size), with bond ratings as the dependent variable. A quantitative method with ordinal logistic regression is employed to examine the relationships among these variables. Secondary data were obtained from banking companies’ financial reports and bond ratings issued by PT Pefindo. The findings indicate that profitability (ROA) has a significant negative effect on bond ratings, suggesting that highly profitable companies do not necessarily receive better ratings. Meanwhile, leverage (DER), liquidity (CR), and firm size do not significantly impact bond ratings. The regression model is validated with a Nagelkerke R2 value of 0.784, indicating that the independent variables explain 78.4% of the variation in bond ratings. These results provide insights for investors and stakeholders that profitability plays a more critical role in determining bond ratings than other financial factors. Therefore, banking companies should optimize their profitability management to enhance bond credibility in financial markets.
Development of Deep Learning Model Based on Convolutional Neural Network (CNN) for Brain Tumor Classification Using MRI Images Sinaga, May Rani Tabitha; Tampubolon, Bungaria; Daulay, Nurfitri Humayro; Triana, Dinie; Hani, Aulia; Simanjuntak, Ferdyanto Abangan; Arnita, Arnita
EduMatika: Jurnal MIPA Vol. 5 No. 2 (2025): EduMatika: Jurnal MIPA
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/emju.v5i2.1105

Abstract

Brain tumor classification using MRI images presents a critical challenge in medical radiology. This study develops a deep learning model based on Convolutional Neural Network (CNN) to classify brain MRI images into four categories: Normal, Glioma, Meningioma, and Pituitary. A publicly available dataset from Kaggle consisting of 20,672 images was used, with preprocessing and data augmentation applied. The model architecture includes convolutional, pooling, flatten, dense, and dropout layers, optimized using the Adam optimizer and categorical crossentropy loss function. The evaluation results show that the model achieved an overall accuracy of 96% with high f1-scores across all classes, particularly for the Pituitary class (0.98). The main contribution of this study lies in the integration of diverse data augmentation techniques and Explainable AI (XAI) methods, enabling the visualization of key areas in MRI images that support classification decisions. The proposed model is not only accurate but also demonstrates strong generalization and interpretability, making it a promising tool for clinical decision support systems in brain tumor diagnosis.
Pengaruh Jenis Cairan Pelapis terhadap Tingkat Pencoklatan Buah Apel dengan Rancangan Acak Kelompok Lengkap Panjaitan, Hotnauli Roni Arta; Triana, Dinie; Hutapea, Risca Octaviyani; Pulungan, Zakiy Maulana; Ndruru, Albert Servant
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 12 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/aksioma.v2i12.1996

Abstract

This study aims to determine the effect of coating solutions consisting of control, lemon water, and salt water on the browning intensity of fresh-cut apples using a Completely Randomized Design (CRD). Enzymatic browning is a major problem in fresh-cut apples due to the oxidation of phenolic compounds triggered by the activity of the polyphenol oxidase enzyme. Lemon water acts through mechanisms of pH reduction and antioxidant activity, while salt water inhibits browning through ionic effects and osmotic pressure. The experiment was conducted using homogeneous apple units, and the browning scores obtained were analyzed using ANOVA at a 5% significance level. The results showed a significant effect among treatments, with an F-value of 5.136 exceeding the F-table value of 4.226. Lemon water was found to be the most effective in inhibiting browning, followed by salt water, while the control treatment exhibited the highest browning intensity. These findings confirm that simple natural materials can serve as effective anti-browning coatings, especially when applied to homogeneous experimental units using a CRD.
Co-Authors Arnita Arnita Daulay, Nurfitri Humayro Faradhilah, Anatasia Faradhilla, Anatasia Hani, Aulia Hutapea, Risca Octaviyani Ndruru, Albert Servant NURMAYANI NURMAYANI Panjaitan, Hotnauli Roni Arta Pulungan, Zakiy Maulana Putri, Alya Nabila Putri, Amelia Simanjuntak, Ferdyanto Abangan Sinaga, May Rani Tabitha Sitorus, Yolanda Angelina Tampubolon, Bungaria