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All Journal Algoritma: Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian dan Angkasa International Journal of Applied Mathematics and Computing. J-CEKI
Kosasih, Eva
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Humanities Computer Science & IT Earth & Planetary Sciences Mathematics Social Sciences

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Analisis Perpindahan Preferensi Konsumen Antar Merek Mie Instan Menggunakan Model Markov Chain: Studi Kasus: Mie Gacoan, Mie Kober, dan Wizzmie Kosasih, Eva; Barus, Eka Valencia Br; Rusniati, Ni Wayan; Cahyani, Cokorda Istri Sintya Dwi Mirah
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 3: April 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i3.8352

Abstract

This study aims to analyze consumer brand switching behavior among three instant noodle brands: Mie Gacoan, Mie Kober, and Wizzmie, using the Markov Chain model. The Markov Chain method is employed to determine transition probabilities of consumer preferences and predict future consumption behavior based on past patterns. A survey of 100 respondents was conducted, focusing on their brand preferences over the past three months and their most recent consumption choice. The results indicate that Mie Gacoan has the highest consumer retention rate, whereas Mie Kober and Wizzmie exhibit varying switching patterns. The equilibrium transition probabilities predict that, in the long run, Mie Gacoan will hold 74% of the market share, Mie Kober 4%, Wizzmie 9%, and 'Other' brands 13%.
Identification of Risk Factors for Chronic Kidney Disease Using Binary Logistic Regression Kosasih, Eva; Asmara Santhi, Ni Kadek Wulanda; Febriyanti, Ni Wayan Atik; Br Barus, Eka Valencia; Susilawati, Made
International Journal of Applied Mathematics and Computing Vol. 2 No. 3 (2025): July : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i3.222

Abstract

Chronic Kidney Disease (CKD) is a major global health issue that can lead to serious complications and long-term medical care. This study aims to identify key clinical factors associated with CKD status using binary logistic regression analysis. The dataset, obtained from Kaggle, contains 400 patient records with various clinical and demographic attributes. The dependent variable is CKD status (positive or negative), while the independent variables include age, blood pressure, hemoglobin level, urine albumin level, and serum creatinine. Initial analysis involved descriptive statistics and multicollinearity checks, followed by model estimation and evaluation using likelihood ratio and Wald tests. The final model identified four significant predictors: blood pressure, hemoglobin, urine albumin, and serum creatinine. The model achieved a high classification accuracy of 95.50% and an Area Under the ROC Curve (AUC) of 98.78%, indicating excellent predictive performance. These results highlight the importance of these clinical indicators in early CKD detection and support their use in risk assessment models for kidney disease screening Keywords: Chronic Kidney Disease, Binary Logistic Regression, Likelihood Ratio Test, Wald Test, Classification Accuracy
Optimisasi Keuntungan Produksi Kue pada Cake By Cece Menggunakan Algoritma Branch and Bound Kosasih, Eva; Rusniati, Ni Wayan; Tari Tastrawati, Ni Ketut
Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa Vol. 3 No. 5 (2025): Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/algoritma.v3i5.748

Abstract

This study aims to optimize the cake production profit at Cake by Cece using the Branch and Bound algorithm. The data used include raw material requirements per batch, daily raw material availability, and selling prices for three types of cakes: Cookies, Brownies, and Cinnamon Roll. The optimization model is formulated as an Integer Linear Programming problem with the objective of maximizing total daily profit. The model is solved using the simplex method followed by the Branch and Bound algorithm to obtain valid integer solutions. The results indicate that the optimal production combination is 2 batches of Cookies, 2 batches of Brownies, and 3 batches of Cinnamon Roll, yielding a maximum profit of IDR 233,000 per day. This solution satisfies all raw material constraints and is feasible for daily operational implementation. This study provides quantitative recommendations to support production decision-making in culinary sector MSMEs.
Co-Authors Asmara Santhi, Ni Kadek Wulanda Barus, Eka Valencia Br Br Barus, Eka Valencia Cahyani, Cokorda Istri Sintya Dwi Mirah Febriyanti, Ni Wayan Atik Made Susilawati Rusniati, Ni Wayan Tari Tastrawati, Ni Ketut