cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota bandung,
Jawa barat
INDONESIA
Kubik
Published by Universitas Islam Negeri Sunan Gunung Djati Bandung
ISSN : -     EISSN : -     DOI : -
Core Subject : Education,
Education
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol 10 No 2 (2025): IN PRESS" : 5 Documents clear
Bellman-Ford Algorithm for Optimizing Drinking Water Distribution by Perumda Air Minum Tirta Raharja in Cicalengka Lusiani, Anie; Sartika, Euis; Nuryati, Neneng; Hedi, Hedi
KUBIK Vol 10 No 2 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Access to clean water in Cicalengka District, Bandung Regency, remains limited, with current coverage reaching only 5.08% of the population. Perumda Air Minum Tirta Raharja has set a target to expand drinking water service to 44% by 2030. To support this goal, this study investigates the optimization of the water distribution pipe network in Cicalengka. The research applies the Bellman-Ford algorithm to model the distribution network as a weighted, undirected, and connected graph, where customer houses are represented as vertices, pipe connections as edges, and pipe lengths as weights. Using data from the existing network and customer locations, the algorithm was implemented to identify optimal distribution paths. The results yielded two shortest path alternatives between the specified source and destination nodes. These findings demonstrate the potential of graph-based optimization in improving distribution planning and can serve as a reference for the development and management of future water supply infrastructure.
Statistical Optimization of Experimental Conditions for Enhanced Removal of Heavy Metals from Wastewater Sylvi, Pismia
KUBIK Vol 10 No 2 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v10i2.49983

Abstract

Increasing concentrations of heavy metals in industrial liquid waste demand the development of more efficient treatment strategies to minimize the impact on the environment and public health. This study aims to statistically optimize experimental conditions to improve the efficiency of heavy metal removal (especially Pb²⁺, Cd²⁺, and Cr⁶⁺) from synthetic liquid waste through the batch adsorption process. A well-planned experimental design was implemented using the Response Surface Methodology (RSM) approach with Central Composite Design (CCD) to evaluate the individual influences as well as interactions of four key variables: the initial concentration of the metal, the pH of the solution, the adsorbent dose, and the contact time. The results of the experiment were modeled in the form of second-order polynomial regression, and model validation was carried out strictly through variety analysis (ANOVA), determination coefficients (adjusted R² and R²), and lack-of-fit tests. The optimization process successfully identified a combination of operating parameters that significantly improved the elimination efficiency, reaching a level above 95% at the optimized conditions that had been validated. The residue analysis showed the fulfillment of the assumptions of normality, homogeneity of variance, and error independence, thus confirming the predictive reliability of the model. These findings confirm the effectiveness of RSM-based optimization approaches in wastewater treatment research, as well as the importance of statistical-based experimental planning in maximizing process efficiency. This approach provides a robust framework for advanced applications in industrial waste management and sustainable environmental engineering.
Logistic Regression Analysis to Determine Factors Influencing Career Choices of Undergraduate Alumni: Analisis Regresi Logistik untuk Menentukan Faktor-Faktor yang Mempengaruhi Pilihan Karir Lulusan Sarjana Perguruan Tinggi Febrian, Didi; Harliana, Putri; Farhana, Nurul Ain
KUBIK Vol 10 No 2 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v10i2.45050

Abstract

An undergraduate alumni has three career choices, namely work, postgraduate study or entrepreneurship. The success of an alumni's career is not only influenced by academic knowledge, but also by other factors that reflect the individual's personal and professional abilities. These factors are certainly obtained from the experiences that the alumni have gone through while studying for their undergraduate program. The respondents of this study were 100 undergraduate alumni of Universitas Negeri Medan in 2021 and 2022. This study aims to determine the effect of GPA (X1), study period (X2), number of achievements (X3), organizational activity (X4), work intensity during undergraduate (X5), and TOEFL score (X6) on alumni career choices (Y). In logistic regression analysis, the independent variable must have at least two categories so that the alumni's career choices (Y) are working (0) and postgraduate study (1). The results of the study showed that only the work intensity factor during S1 (X5) and TOEFL score (X6) had a significant influence on alumni career choices. The Logistic Regression Model based on the influential variables was . The percentage of model accuracy can predict correctly by 72.0%.
Model Indeks Tunggal Dalam Optimalisasi Portofolio Saham dan Long Short Term Memory dalam Peramalan Harga Saham Optimal Aeni, Kurnia'; Rohaeti, Embay; Widyastiti, Maya
KUBIK Vol 10 No 2 (2025): IN PRESS
Publisher : Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak Dalam berinvestasi, berbagai pilihan saham dihadapkan oleh investor. Strategi yang diperlukan oleh investor dapat meminimalkan risiko dan memaksimalkan potensi keuntungan. Salah satu yang diperlukan dengan pendekatan Model Indeks Tunggal untuk dapat mengoptimalkan saham dalam portofolio, sehingga dapat memberikan keputusan saham yang optimal. Pada saham yang telah optimal dapat dilanjutkan untuk diramalkan harga saham terpilih. Harga saham memiliki pergerakan ketidakpastian, sehingga diperlukan pendekatan Long Short-Term Memory (LSTM). Pendekatan LSTM untuk menangani kompleksitas harga saham. Pendekatan LSTM ini dapat memberikan hasil peramalan harga saham yang akurat pada periode mendatang. Tujuan penelitian untuk mengoptimalisasi portofolio saham serta meramalkan harga saham optimal terpilih untuk periode mendatang. Data penelitian menggunakan data saham Blue Chip. Pada tahapan pertama dilakukan dengan Model Indeks Tunggal dan tahapan kedua meramalkan harga saham yang telah optimal terpilih dengan LSTM. Hasil tahapan pertama diperoleh 13 saham yang termasuk ke dalam portofolio optimal. Pada hasil tahapan kedua diperoleh peramalan kinerja harga saham dengan performa terbaik. Akurasi peramalan kinerja harga saham diperoleh dengan MAPE sebesar 4,23%. Hasilnya dapat dikatakan peramalan dari kinerja harga saham memiliki akurasi sangat baik. Kata kunci: Portofolio Saham, Model Indeks Tunggal, , Long Short-Term Memory (LSTM)
Identification of Banking Stock Risk Factors through Stochastic Search Variable Selection in a CoVaR Models Based on Quantile Regression and Quantile Autoregressive Almas, Luqyana; Prastyo, Dedy Dwi; Rahayu, Santi Puteri
KUBIK Vol 10 No 2 (2025): IN PRESS
Publisher : Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The stability of the banking sector is crucial for maintaining economic balance, particularly in Indonesia where banks play a central role in the financial system. Conventional risk measures such as Value-at-Risk (VaR) mainly capture individual bank risk and are limited in assessing systemic risk arising from interbank spillovers. This study proposes an integrated systemic risk framework that combines Quantile Autoregressive (QAR) based VaR estimation with Conditional Value-at-Risk (CoVaR) derived from quantile regression, while incorporating Stochastic Search Variable Selection (SSVS) to identify key risk factors. The QAR approach accommodates asymmetry and heavy-tailed characteristics of bank return distributions, whereas CoVaR measures the conditional impact of bank distress on the overall financial system.  The SSVS is implemented within a Bayesian framework to select significant market and macroeconomic variables based on posterior inclusion probabilities. Model performance is evaluated using the Kupiec Proportion of Failures (POF) test. The results show that QAR-based VaR effectively captures tail risk at the 5% and 1% quantiles. CoVaR estimates reveal heterogeneity in systemic risk exposure, with medium-sized and digital banks exhibiting greater sensitivity to systemic stress than large banks. Overall, the CoVaR–SSVS model demonstrates superior validation performance and estimation stability compared to the conventional CoVaR approach.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol 10 No 2 (2025): IN PRESS Vol 10, No 1 (2025): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 10 No 1 (2025): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 9 No 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 9, No 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 9 No 1 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 8 No 1 (2023): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 7, No 1 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 6, No 2 (2021): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 6, No 1 (2021): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 6 No 1 (2021): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 5, No 2 (2020): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 5, No 1 (2020): KUBIK: Jurnal Publikasi Ilmiah Matematika Vol 4, No 2 (2019): KUBIK : Jurnal Publikasi Ilmiah Matematika Vol 4, No 1 (2019): KUBIK : Jurnal Publikasi Ilmiah Matematika Vol 3, No 2 (2018): KUBIK : Jurnal Publikasi Ilmiah Matematika Vol 3, No 1 (2018): KUBIK : Jurnal Publikasi Ilmiah Matematika Vol 3, No 1 (2018): KUBIK (Publikasi Ilmiah Matematika) Vol 2, No 2 (2017): KUBIK : Jurnal Publikasi Ilmiah Matematika Vol 2, No 1 (2017): KUBIK : Jurnal Publikasi Ilmiah Matematika Vol 1, No 1 (2015): KUBIK : Jurnal Publikasi Ilmiah Matematika More Issue