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KUBIK: Jurnal Publikasi Ilmiah Matematika
Published by UIN Sunan Gunung Djati Bandung
ISSN : 23380896     EISSN : 26860341     DOI : 10.15575/kubik
Core Subject : Economy, Science, Education,
Computer Science & IT Economics, Econometrics & Finance Mathematics
Fuzzy Systems and its Applications Geometry Theories and its Applications Graph Theories and its Applications Real Analysis and its Applications Operation Research and its Applications Statistical Theories and its Applications Dinamical Systems and its Applications Mathematics Modeling and its Applications Discrete Mathematics and its Applications Computer Mathematics and its Applications Mathematics Actuaria and its Applications
Arjuna Subject : Matematika - Matematika Terapan
Articles 157 Documents
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Courses Scheduling using Graph Labeling Ramdani, Rismawati; Nursyahida, Salwa
KUBIK Vol 10 No 1 (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.v10i1.44243

Abstract

At the beginning of each academic semester, universities are routinely required to develop course schedules that minimize or eliminate conflicts. Scheduling conflicts typically arise when multiple courses are taught by the same lecturer, taken by the same group of students, or require the use of the same classroom. As a result, an efficient and systematic method is needed to generate conflict-free schedules while optimizing the use of available time slots. One alternative approach is to apply graph theory, particularly graph coloring techniques, to the scheduling process. In this approach, each course is represented as a vertex in a graph, and an edge is established between two vertices if the corresponding courses cannot be held simultaneously. Graph coloring is then used to assign different time slots (represented as colors) to adjacent vertices, ensuring that no conflicting courses are scheduled at the same time. This paper proposes a course scheduling algorithm based on graph coloring, aiming to produce feasible schedules that reduce conflicts and enhance resource utilization. The approach provides a mathematical framework that can support automated and scalable scheduling systems in academic institutions.
Penerapan Model Seasonal Autoregressive Integrated Moving Average (SARIMA) dalam Peramalan Curah Hujan di Kabupaten Bandung Barat nadhira, valda azka; Ruchjana, Budi Nurani; Parmikanti, Kankan
KUBIK Vol 10 No 1 (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

The expansion of the Kabupaten Bandung, namely Kabupaten Bandung Barat (KBB) is located in hilly and lowland areas. Rainfall in Kabupaten Bandung Barat has an impact on the productivity and performance of key sectors, such as agriculture, plantations and tourism. Low rainfall can lead prolonged dry seasons and result in drought. Conversely, extreme rainfall can also have negative impacts, such as causing soil erosion and potentially affecting the appeal and smooth operation of tourist destinations. Therefore, rainfall forecasting is needed in making appropriate policies, especially regarding the impacts of rainfall changes in KBB. The Seasonal Autoregressive Integrated Moving Average (SARIMA) method is applied in this study to forecast rainfall in KBB. The aims of this research are to estimate the parameters of the SARIMA model using the Maximum Likelihood Estimation (MLE) method and to apply the SARIMA method in forecasting rainfall in KBB, particularly during the December-January-February (DJF) period. The results of the analysis show that the SARIMA model can be applied to forecast rainfall in KBB. The best SARIMA model obtained ARIMA(2,1,0)(0,0,1)3 with a MAPE value 17,80%, which indicates an accurate forecasting criterion. Keywords: SARIMA, MLE, Rainfall.
Probabilistic Model of Back Order Policy on Dodol Pulut Raw Material Inventory Control With Linear Programming Br Siahaan, Erika Handayani; Riri Syafitri Lubis
KUBIK Vol 10 No 1 (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.v10i1.49121

Abstract

The high production costs of Dodol Pulut Raya further emphasize the importance of implementing a systematic, measurable, and effective inventory control strategy to maintain profitability, operational efficiency, and long-term business stability. This study applies the Probabilistic Back Order Policy Model combined with the Simplex Linear Programming method to determine the most optimal raw material management policy, taking into account demand uncertainty, supply variability, and the risk of stock shortages that could disrupt production smoothness. This approach comprehensively integrates precise safety stock calculations to minimize stockouts, reduce production delays, and ensure raw material availability so that customer needs can be consistently, timely, and sustainably met. The analysis results show that the implementation of this model can significantly reduce annual production costs from IDR 509,941,040 to IDR 338,719,300, resulting in cost efficiency of IDR 171,221,740 per year. This finding demonstrates the model's effectiveness in minimizing total inventory costs while enhancing competitiveness and operational sustainability. Additionally, this study provides a practical framework for small and medium-sized enterprises facing fluctuating demand, balancing service levels, safety stock, and overall cost optimization.
Application of the Clarke and Wright Savings Algorithm to Solve the Vehicle Routing Problem in Optimizing Chip Distribution Sitompul, Apri Yani; Husein, Ismail
KUBIK Vol 10 No 1 (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.v10i1.49162

Abstract

Efficiency in the distribution process is crucial for companies to reduce operational costs while maintaining service satisfaction. This research aims to optimize the product delivery route for the Keripik Cinta Mas Hendro business by applying the Clarke and Wright Savings algorithm approach to solve the Vehicle Routing Problem (VRP). This method works by calculating the distance savings from combining distribution points, then constructing optimal routes based on the order of highest savings while still considering vehicle capacity. The data used consists of customer coordinates, which are processed into distances between locations using the Euclidean formula. The results show that the distribution route, which was initially divided into three lanes with a total length of 403.54 km, can be simplified into two lanes with a total length of 272 km. This study proves that the Clarke and Wright Savings algorithm is able to provide a more cost-effective distribution solution. Keywords: Distribution, Optimization, Chips, VRP, Clarke and Wright SavingsMSC2020:  90B06, 68W40, 90C59 Abstrak Efisiensi dalam proses distribusi sangat penting bagi perusahaan agar dapat menekan biaya operasional sekaligus menjaga kepuasan pelayan. Penelitian ini bertujuan untuk mengoptimalkan jalur pengiriman produk keripik pada usaha Keripik Cinta Mas Hendro dengan menerapkan pendekatan algoritma Clarke and Wright Savings dalam menyelesaikan permasalahan Vehicle Routing Problem (VRP). Metode ini bekerja dengan menghitung nilai penghematan jarak dari penggabungan titik-titik distribusi, lalu menyusun rute optimal berdasarkan urutan penghematan tertinggi yang tetap memperhatikan kapasitas kendaraan. Data yang digunakan berupa koordinat pelanggan yang diolah menjadi jarak antar lokasi menggunakan rumus euclidean. Hasil menunjukkan bahwa rute distribusi yang semula terbagi tiga jalur dengan total 403,54 km dapat disederhanakan menjadi dua jalur dengan total 272 km. Penelitian ini membuktikan bahwa algoritma Clarke and Wright Savings mampu memberikan solusi distribusi yang lebih hemat. Kata kunci: Distribusi, Optimasi, Keripik, VRP, Clarke and Wright Savings MSC2020:  90B06, 68W40, 90C59  
Optimization of Potato and Carrot Production in Karo District Using the Beale Method riezky, riezkyfadhillah; Rina Filia Sari
KUBIK Vol 10 No 1 (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.v10i1.49213

Abstract

This study aims to optimize land allocation for potato and carrot production in Karo Regency, North Sumatra, using a quadratic programming approach using the Beale method. Secondary data from the Karo Regency Agriculture Office for 2018-2024 are used to construct a quadratic objective function using the least squares method. The Beale method is applied iteratively to solve optimization problems with linear constraints. The results show that the optimal land allocation of 0.5382 hectares for carrots and 0.4005 hectares for potatoes provides a maximum yield of 1.6239 tons. These findings demonstrate the effectiveness of the mathematical optimization approach in improving land use efficiency and supporting data driven decision making in the horticultural agricultural sector.
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.

Page 16 of 16 | Total Record : 157

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