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Fahrudin Muhtarulloh
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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 11 Documents
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Search results for , issue "Vol 10 No 1 (2025): IN PRESS" : 11 Documents clear
Risk Analysis of Oyster Mushroom Cultivation Success through Artificial Neural Network with Backpropagation Algorithm Aslam, Fazri; Lubis, Riri Syafitri
KUBIK Vol 10 No 1 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

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Abstract

Consumption mushroom cultivation is still rare in most parts of Indonesia, although the demand for this agricultural product continues to increase. Mushroom business opportunities are actually quite promising. This research aims to analyze the prediction of the risk level of oyster mushroom cultivation success using the artificial neural network method with the Backpropagation algorithm. This research combines qualitative and quantitative approaches, with data analysis methods in the form of Backpropagation algorithm training implemented through MATLAB software. Based on the results of testing or training conducted using the 5-3-1 Artificial Neural Network (JST) architecture and Epoch 1, the minimum error is 0.6 or 4 kg of yield (IDR 80,000), while the maximum error is 0.7 or 5 kg of yield (IDR 100,000). with a training MSE of 0.0964 with This means that artificial neural networks can create patterns to predict the yield of oyster mushroom cultivation.
Improve of Multiobjective Model on the Classification Problem of Food Consumption Levels in Indonesia Susanti, Eka; Dewi, Novi Rustiana; Arsi, Arsi
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.v10i1.40632

Abstract

Classification is the process of grouping objects based on similarities and differences. In this article, a multi-objective classification model is developed with three objective functions, namely the function that maximizes the values of accuracy, sensitivity and specificity. The developed model is applied to the problem of classifying meat, egg and fish consumption levels. The classification method used is K-Nearest Neighbor (KNN) with three objective functions and the addition of the GridSearchCV module to the KNN calculation. Completion of the multiobjective model using the weighting method and Particle Swam Optimization (PSO). Based on the data, with objective function weights of 1, 2 and 3 respectively being 0.7, 0.15 and 0.15, the results obtained for Rural Areas Meat, Fish and Egg Attributes of the model performance are in good criteria. for Urban Areas Attributes of Meat, Fish and Eggs the model's performance in the criteria is very good. Addition of the GridsearchCV module can facilitate the calculation of the KNN method classification because the model will provide the best k value without having to do repeated calculations.
Optimization of Multi-Product Distribution with Modification of The Modified Exponential Approach Method Pajriah, Dwi; Pasaribu, Meliana; Kiftiah, Mariatul
KUBIK Vol 10 No 1 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

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Abstract

In the distribution of several different products, there is a condition where product allocation is not appropriate or there is a multi-product transportation problem. As a result, it is necessary to analyze the appropriate product allocation with minimum shipping costs. In solving this problem, a multi- product transportation problem model and modification of the Modified Exponential Approach method are proposed to obtain an allocation for each product with minimum shipping costs. In the case of the distribution of sweet snack products and spicy/salty snacks at the MSME Giu Store. Delivery is carried out using delivery services (J&T Express, Surya Cargo) and private delivery. Therefore, this problem is a form of transshipment problem. This problem is transformed into a multi-product transportation problem and solved by modifying the Modified Exponential Approach method. The calculation results show that private delivery is inefficient. It is recommended that products be distributed by J&T Express with delivery to the Sambas, Sekadau, and Sintang areas. Surya Cargo delivers to the Sanggau, Mempawah, and Singkawang areas. With this allocation, a minimum distribution cost of Rp 1,378,398 is obtained.
Implementation of BiLSTM to Predict World Crude Oil Prices Sari, Firda Yunita; Ulinnuha, Nurissaidah
KUBIK Vol 10 No 1 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

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Abstract

The main source of energy worldwide is crude oil, which is used by almost all countries as an energy source. Crude oil plays a key role in driving the global economy, especially in the industrial and transportation sectors. Along with technological developments, crude oil price predictions can be made more sophisticated using artificial intelligence-based methods, one of which is the Bidirectional Long Short-Term Memory (BiLSTM) method which is a development of the Long Short-Term Memory (LSTM) method by combining past and future information when processing sequential data, BiLSTM uses forward and backward LSTM simultaneously to increase accuracy. The study used world crude oil price data for 1 year. There are 57 tests with several parameters such as data division, number of neurons, batch size, and activation function. After testing with the BiLSTM method for 57 scenarios, there is the smallest MAPE value of 0.09% at a data division of 90:10, number of neurons 100, batch size of value 4, and ReLu activation function. The resulting prediction model is highly accurate based on the MAPE criterion value.
Penerapan Regresi Binomial Negatif Dalam Menganalisis Faktor-Faktor Yang Mempengaruhi Kasus Angka Kematian Ibu Di Indonesia Hutabarat, Ida Mariati; Kelirey, Rifky Ibrahim; Chairani, Ikfina
KUBIK Vol 10 No 1 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

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Abstract

Angka Kematian Ibu (AKI) adalah indikator yang menggambarkan jumlah kematian perempuan yang diakibatkan oleh komplikasi selama kehamilan, persalinan, dan masa nifas per 100.000 kelahiran hidup. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi angka kematian ibu di Indonesia berdasarkan data dari Profil Kesehatan Tahun 2022. Data mengalami overdispersi, sehingga analisis dilanjutkan dengan menggunakan regresi binomial negatif. Penelitian ini mempertimbangkan lima variabel prediktor yaitu Persentase Cakupan Pelayanan Kesehatan (K4), Persentase Cakupan Pelayanan Kesehatan (K6), Persentase Cakupan Imunisasi Td2+ pada Ibu Hamil, Persentase Ibu Hamil yang Mendapatkan Tablet Tambah Darah (TTD), dan Persentase Ibu Nifas yang Mendapatkan Vitamin A. Hasil analisis menunjukkan bahwa Persentase Cakupan Pelayanan Kesehatan (K6) merupakan variabel yang secara signifikan mempengaruhi angka kematian ibu. Nilai Akaike Information Criterion (AIC) dari model ini adalah sebesar 375,75, dengan tiga variabel prediktor yang signifikan. Penelitian ini mengindikasikan bahwa peningkatan cakupan pelayanan kesehatan (K6) berhubungan positif dengan peningkatan angka kematian ibu. Hal ini menunjukkan bahwa peningkatan cakupan pelayanan kesehatan (K6) yang tidak diimbangi dengan kualitas pelayanan dapat berkontribusi pada peningkatan angka kematian ibu. Oleh karena itu, kebijakan kesehatan yang berfokus pada peningkatan cakupan harus disertai dengan peningkatan kualitas pelayanan kesehatan untuk mengurangi angka kematian ibu di Indonesia.
PARAMETER ESTIMATION AND ANALYSIS OF AVERAGE YEARS OF SCHOOLING IN MERAUKE DISTRICT WITH BIRNBAUM-SAUNDERS DISTRIBUTION APPROACH Langowuyo, Agustinus; Yokhu, Sara; Reba, Felix
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.v10i1.42992

Abstract

Average years of schooling is an important indicator in assessing the success of education development in a region. This study aims to analyze data on average years of schooling in Merauke Regency, Papua Province, using the Birnbaum-Saunders (BS) Distribution approach. This distribution was chosen because of its ability to model data that has asymmetric characteristics and low variability. The parameters resulting from the analysis include a scale parameter (β) of 8.35, which reflects the average years of schooling of the population, and a shape parameter (α) of 0.0545, which indicates the low degree of dispersion of the data around the mean. The results of the analysis show that the average length of schooling in Kabupaten Merauke is at the junior high school (SMP) level, with a homogeneous data distribution. This homogeneity reflects good equity in access to education, but also indicates the potential for stagnation at certain levels of education. The Birnbaum-Saunders distribution proved to be effective in modeling education data in this region, providing a more accurate picture than traditional approaches. This research makes an important contribution in understanding the distribution pattern of average years of schooling in Merauke district. The results can be used as a basis for designing more targeted policies in improving the quality and access to education, especially at the senior secondary level. In addition, this approach can serve as a reference for analyzing education in other regions with similar geographical and socio-economic challenges
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

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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  

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