cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Jose Rizal
Contact Email
jrizal@unib.ac.id
Phone
6281321420921
Journal Mail Official
diophantine@unib.ac.id
Editorial Address
FMIPA Universitas Bengkulu JLWR Supratman Kelurahan Kandang Limun Kecamatan Muara Bangkahulu Kota Bengkulu
Location
Kota bengkulu,
Bengkulu
INDONESIA
Diophantine Journal of Mathematics and Its Applications
Published by Universitas Bengkulu
ISSN : -     EISSN : 2987906X     DOI : https://doi.org/10.33369/diophantine
Core Subject : Economy, Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering
The DJMA is published twice a year in June and December. This journal is managed by the Mathematics Department of Bengkulu University. The scope of this journal includes the fields of: 1. Mathematics 2. Applied Mathematics 3. Statistics 4. Applied Statistics 5. Computer Science.
Arjuna Subject : Matematika - Matematika Terapan
Articles 6 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2023)" : 6 Documents clear
Kajian Matematis Mengenai Strategi Pengembangbiakan Sapi Potong Lokal Guna Meningkatkan Kualitas Daging Sapi Hidayat, Zaki Maulana; Andzar Tsaqif Laksana; Anita Triska
Diophantine Journal of Mathematics and Its Applications Vol. 2 No. 1 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v2i01.27771

Abstract

Beef is one of the most demanded food products in Indonesia compared to other meat commodities. The high demand of this commodity causes a shortage of its supply so that the government has to import it from other countries. As the consequences, people in Indonesia prefer to consume imported beef rather than local beef, especially those in the food industry, since imported beef has better quality. Thus, government may establish a program that is able to increase the local beef quality thereby increasing its competitiveness, for instant by cross-breeding of local and imported cattle. This paper is to discuss a cross-breeding simulation to predict the distribution of offspring produced in the next few generations through mathematical approach. Simulations are conducted by following the X-Linked Inheritance concept and algebra. Simulations are carried out by three different scenarios which consider gender of the imported cattle. The simulations show that all scenarios are able to produce local cattle offspring with imported quality. However, the offspring from the cross-breeding still preserve cattle with original local genetic with a different ratio between the first and the second scenario.
Analisis Manajemen Pengelolaan Pohon Gmelina arborea Roxb. pada Hutan Rakyat di Tasikmalaya dan Banjar, Jawa Barat Ellena, Siti Aizal Yasni; Lidia H. Y. A. Rudamaga; Anita Triska
Diophantine Journal of Mathematics and Its Applications Vol. 2 No. 1 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v2i01.27772

Abstract

Forests are natural resources which if it is managed properly can provide the economic benefits to the surrounding. Woods from trees in the forest are one of the economic benefits that can be gained from the forest. However, trees must be logged under a precise calculation and controlled continuously so that they are not extinct. Logging time in a forest is generally determined by the needs of farmers, which may not necessarily provide maximum benefits. Therefore, harvesting management is needed to obtain optimal benefits while still maintaining the forest sustainability. This paper discusses a basic model of the tree harvesting using Linear Algebra which is applied to one of economically valuable trees, i.e., Gmelina arborea Roxb. on the community forest in Tasikmalaya and Banjar, West Java. Initially, the tree population is divided into 16 class intervals based on their diameter. Analysis of the harvesting model implies that the optimal results will be obtained by logging all of trees in one class with the highest selling value. By applying this scenario, all of the Gmelina arborea Roxb. on the community forest in Tasikmalaya and Banjar, West Java must be logged at the 9th class which will provide a maximum profit of IDR 12,491,843.889 for every 1,000 trees harvested.
Analisis Persediaan Bahan Baku Multi Item Usaha Kerupuk Kulit Alhamdulillah Menggunakan Metode Economic Order Quantity Cahyani, Vebby Afifah Cahyani; Rizal, Yusmet
Diophantine Journal of Mathematics and Its Applications Vol. 2 No. 1 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v2i01.28208

Abstract

Controlling raw material stocks is a crucial aspect of effective inventory management for businesses. The company's objective is to maximise profits. To maximise earnings, the corporation must prudently maintain appropriate inventory levels in order to limit existing inventory expenses. Kerupuk Kulit Alhamdulillah is a small to medium-sized business in the food industry that manufactures skin crackers in various packaging sizes. This is an example of applied research. This study employs the Lilliefors normality test to assess if the data are normally distributed. According to the findings of calculations using the method Economic Order Quantity (EOQ), the entire cost of multi-item raw material inventory according to the Kerupuk Kulit Alhamdulillah is Rp 4,703,520.00, however according to the EOQ method, the total cost is Rp 2,093.00. Kerupuk Kulit Alhamdulillah Business can save Rp 2,694,427.00 by utilising the EOQ approach.
Klasifikasi Kualitas Air Minum menggunakan Penerapan Algoritma Machine Learning dengan Pendekatan Supervised Learning Savitri, Lidya; Nursalim, Rahmat
Diophantine Journal of Mathematics and Its Applications Vol. 2 No. 1 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v2i01.28260

Abstract

The need for the provision and service of clean water from time to time is increasing which is sometimes not matched by the ability and knowledge of clean water. The majority of people still do not know whether water is suitable for consumption or not. The quality of drinking water can be distinguished based on the mineral parameters contained in the water. This article will explain the classification of water sample data by applying a Machine Learning Algorithm, which includes modeling with Logistic Regression, Support Vector Machine (SVM), Random Forest Classifier, K- Nearest Neighbor(KNN), XGBoost Classifier. Classification models produce varying degrees of accuracy. The highest accuracy is obtained in the Random Forest Classifier model with an accuracy rate of 78%. Analysis of drinking water quality with machine learning algorithms is very easy to understand, because the results of this study produce very simple results so that they are easy to understand
Implementasi Algoritma Greedy pada Pewarnaan Wilayah Peta Kecamatan Gelumbang Muara Enim Al Jufri, Khuzaimah; Agustiani, Riza
Diophantine Journal of Mathematics and Its Applications Vol. 2 No. 1 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v2i01.28347

Abstract

A map becomes more attractive and easier to read when it is colored. However, excessive use of color can make the map ineffective. Gelumbang Subdistrict was chosen because its map had not yet been colored. Graph theory can be applied to the problem of map region coloring. Gelumbang Subdistrict is represented by a dual graph consisting of 23 vertices and 53 edges. The Greedy Algorithm was chosen as the solution to the coloring optimization problem for the Gelumbang Subdistrict map, resulting in a minimum coloring that uses four colors to represent all 23 villages within the subdistrict.
Performa Teknik Regularisasi Dalam Penanganan Masalah Multikolinieritas Fikri, Alin Febianti; Agwil, Winalia; Agustina, Dian
Diophantine Journal of Mathematics and Its Applications Vol. 2 No. 1 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v2i01.28480

Abstract

Multikolinieritas adalah kondisi terdapat hubungan linier antar variabel independen, dimana diantara variabel independen tersebut saling berkorelasi. Akibatnya akan sulit untuk melihat pengaruh variabel independen terhadap variabel dependen. Penanganan multikolinieritas salah satunya dapat dilakukan menggunakan teknik regularisasi yaitu bentuk regresi yang mengatur atau menyusutkan perkiraan koefisien menuju nol. Teknik regularisasi yang akan dibahas pada penelitian adalah regresi ridge, LASSO dan elastic net. Regresi ridge hanya dapat menyusutkan koefisien regresi menuju angka 0, tetapi tidak pernah tepat ke angka 0. Regresi elastic net dapat menyusutkan koefisien regresi tepat nol, melakukan seleksi variabel secara simultan dan dapat memilih kelompok peubah yang berkorelasi. Sedangkan, regresi LASSO hanya dapat menyusutkan koefisien dan menetapkan koefisien ke angka 0. Oleh karena itu, LASSO dapat menghasilkan model dengan variabel terbaik. Namun, LASSO memiliki beberapa kelemahan. Ketika jumlah variabel independent lebih kecil dibanding jumlah amatan, kinerja LASSO lebih didominasi oleh ridge. Ketika jumlah variabel independent lebih besar dibanding jumlah amatan, maka LASSO hanya memilih n variabel yang diikutkan dalam model. Sehingga, untuk mengatasi high dimensional data yang mengandung multikolinieritas dilakukan penelitian menggunakan teknik regularisasi regresi ridge, LASSO dan elastic net untuk dibandingkan kebaikan modelnya berdasarkan nilai MSE terkecil. Data yang digunakan merupakan data simulasi dan studi kasus dari website resmi BPS serta UCI machine learning repository. Disimpulkan bahwa dari 30 pengacakan, model ridge baik memodelkan dataset dengan p = 20, 40, dan 80 atau kondisi dataset dimana jumlah variabel independent lebih kecil dibanding jumlah amatan dan elastic net baik memodelkan dataset dengan p = 100, 160, dan320.

Page 1 of 1 | Total Record : 6

 1 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol. 4 No. 1 (2025) Vol. 3 No. 2 (2024) Vol. 3 No. 1 (2024) Vol. 2 No. 2 (2023) Vol. 2 No. 1 (2023) Vol. 1 No. 1 (2022)