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Sinkron : Jurnal dan Penelitian Teknik Informatika
Published by Politeknik Ganesha Medan
ISSN : 2541044X     EISSN : 25412019     DOI : 10.33395/sinkron.v8i3.12656
Core Subject : Science,
Computer Science & IT
Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial Neural Network 14. Fuzzy Logic 15. Robotic
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 1,196 Documents
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A Decision Model For Tackling Logistic Optimization Problem in Online Business Environment Syahraini, Syahraini; Efendi, Syahril; Sitorus, Syahriol
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11593

Abstract

Online business has increased during the COVID-19 pandemic, but the emergence of a number of problems, namely reduced material supply, price fluctuations because an item is difficult to distribute and slow delivery due to transportation of goods based on the type of transportation used (Trucks, Trains, Airplanes and Ships). a number of declines due to the COVID-19 virus pandemic, resulting in longer order waiting times. Pick-up and Delivery Issues are variations of Vehicle Routing Issues that appear in many real-world transportation scenarios, such as product delivery and courier services. This work studies the Pickup and Delivery Problem with Time Windows, where goods must be transported from one location to another, with taking into account certain time limits and vehicle capacity. This aims to minimize the number of vehicles used, as well as operational costs for all routes. To solve this problem, a mathematical model in the form of is used Mixed Integer Linear Programming (MILP) from Pickup and Delivery Problems with Time Windows
Using the Deep Constrained Clustering Approach to Create a Business Profile Latif, Abdul; Sutarman; Damius, Open
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11594

Abstract

Identification of customers in the business sector that really needs to be done as an evaluation of a business that is run so that it can continue to grow and be able to follow business developments in the same sector. The deep constraint clustering approach is used to cluster customers towards a business. In this study, a clustering of customers using rail mass transportation will be carried out. The results achieved are the formation of 6 clusters using trains be built. The result of research expected to be a consideration in improving services to the company
THE CYCLE LENGTH OF SPARSE REGULAR GRAPH Christy, Claudia; Suwilo, Saib; Tulus, Tulus
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11595

Abstract

Let be a reguler graph with girth . Set of cycle length in Graf is denoted by . Graph is a sparse graph if and only if . Furthermore, it was obtained the number of cycle length of sparse reguler graph which denoted is .
Development of The Steepest Descent Method for Unconstrained Optimization of Nonlinear Function Evada, Zakiah; Tulus; Herawati, Elvina
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11596

Abstract

The q-gradient method used a Yuan step size for odd steps, and geometric recursion as an even step size (q-GY). This study aimed to accelerate convergence to a minimum point by minimizing the number of iterations, by dilating the parameter q to the independent variable and then comparing the results with three algorithms namely, the classical steepest descent (SD) method, steepest descent method with Yuan Steps (SDY), and q-gradient method with geometric recursion (q-G). The numerical results were presented in tables and graphs. The study used Rosenbrock function f(x)=〖(1-x_1)〗^2+100〖(x_2-〖x_1〗^2)〗^2 and determined μ=1,σ_0=0.5,β=0.999, the starting point (x_0) with a uniform distribution on the interval x_0= (-2.048, 2.048) in R^2, with 49 starting points (x_0) executed using the Python online compiler on a 64bit core i3 laptop. The maximum number of iterations was 58,679. Using tolerance limits as stopping criteria is 10-4 and the inequality 〖f(x〗^*)>f to get numerical results. q-GY method down ward movement towards the minimum point was better than the SD and SDY methods while the numerical results of the Rosenbrock function showed good enough performance to increase convergence to the minimum point
Support Vector Machine Using A Classification Algorithm Ovirianti, Nurul Huda; Zarlis, Muhammad; Mawengkang, Herman
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11597

Abstract

Support vector machine is a part of machine learning approach based on statistical learning theory. Due to the higher accuracy of values, Support vector machines have become a focus for frequent machine learning users. This paper will introduce the basic theory of the Support vector machine, the basic idea of classification and the classification algorithm for the support vector machine that will be used. Solving the problem will use an algorithm, and prove the effectiveness of the algorithm on the data that has been used. In this study, the support vector machine has obtained very good accuracy results in its completion. The SVM classification uses kernel RBF with optimum parameters Cost = 5 and gamma = 2 is 88%.
OPTIMIZATION MODEL IN CLUSTERING THE HAZARD ZONE AFTER AN EARTHQUAKE DISASTER Bangun, Monica Natalia; Darnius, Open; Sutarman
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11598

Abstract

There are a large number of approaches to clustering problems, including optimization-based methods involving mathematical programming models to develop efficient and meaningful clustering schemes. Clustering is one of the data labeling techniques. K-means clustering is a partition clustering algorithm that starts by selecting k representative points as the initial centroid. Each point is then assigned to the nearest centroid based on the selected specific proximity measure. This writing is focused on the grouping of post-earthquake hazard zones based on grouping with regard to certain characteristics which aim to describe the process of partitioning the N-dimensional population into K-sets based on the sample. This research consists of three steps, namely standardization, data clustering using K-means and data interpolation using the K-means clustering algorithm and zoning of 7 variables, namely magnitude, depth, victim died, the victim didn’t die, public facilities were heavily damage, public facilities were slightly damage, and affected areas.
Decision Model for Unplanned ICU Transfer in a Hospital with Association Rule Learning Lestari, Nanda; Sawaluddin; Gultom, Parapat
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11599

Abstract

The initial decision after treatment in the hospital emergency room is very important because apart from being an indicator of the quality of care for emergency room practitioners, it is also needed to achieve health goals, namely improving the quality of critical care and preventing death. The initial decision was also for an unplanned ICU transfer. Unplanned ICU transfer is the transfer of patients who originally came from the ER (Emergency Room), then to the Inpatient Room (having been treated for 24-48 hours), then to the ICU. Many studies have been carried out to predict the initial decision of unplanned ICU transfer using univariate analysis, logistic regression analysis, and association rules. The association rule algorithm generates rules between patient diagnosis features that form a decision model for unplanned ICU transfers, so it is essential to get an association rule algorithm that is more efficient in generating rules. In this study, we compare two association rule algorithms to get a more efficient algorithm; then, the rules are used to form a decision model for unplanned ICU transfers. The study results obtained that the Apriori algorithm requires a completion time of 3 ms and the FP-Growth algorithm requires a completion time of 31 ms. Hence, the FP-Growth algorithm is 28 ms more efficient than the Apriori algorithm, while the resulting rule generation is the same number of 67 rules. Only 11 rules meet the minsupp and minconf threshold and include the set of Class Association Rules (CAR), which are used to form a decision model for unplanned ICU transfers with binary integer programming
Data-Driven Decision Making In Large Scale Production Planning Christefa, Dea; Mawengkang, Herman; Zarlis, Muhammad
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11600

Abstract

Production planning is a very important part for a company in making the right decisions before carrying out production activities in order to obtain maximum profit with a minimum level of production costs. Production planning is defined as a process in producing goods and services within a certain period by considering resources such as labor, materials, machinery and etc. In this research, a production planning model is produced based on several variables and parameters that can assist in making production decisions
Graph-Based Modeling for Optimal Strategy in Online Buying Tarigan, Ruffiana; Mardiningsih; Suwilo, Saib
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11601

Abstract

Discount is a type of online purchase promotion that is presented based on the total value of consumer purchases. In this paper, an online purchase optimization problem will be studied, where a buyer is interested in buying several items (x≥2) by considering the total value discounts from different retailers, so that result in significant cost savings. The comparison shopping websites can be an alternative for consumers to find and compare information on items they want to buy from many online retailers. An integer programming formulation is proposed to obtain a near-optimal model of the online purchase problem. Then this formulation was developed into a graph-based modeling which was presented to build an optimization model (OptiGraph). The OptiGraph model obtained consists of the OptiNode set (subgraph) SG_a,SG_b,SG_c (retailer a, b, and c which contains nodes m_1 and m_2 in each subgraph representing the item to be purchased) and the OptiEdge set which describes the relationship between nodes in the subgraph. All nodes and edges contain the constraint function properties of the integer programming formulation of the online purchase problem with discount.
The Maximum Degree of an Exponentially Distributed Random Graph Harahap, Desti Alannora; Suwilo, Saib; Mardiningsih
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11602

Abstract

Let G G (n, p) be a graph on n vertices where each pair of vertices is joined independently with probability p for 0 < p < 1 and q = 1 p. In this work, we introduce weighted random graf G with exponential distribution and investigate that the probability that every vertex of G has degree at most np + b√pqn is equal to 0.595656764.

Page 39 of 120 | Total Record : 1196

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