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Journal of Soft Computing Exploration
Published by shm publisher
ISSN : 27467686     EISSN : 27460991     DOI : -
Core Subject : Science,
Computer Science & IT
Journal of Soft Computing Exploration is a journal that publishes manuscripts of scientific research papers related to soft computing. The scope of research can be from the theory and scientific applications as well as the novelty of related knowledge insights. Soft Computing: Artificial Intelligence Applied Algebra Neuro Computing Fuzzy Logic Rough Sets Probabilistic Techniques Machine Learning Metaheuristics And Many Other Soft-Computing Approaches Area Of Applications: Data Mining Text Mining Pattern Recognition Image Processing Medical Science Mechanical Engineering Electronic And Electrical Engineering Supply Chain Management, Resource Management, Strategic Planning Scheduling Transportation Operational Research Robotics
Arjuna Subject : Ilmu Komputer (semua kategori) - Perangkat Lunak
Articles 13 Documents
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Search results for , issue "Vol. 2 No. 2 (2021): September 2021" : 13 Documents clear
Car insurance segmentation prediction based on the most influential features using random forest and stacking ensemble learning Etna Vianita; Adi Wibowo; Bayu Surarso; Aris Puji Widodo
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.39

Abstract

In addition to financial transaction services, the Bank also provides insurance services by conducting regular campaigns to attract new customers such as car insurance based on market segmentation, which is one of the main aspects of marketing used in financial services based on demographic data. One way to analyze the market is to predict the likely target market based on the campaign's target demographic data. Therefore, this study aims to find the best classification method for predicting campaign targets using historical data from 4000 customers of a bank in the United States. The market segmentation analysis process uses the best feature selection and ensemble learning. The best feature selection is selected using important features for Random Forest. The ensemble learning used is a stacking model consisting of the basic model of Logistic Regression, Support Vector Classifier, Gradient Boosting, Extra Tree, Bagging, Adaboost, Gaussian Naive Bayes, MLP, XBoost, LGBM, KNeighbors, Decision Tree, and Random Forest. The accuracy results of the stacking model can exceed the accuracy of the basic model with an accuracy rate of 78.80%.
New fuzzy transportation algorithm without converting fuzzy numbers Muhammad Sam'an; Yahya Nur Ifriza
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.41

Abstract

The ranking function is widely used to convert fuzzy numbers to be crisp on solving fuzzy transportation problems. The converting process can indeed make it easier to play the fuzzy transportation method, but from the convenience, it causes failed in interpreting the results of converting fuzzy numbers. This is because the converting process of fuzzy numbers still has subjectivity values, so it cannot be eliminated, moreover, the ordering can cause incompatible input and output fuzzy numbers resulted. Therefore, the new fuzzy transportation method is proposed by fuzzy Analytical Hierarchy Process to order fuzzy parameters on fuzzy transportation problem without converting fuzzy numbers to crisp numbers, then Algorithm 2 until 6 is used to obtain a fuzzy optimal solution. The advantages of the new proposed method can improve the shortcomings of the existing methods, as well as relevant to solve fuzzy transportation problems in real life
Performance comparison of support vector machine and gaussian naive bayes classifier for youtube spam comment detection Yahya Nur Ifriza; Muhammad Sam'an
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.42

Abstract

Youtube is a video sharing site that was begun back in 2005. Youtube produces over 400 hours of substance each moment and more than 1 billion hours of substance are devoured by clients every day. In this work, we present a new approach by comparing the analysis results using a support vector machine and the Gaussian Naive Bayes classificatio. Our proposed methodology We used the dataset from UCI especially Youtube-Shakira for training and testing. The transformed dataset is split into training and testing subsets and fed into Naive Bayes and Support Vector Machin. In all cases, the F1 score was used to evaluate the classifier's performance. The results of the experiment are displayed in Gaussian Naive Bayes with an F1 score of 84.38% and a Support Vector Machine (SVM) with an F1 score of 88.00%. Naive Bayes is consistently the worst performer than SVM.
Decision support system for choosing the best tourist attractions using simple additive weighting (SAW) method Alya Aulia Nurdin
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.43

Abstract

Every year, various regions in Indonesia always have many tourists both local and foreign so as to provide benefits for the government and the surrounding local community. However, due to the Covid-19 pandemic, the tourism sector has slumped. Therefore, to revive the tourism sector in the new normal due to Covid-19, there needs to be various considerations. One of them, namely decision support system for choosing tourist attractions with facilities that meet health protocol standards in the new normal/adaptation of new habits. In this study, a case was raised with the aim of choosing the best tourist attractions in Kendal Regency, Central Java with several criteria determined, especially regarding facilities that comply with health protocols. The calculation in this study was done by Simple Additive Weighting (SAW) method. The research was conducted by determining alternatives, criteria, and weight values on each criterion. Then the calculation of the value of preferences and stamps to get the best alternative. From the calculations that have been done, the result of the best tourist attractions in Kendal is Tirto Arum Baru with a preference value of 0.766. However, due to the dynamic nature of the criteria and weight data, it is possible that at any time the selected data may change.
Simulations of text encryption and decryption by applying vertical bit rotation algorithm Dwika Ananda Agustina Pertiwi; Djuniadi Djuniadi
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.44

Abstract

Cryptography is the study of hiding text and numbers in the form of codes. Vertical Bit Rotation (VBR) is one of the most widely implemented cryptographic algorithms as a one-way hash function that simplifies the encryption process with a high degree of difficulty in decryption. The purpose of this study is to apply VBR hash algorithm modeling to binary value characters with bit rotation keys 10, 11, 7, 3, 2, 7, 5, and 4. Thus, generating a passcode. The results of the encryption simulation show the code in the form of letters and characters, then the result of the decryption with the opposite rotation to the encryption process returns the value from ciphertext to plaintext based on ASCII characters. Cryptographic algorithms are applied to avoid cryptanalytic experiments in opening encryption codes.
Factors affecting interest in utilization and use of online shop (study on shopee customers) Sayidah Rohmatul Hidayah; Chyntia Eka Putri
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.45

Abstract

The development of information technology has led to the emergence of various e-commerce services. One of them is engaged in the mobile marketplace, namely Shopee. Shopee as a mobile marketplace is always faced with competitors. Therefore, this study aims to determine the factors that influence the interest in the use and use of the online shop, especially the Shopee application. In this study, the UTAUT2 framework was used, where this framework is a framework that is often used to determine user intentions and behavior in using technology or applications. The UTAUT2 framework has seven main constructs and in this study one construct is added, namely trust. The results of this study indicate that the UTAUT2 framework with additional trust constructs has a positive regression weight for all UTAUT2 constructs and additional trust constructs except for the effort expectancy and hedonic motivation constructs. This shows that all UTAUT2 constructs and additional trust constructs have a positive effect on the intention to use the Shopee application when shopping online except for the effort expectancy and hedonic motivation constructs. Intention to use also has a positive effect on user behavior to use the Shopee application when shopping online.
Improvement business process model and notation on the drink distribution industries using six core element Oktaria Khoirunnisa; Dwika Ananda Agustina Pertiwi; Erika Noor Dianti; Ahmad Maulana Malik Fattah; Kholiq Budiman
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.46

Abstract

The development of distribution and market segmentation has become the company's background in improving business processes. The purpose of this research is to analyze the business processes of beverage companies using Business Process Management (BPM) modeling and improvised based on six core element management. In the analysis process, it is found that there is no stock forecasting system in forecasting sales stock that must be fulfilled. The results of the study show that the Business Process Management model is improved with the addition of a stock forecasting system, so that business processes become more controlled with the presence of a product stock inventory forecasting system in the company.
Analysis and development of company business processes using business process model notation (case study of PT Datacomm Diangraha) Ryanis Naufalia; Sahda Armandiva Usman; Cholilah Lateefa Bambang
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.48

Abstract

Companies in supporting activities that can achieve competitive advantage require a description of the right activities or commonly called business processes. To evaluate existing business processes so as to improve business productivity performance, every company needs to conduct business process analysis so that it is easy to understand the ongoing business processes and can improve them if needed. An important stage of business process analysis is modeling. The purpose of writing this journal is to identify business processes at PT Datacomm Diangraha and make modeling of ongoing business processes (As-Is Model). The Business Process Model Notation (BPMN) method which is a technique or method for understanding, designing and analyzing a business process is used in this research. This study uses observation, interviews and literature review to obtain data. The results obtained are the business processes at PT Datacomm consisting of the contract making process, the work design submission process, the process of paying service fees in stages (30%, 60%, 10%), providing a guarantee period, and customer service and process improvement.
Laptop selection decision support system according to buyer criteria with the simple additive weighting method Nur Hazimah Syani Harahap; Afifah Zahraini
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.49

Abstract

Along with the development of increasingly modern times, so that all activities require gadgets, including laptops. However, it is often found among prospective laptop buyers who are still confused in determining a laptop to suit their needs, for that purpose the purpose of this study is to help people who want to buy a laptop when choosing or who are looking for a laptop to get the right one for their needs. To achieve this goal, a decision support system is needed. The Decision Support System that will be used is the SAW (Simple Additive Weighting) method because this method can filter out several existing alternatives and based on predetermined criteria so that later you get the best alternative. By using this SAW method, a matrix normalization process is needed, the weight value of each attribute, and finally a ranking process that will determine the optimal alternative. The results obtained in this study are to be able to provide laptop advice to prospective buyers based on the specifications of the prospective buyers' needs and with a 100% accuracy level based on calculations from the decision support system.
Usefulness factors to predict the continuance intention using mobile payment, case study: GO-Pay, OVO, Dana Cholilah Lateefa; Ryanis Naufalia; Danendra Yassar
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.50

Abstract

The advancement of information technology continues to grow in line with the increasing years. The benefits gained from the advancement of information technology make all aspects of human life today can not be separated from information technology and also ikut encouragethe emergence ofinnovations in thedevelopment of informationtechnology, sepertinya payment is no longer conventionally nal but with mobile payment. This study aims to find out what useful factors influence the continuation of the intention to use mobile payment in the go-pay, OVO, and DANA case studies. Analysis of factors that influenced this study include: Computer Self Efficacy (CSE), Enjoyment (E), Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Confirmation (CON), Perceived Value (PV), Technical System Quality (TSQ), Satisfaction (SAT),and Continuance Intention (CI). This study uses random sampling techniques by collecting data utilizing google form containing 45 statements using five Likert-scale distributed online. The sample used in this study was 117 respondents. The statistical analysis techniques used in this study are Structural Equation Modeling (SEM) and use SMARTPLS 3.0 application as a tool to analyze the data. The results obtained are that Computer-Self Efficacy (CSE), Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) has no significant effect on Continuance Intention (CI). While Satisfaction (SAT), has a significant influence on Continuance Intention (CI).

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