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Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB
Published by Universitas Pelita Bangsa
ISSN : 24073903     EISSN : 28291891     DOI : https://doi.org/10.37366/sigma.v16i1
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB merupakan jurnal ilmiah yang diterbitkan oleh Program Studi Teknik Informatika Universitas Pelita Bangsa (UPB) Cikarang dengan no p-ISSN 2407-3903 (Media Cetak). Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB adalah sebagai salah satu wadah publikasi bagi dosen-dosen yang memiliki penelitian ilmiah di bidang Teknik Informatika, Ilmu Komputer, Sistim Informasi, Artificial Inteligent, Data Mining, Image Processing, Rekayasa Perangkat Lunak. Setiap artikel yang diterbitkan oleh Jurnal Ilmiah SIGMA: Informatics Engineering of UPB telah melalui proses review dan editorial yang ketat serta menghormati ketentuan hukum hak cipta, privasi, dan etika publikasi ilmiah. Jurnal Ilmiah SIGMA : Information Technology Journal of UPB terbit dua kali dalam setahun, yaitu bulan Maret, Juni, September dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 10 Documents
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Search results for , issue "Vol 11 No 2 (2020): Juni 2020" : 10 Documents clear
Mencegah Kredit Macet Dengan Analisa Kelayakan Pembiayaan Dengan Metode C4.5 Dan Naïve Bayes (Studi Kasus : Koperasi BMT UGT Sidogiri Cabang Cikarang) Agung Nugroho
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The progress of the growth of MSMEs (Micro, Small and Medium Enterprises) in Indonesia from time to time which is increasingly rapid, resulting in an increase in the need for capital to develop their business. This is evidenced by the increasing number of credit or financing withdrawals from savings and loan cooperatives and BPRs (Rural Banks). The problem faced by savings and loan cooperatives, BPRs, or other financial institutions at this time in providing credit is the risk of late payments, repayments and even failure of credit payments. This problem occurs due to credit misuse and weak supervision both in the process of providing credit and in the implementation stage. The right solution to solve existing problems is by using data mining algorithms. The concept of data mining will make it easier to solve problems that are not optimal in cooperatives, the classification method is able to find models that differentiate concepts or data classes with the aim of making it easier to predict creditworthiness. The Naive Bayes algorithm and the C4.5 algorithm are considered to be able to predict future opportunities based on previous experiences. The author conducted research on the BMT UGT Sidogiri Cooperative with the title "Preventing bad credit by analyzing the feasibility of financing with the Naive Bayes and C4.5 methods". In this study the authors used 9 attributes as an assessment, namely: name, residence status, financing contract, income, ceiling, term of repayment, number of dependents, collateral. Testing is done using 520 data and 104 randomly selected testing data. From the results of tests carried out using Rapid Miner tools, it can be concluded that the accuracy level of the C4.5 algorithm is more accurate at 81.35%, while the Naive Bayes algorithm is 78.85%. Keywords : Credits, Classification, Accuracy, Naive Bayes, C4.5.
Sistem Pendukung Keputusan Penilaian Kinerja Guru Terbaik Pada SMA Negeri 1 Telukjambe Barat Menggunakan Metode Analytic Hierarchy Process (AHP) Arif Siswandi
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

In line with this global era, with the rapid development of technology the need for information is needed. Moreover, the information generated contains true, accurate, fast and precise values. Problems that often occur in the teacher performance appraisal process include the subjectivity of decision making, especially if some teachers have responsibilities that are not much different. Decision support system is a decision making process assisted by using computers to help decision making by using certain data and models to solve some unstructured problems. While the Analytic Hierarchy Process (AHP) is a method or tool in multi-criteria decision making using the help of Expert Choice Ver.11 software. the criteria used as a benchmark in determining the assessment of the best teacher performance at SMAN 1 Telukjambe Barat are: Responsibility, Discipline, Diligent, Friendly. From this study found that responsibility is a priority or is preferred at SMAN 1 Telukjambe Barat from the 19 teachers Maya has far better responsibilities and meets the criteria to be the best teacher compared to other teachers. Keywords : Decision Support System (SPK), Analytic Hierarchy Process (AHP), Expert Choice Ver.11., The best teacher
Analisis Sentimen Terhadap Operator Seluler Telkomsel Menggunakan Algoritma Naïve Bayes Candra Naya
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The use of social media in the era of globalization is very necessary for all people including Telkomsel cellular operators, Telkomsel uses Twitter as a promotional media. However, the use of Twitter as a medium for promotion of Telkomsel received various compliments of input and criticism and in this case the authors conducted research to analyze Telkomsel user sentiment. And in this study the authors used the Naïve Bayes algorithm to classify sentiments and look for preference values. From the results of tests conducted using cross validation techniques and accuracy measurements using confusion matrix with 10 times the best accuracy testing obtained was 85.33 % and the positive response obtained from the calculation of preference value was 37.03 %. It can be concluded that the Naïve Bayes algorithm can be used to classify quite well and be able to measure user responses. Keywords : Twitter, Sentiment Analysis, Naïve Bayes Classifier, Cross Validation, Preference Value
Analisis Data Mining Menggunakan Algoritma Naïve Bayes Dalam Memprediksi Pembelian Material Plastik Injection (Studi Kasus: PT. Surya Technology Industri) Muhtajuddin Danny
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

To facilitate every decision making in the process of purchasing plastic injection material in the sales department of PT. Surya Technology Industri, which has not been controlled with production or sales to customers, resulting in too much stock and cannot be sold. PT. Surya Technologi Industry, which is engaged in Manufacturing, has more than 400 types of raw materials so that companies find it difficult to predict future needs and what the company needs. The aim of this research is to analyze the data for purchasing plastic injection materials for more accurate and efficient results. Data mining techniques with the Naïve Bayes algorithm method are used in this study to classify so as to produce decisions with probability values and useful rules as input in determining the decision-making process. Of the 1120 datasets on the purchase of plastic injection material, testing was carried out ten times, the distribution of the test with different training data and testing data with the provisions of 10% test data and 90% training data. Based on the results obtained, it shows that the Naïve Bayes algorithm in classifying data on the purchase of plastic injection materials using the Rapid Miner tools has the highest accuracy, precision and recall values, namely testing at the proportion of 90% (1008 data) training and 10% (112 data) testing using cross validation 10-fold with 88.93% accuracy, 92.88% precision and 87.77% recall. This shows that the Naïve Bayes algorithm has a fairly good performance in making predictions so that it can be implemented for the decision- making process for the company. Keywords : Naïve Bayes Algorithm, Data Mining, RapidMiner, Classification
Pemanfaatan Sistem Pendukung Keputusan Untuk Penentuan Alokasi Dana Kegiatan Berbasis Web Menggunakan Metode Object Oriented Analisis Design Dan Unified Modeling Language (Studi Kasus SMK Negeri 1 Cikarang Utara) Muhamad Fatchan
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The development of technology in the current era runs very rapidly, this is evidenced by the many uses of the internet network in various communities today. The use of computers has evolved from merely processing data or presenting information to management, to being able to provide choices as a decision support tool for management. Computer-based information systems (Computer Based on Information Systems), one of which is a Decision Support System (Decision Support System), which is an interactive computer information system that can provide alternative solutions for decision makers. At SMK N 1 Cikarang Utara the process of submitting an activity proposal has not been computerized and does not yet have a decision support system for determining the allocation of activity funds. So it must take a long time to verify the proposed activity proposal. The development of information technology has enabled decision makers to be done more quickly and accurately. So as to make decisions more quickly, carefully avoid and reduce the subjectivity of the resulting decisions needed a decision support system that aims to facilitate the process of verifying the proposal of activities and determination of activity funds for student activity units through the process of determining the feasibility of activities and allocation of funds given to carry out activities the. To get a solution to the problem of submission of proposals so that only incoming proposals that are in accordance with the criteria specified by the School Principal so that there is no prolonged revision process and no difficulty in processing proposal data, a website- based decision making system is designed. data collection methods using interview, observation and literature study methods, while in the design of information systems the author uses the Object Orientied Analyst Design "OOAD" method using Unified Modeling Language (UML) software that was built using PHP and MySQL programming languages as the database. The new system can maximize the work of treasurers and principals in delivering accurate information and administrative services effectively and efficiently. Keywords : Website, Decision Making System, Proposal, OOAD, UML
Sistem Pendukung Keputusan Karyawan Terbaik Dengan Metode Profile Matching Best Employee Decision Support System With Matching Profile Process Method Yoga Religia
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Promising human resources can support the advancement of a company. Human resource development must also have clear and well-planned rules. To maintain good resources and produce promising resources, management planning is needed, for example in the form of hiring new employees, conducting training, performance appraisal, etc. The process of selecting the best employees at PT Samudera Ocean Perkasa Indonesia which is still manual and accompanied by decision making takes a long time. So as to simplify the process of selecting the best employee recommendations, it is very necessary to build a decision support system so that it can help to provide the best employee selection recommendations. In this study the problem was formulated about how to implement the profile matching method for the selection of employees in PT Samudra Ocean Perkasa Indonesia. While the aim of this research is to choose the best employees in PT Samudra ocean mighty Indonesia to be more targeted. The result of this application is the system automatically recommends the best employees, and testing this system using a blackbox, and after use the blackbox system is ready to use. Keywords : decision support system, Profile Matching, php.
Penerapan Data Mining Menggunakan Metode Algoritma Naive Bayes Untuk Menentukan Kelayakan Kredit Rumah Bersubsidi Muhammad Makmun Effendi
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Data mining has been implemented in various fields, including business, education and telecommunications. In the business sector, for example, the results of implementing data mining can help in making decisions about the feasibility of subsidized home loans. In determining the feasibility of subsidized home loans, PT. Gernis Pratama Properti conducts an analysis so that it can be determined whether the subsidized home loan process can be approved or not. Currently there are several obstacles in the assessment process, namely the inaccurate results of the decision at interview stage 1 in the company as an initial stage of the consumer eligibility process. Naive Bayes Algorithm Method is an algorithm found in the classification technique that uses a simple probability method based on the theory of infants with high independent assumptions. The process carried out in this study uses Rapid Miner tools to process data with the Naive Bayes algorithm, from the tests carried out it produces an accuracy of 96.23%. With the application of the Naive Bayes method, it uses data to produce the probability of each criterion for different classes, so that the probability values of these criteria can be optimized to determine the eligibility of "Eligible" and "Eligible" subsidized home loans quickly and efficiently based on the classification made by Naive Bayes method. Keyword : Creditworthiness of subsidies ,Data Mining, Algorithm Naive Bayes.
Rancang Bangun Aplikasi Edukasi Sebagai Media Pembelajaran Mengenal Tanaman Untuk Anak Usia Dini Menggunakan Augmented Reality Berbasis Android Edora Edora
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

One of the most common knowledge taught to children is art with a variety of materials such as knowing plants. At present the introduction of plants at an early age still uses picture books and explanations explained by teachers. With Augmented Reality (AR) supported by the markerless method. Users don’t need a special marker in the form of black and white, but use 2D images that are presented in the form of magic cards by the author as a reference to issue 3D objects. In this study several devices with different specifications are used to test whether this application can run well or not. From the results of this study that the marker can be read with a smartphone camera with a response time to detect the marker of approximately 1 second. The minimum distance to detect the marker is 20 cm and the maximum distance is 100 cm. For an optimal distance of 30 cm. The minimum angle for marker detection is 30o and the maximum angle is170o. For an optimal angle of 45o-60o. Keywords : : Learning Media, Augmented Reality, Marker, Markerless, Android, Unity 3D
Penerapan Algoritma Naive Bayes Untuk Menentukan Klasifikasi Produk Terlaris Pada Penjualan Pulsa Wahyu Hadikristanto
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

This research is motivated by the progress of the development of communication technology and information is very fast and increasingly cheap so that makes the community for mobile phone pulses become a mandatory requirement at the presente time. Of various pulse products available at the counter RA Cell Pulses Tekomsel, Pulses XL, Pulses Indosat, and Pulses 3 the autors classify as bestseller and non-sellers. The goal is to find out the implementation of data mining using the Naive Bayes algorithm in determining the classification of best-selling products and the result of the accuracy of the data in the sales of pulses. By collecting 600 data into 480 training data and 120 testing data. Data mining is a form of extracting data in classifying a large amount of data, using the RapidMiner application and the Naive Bayes algorithm is a classification method that is widely used because of its simple and high accuracy in classifying data. Based on the result of researh that has been done, the type of product that is most restricted to the sale of pulses by product name is Telkomsel Pulses. The level of classification accuracy with the naive Bayes methodproduces an accuracy value of 97,50%, a precision value of 100%, and a recall value of 93,48% so the Naive Bayes method is good method in this study. Keywords :Pulses, Classification, Data Mining, Naive Bayes
Sistem Pendukung Keputusan Penentuan QCC Terbaik Dengan Metode AHP Pada PT. Century Batteries Indonesia Nurhadi Surojudin
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Selection of the Best QCC Group is giving recognition to the best QCC group who actually and extraordinary do Quality Control System activities by making changes that can increase the effectiveness and efficiency of work or production. The selection of the Best QCC Group of PT Century Batteries Indonesia is held annually. In the Best Group assessment process, PT. CBI appointed an assessment team to conduct an assessment of the QCC group. However, the assessment process is still done manually so it takes a long time to process the data. In addition, the assessment is still subjective and not yet relevant to the actual situation. Based on this, in this study a decision support system was built to be used to select the best QCC group selection process at PT Century Batteries. Decision support system built based on web using the programming language PHP and MySQL as the database. The decision making method used is Analytical Hierarchy Process (AHP). This method is used to determine the weight value of each criterion, which is then carried out by a ranking process to determine the best alternative from a number of alternatives. The test carried out in this study is functional testing with the black box testing method. The test results show that the system can run properly according to its function.. Keywords: Analytical Hierarchy Process (AHP), Decision Support System

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