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Bulletin of Data Science
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 28079493     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
Bulletin of Data Science journal publishes manuscripts within the fields of: 1. Soft Computing, 2. Experts System, 3. Decision Support System, 4. Cryptography, 5. Big Data, 6. Data Mining, 7. Artificial Inteligence, and etc
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 22 Documents
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Sistem Pendukung Keputusan Dalam Penentuan Kinerja Tenaga Pendidik Terbaik Menerapkan Metode MOORA Sri Wulan; Elsa Pratiwi; Mesran Mesran; Desyanti Desyanti
Bulletin of Data Science Vol 1 No 2 (2022): Februari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The performance of educators at a university is a real behavior that is displayed by each educator as the work performance produced by the educators according to their role. To be able to determine the quality of the performance of educators, it is necessary to have clear criteria, therefore it is needed a decision support system (DSS) to overcome these problems. DSS is a Multi Objective Optimization Method on The Basis of Ratio Analysis (MOORA) method that has a high degree of flexibility and easy to understand in separating the subjective part of an evaluation process into weighted criteria decisions with several attributes of decision making. This method has a degree of goal selectivity from conflicting criteria. Where the criteria can be assessed as beneficial and unfavorable (cost). So this method has a good level of selectivity in determining the highest A1 with an optimization value of 3.059
Penerapan Metode Operational Competitiveness Rating Analysis (OCRA) Dalam Keputusan Rekomendasi Mutasi Jabatan Karyawan Surya Sintamie Hasibuan
Bulletin of Data Science Vol 1 No 1 (2021): Oktober 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Position in a company is a level that is very influential on the value of responsibility for the work that must be done to achieve a mission that is targeted by the company. Giving certain positions to employees in a company must of course be based on benchmarks that are the provisions of the leadership of the company. The problems that occur in PT. Wira Agung's creation to carry out the employee job transfer process is the difficulty in making real decisions as expected because the assessment process for employees who will undergo a job transfer is objective. To solve this problem, the author builds a visual-based decision support system using the Visual Basic Net 2008 programming language by applying the Operational Competitiveness Rating Analysis (OCRA) method. The results of this study are expected to be a solution for recommendations for employee transfers at PT. Kreasi Wira Agung.
Sistem Pakar Mendiagnosa Penyakit Pneumonia Menggunakan Metode Constraint Satisfaction Problem (CSP) Wirda Ayu Putri
Bulletin of Data Science Vol 1 No 1 (2021): Oktober 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

At this time the use of computer technology has grown rapidly among the community. Most people use it not only for commercial purposes, but also to get information on disease detection quickly and efficiently with computer-based applications that can help the general public to find out the causes and symptoms of the disease. For that, we need a system that is designed to be able to imitate the expertise of an expert in answering questions and solving a problem in accordance with the knowledge of an expert that is entered into a computer system. The development of artificial intelligence technology that has occurred has allowed expert systems to be applied in detecting diseases using programming languages. One of them is in providing information about various problems, especially pneumonia. The expert system method used is Constraint Satisfaction Problem (CSP) which is used to deal with uncertainty in the diagnosis of pneumonia. With the facilities provided to the user, it allows the user to use this system according to their respective needs. Users are given the convenience of knowing information about the symptoms of pneumonia, and its prevention.
Penerapan Algoritma C4.5 Dalam Memprediksi Kebutuhan Pembibitan Pohon Helmida Br. Manik
Bulletin of Data Science Vol 1 No 1 (2021): Oktober 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

A tree nursery is a place that is managed and designed to produce tree seedlings that are raised in good conditions until these seedlings are ready for planting. These tree nurseries can be small-scale informal nurseries or large commercial enterprises. Nurseries vary in size, facilities (supply, equipment, supplies, etc.), type of seed produced, and operations. Nurseries also have significant differences in the quality and quantity of stock of planting material produced. However, the primary goal of all nurseries is to produce sufficient quantities of high quality seed to meet the needs of seedling users. Seed users include the nursery operators themselves, individuals, organizations, communities, farmer groups, government agencies, non-governmental organizations, companies, or private consumers. The problems that have been experienced so far at the North Sumatran Forestry Service to determine seedling are still ineffective because determining the annual tree nursery is still very difficult, so to overcome this problem, the C4.5 algorithm is applied in predicting nurseries at the North Sumatra Forestry Service because of predictions. is a process of systematically estimating something that is most likely to happen in the future based on past and present information that is owned, so that the error (difference between something that happened and the predicted result) can be minimized. Prediction does not have to provide a definite answer to events that will occur, but seeks to find answers as close as possible to what will happen. The C4.5 algorithm is an algorithm that is used to produce a decision tree that is able to classify an object. C4.5 represents concepts in the form of a decision tree. The rules generated by C4.5 have a hierarchical relationship like a tree (having roots, points, branches, and leaves). Some call the structure of the model generated by C4.5 a decision tree while others call it a rule tree. Where in the process of working on the C4.5 algorithm, it calculates the gain and entropy values ​​for the data attributes that have been presented by the previous database. From the classification process and the results obtained are described in the form of a decision tree and based on the decision tree, new information comes from the previous database in the form of rules or rules private consumers
Identifikasi Patah Tulang Tangan Manusia dengan Menerapkan Metode Hue Saturation Value (HSV) Hendra Giovani
Bulletin of Data Science Vol 1 No 1 (2021): Oktober 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

In identifying broken bone integrity, generally due to trauma. One of the methods used to identify fractures is to look at the picture of the fracture through X-rays or X-rays. Then, it is analyzed manually by a Radiologist. Radiologists often have difficulty in reading X-rays, the presence of faults that cannot be seen by the naked eye and the image quality that contains a lot of noise. And accompanied by the condition of the Radiologist's eyes that are tired after seeing a lot of X-ray images of bones can produce a high level of subjectivity. The level of subjectivity that is meant is the level of differences in observations on X-ray images. For this reason, an approach is needed that can assist radiologists in identifying the location of fractures. This study identifies the ribs of the human hand using the HSV (Hue Saturation Value) method with the aim of classifying the color contrast segmentation that is closest to the way the human eye works and combining information, both color and grayscale (digital images that only have one channel value in each pixel), in other words the value of the RGB portion of an image of a hand fracture
Perancangan Aplikasi Pengenalan Objek 3D Komponen Komputer Menggunakan Augmented Reality Berbasis Android Rasidin Rasidin
Bulletin of Data Science Vol 1 No 1 (2021): Oktober 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Weak knowledge of computer scholars about the components of the preparation of computers often become a joke in the world of work. There are not many programmers and designers who do not know computer components, even though their interactions at the computer are above the average normal use. Augmented reality is a way to combine virtual worlds (virtual environment) into the real world (reality environment) by utilizing the camera in real time. This technique can help display the shape of objects in three-dimensional computer components into the real world. Text Recognition is a detection of writing into a computer system. The application of text recognition to the Augmented Reality technique can detect text as well as project objects of 3 dimensional components of computer components. This certainly makes it easier for users to find out computer components just by using text.
Teknik Klasifikasi C4.5 Dalam Menentukan Faktor Utama Kepuasan Nasabah Terhadap Pelayanan Klaim di PT Asuransi Central Asia Pematangsiantar Muhammad Syahputra; Agus Perdana Windarto; Riki Winanjaya
Bulletin of Data Science Vol 1 No 1 (2021): Oktober 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Insurance claims can be made in accordance with important provisions in claim submission, such as claims in accordance with those stated in the policy, the policy is still valid (inforce), the policy is not in the waiting period and the claim is included in the coverage. Data Mining is a computer-aided process to explore and analyze large amounts of data sets and extract information and knowledge. Decision Tree is one of the Data Mining sections, with C4.5 algorithm is one of the classification methods that use decision tree representations where each nodes present attributes, branches represent the values ​​of attributes, leaves represent classes. and can be used to find dominant factors to find a decision, one of which determines the main factors of customer satisfaction with service claims at PT. Insurance Central Asia Pematangsiantar. It is hoped that the results will later be able to contribute greatly to PT. Insurance Central Asia Pematangsiantar in providing the best service to existing customers
Klasifikasi Calon Nasabah Baru Menggunakan C.45 Sebagai Dasar Pemberian Pertanggungan Asuransi di PT Asuransi Central Asia Pematangsiantar Retno Ayu Syahfitri; Agus Perdana Windarto; Harly Okprana
Bulletin of Data Science Vol 1 No 1 (2021): Oktober 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The problem that often arises in insurance problems is the number of customers who are in arrears in paying premiums, therefore a system is needed that can classify which prospective customers are in the eligible group and which customers are in the unfit group in submitting as insurance customers. so that the insurance company can solve the problem early. In this study, an information system for the classification of acceptance of prospective insurance customers was built using the Classification Tree C4.5. Classification tree C4.5 is used to generate the rules needed for the smooth classification process of customers in paying premiums and is formed from the conversion result of the construction of a classification tree (classification tree). The C4.5 algorithm is considered an algorithm that is very helpful in classifying data because the characteristics of the classified data can be obtained clearly, both (decision tree) and in the form of rules or If - then rules, making it easier for users to extract information on the data in question
Penerapan Algoritma Maximum Marginal Relevance Dalam Peringkasan Teks Secara Otomatis Ade Kurniawan; Mohd Irsan Humaidy
Bulletin of Data Science Vol 1 No 2 (2022): Februari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The search engine is a device for searching information from available documents. But the search engine will give you a lot of search results, so to find a document we have to open a meeting. Text summarization allows us to get key information from a document quickly without requiring us to read the contents of the document manually.One of the methods used is Maximum Marginal Relevance (MMR). MMR belongs to the extractive summary category (choosing the sentence in the document as the main sentence of the document content). MMR is done by weighting each sentence in the document.It is hoped that with the application of the Maximum Marginal Relevance Method this automatic summary of text can reduce the level of data redundancy and can help readers understand the meaning of the summary results and provide good information
Penerapan Algoritma Text Mining dan Lexrank dalam Meringkas Teks Secara Otomatis Ahmad Fauzi
Bulletin of Data Science Vol 1 No 2 (2022): Februari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The growth of media and online news has allowed writers to automate research in the field of text summarization. News that offers a quick and concise concept, but in reality digital news is not organized and it takes so long to find the essence of the news. Document summarization is an effective way to get information from a document without reading the entire document. However, document summaries for Indonesian are still relatively small compared to other languages. This study develops document summarization automatically using a graph-based method, namely the Lexrank Algorithm which can be proven by research that has been tested using Indonesian news data obtained from liputan6.com. The number of sentences extracted is 25%-50% of the total sentences in the document. The results of the Lexrank summary in order of the highest weight order are = D2 = 1,433, D10 = 1,289, D3 = 1,253, ….. D8 = 0.673. The largest value from the summary will be arranged according to the order of words so as to get the summary of the news.

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