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Bulletin of Informatics and Data Science
Published by Asosiasi Peneliti Data Science Indonesia
ISSN : -     EISSN : 25808389     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Bulletin of Informatics and Data Science journal discusses studies in the fields of Informatics, DSS, AI, and ES, as a forum for expressing research results both conceptually and technically related to Data Science
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
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Search results for , issue "Vol 1, No 1 (2022): May 2022" : 5 Documents clear
Penerapan Metode Preference Selection Index (PSI) Dalam Penerimaan Staff IT Widya Indah Safitri; Mesran Mesran; Sarwandi Sarwandi
Bulletin of Informatics and Data Science Vol 1, No 1 (2022): May 2022
Publisher : PDSI

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Abstract

In a company or agency, employees are one of the keys to success in achieving certain goals in the company. However, getting the right IT staff and in accordance with what the company or agency wants is certainly not easy. Therefore, to get employees who meet expectations and fulfill all stages carried out by the company, it is necessary to select the right employee candidates so that later it will produce competent IT staff in their fields. The Preference Selection Index (PSI) method is a method for solving multi-criteria decision making (MCDM). This method is useful when there is a conflict in determining the relative importance between attributes. From the results of the study, it was obtained that alternative A9 was the best alternative to be chosen as the company's IT staff with the highest score of 0.9624
Klasifikasi Citra Tanaman Perdu Liar Berkhasiat Obat Menggunakan Jaringan Syaraf Tiruan Radial Basis Function Rohmat Indra Borman; Imam Ahmad; Yuri Rahmanto
Bulletin of Informatics and Data Science Vol 1, No 1 (2022): May 2022
Publisher : PDSI

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Abstract

Wild plants or what are usually called weeds are plants that are considered harmful because they grow in unwanted places. But it turns out that some wild plants have many benefits for the health of the human body. Wild plants have many forms of vegetation, one of which is often encountered is shrubs. There are many wild herbaceous plants that are efficacious as medicine. However, most of the people who do not have knowledge about the types of wild shrubs that have medicinal properties. This study aims to implement the Radial Basis Function (RBF) algorithm for the classification of wild herbaceous plant species with medicinal properties by extracting color and texture features. The color feature extraction is based on the average RGB value, while the texture feature extraction uses a Gabor filter with the mean, entropy, and variance parameters of the magnitude image. The result of feature extraction becomes input data which will be managed by the RBF artificial neural network. RBF is a neural network that has three layers that have feedforward properties that can assist in solving classification or pattern recognition problems. Based on the test results, the precision value is 91%, recall is 89% and accuracy is 90%. These results show that the Radial Basis Function (RBF) algorithm with color and texture feature extraction can classify wild shrubs with medicinal properties well.
Analisis Metode K-Medoids Cluster Dalam Mengelompokkan Siswa Yang Berprestasi Indri Fatma; Heru Satria Tambunan; Fitri Rizki
Bulletin of Informatics and Data Science Vol 1, No 1 (2022): May 2022
Publisher : PDSI

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Abstract

Cluster analysis of outstanding students using data mining, namely the K-Medoid Cluster Algorithm. Previously, the school still used the manual method in determining students who excel at the school, so it took a long time and the results were not accurate. K-Medoid Cluster is one of the algorithms used for data classification or grouping, the authors apply the K-Medoid Cluster algorithm in grouping students with high achievement in order to get more accurate, fast, and effective results.
Sistem Pendukung Keputusan Pemilihan Pegawai Honorer Kelurahan Medan Sinembah Menerapkan Metode ROC dan MOORA Ketrin Munthe; T Razeki Aditya Syahputra; Azi Alfisya Pasuli; Muhammad Andika Hasibuan
Bulletin of Informatics and Data Science Vol 1, No 1 (2022): May 2022
Publisher : PDSI

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Abstract

An honorary employee is someone who works for a company that is eligible to be employed as a daily employee for a predetermined period of time and also with a definite salary from the company he works for. The problem experienced in this study is about the process of selecting honorary employees. The selection of honorary employees so far has only looked at education, even though in the process of selecting honorary employees several criteria must be used. The criteria in this study are Education, Age, Height, Distance from Home, Work Experience, Character and Test Values. From the problems encountered, it is very appropriate if the Medan Sinembah Village party implements a Decision Support System. The method used in this study is ROC and MOORA, this method was chosen because it is able to provide the best decision based on predetermined criteria where the best alternative is alternative A18 on behalf of "Andry" with a value of Yi = 0.328
Penerapan Metode Promethee Pada Aplikasi Penerima Kartu Keluarga Sejahtera (KKS) Azizah Azizah; Khairudin Nasution
Bulletin of Informatics and Data Science Vol 1, No 1 (2022): May 2022
Publisher : PDSI

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Abstract

The Prosperous Family Card or commonly referred to as KKS is a government program in poverty alleviation. This program is a development of the previous program called the Social Protection/Prosperity Card (KPS) which was implemented during the era of President Susilo Bambang Yudhoyono's administration. And therefore, to minimize the occurrence of errors in the selection of the community in getting the Prosperous Family Card (KKS), an application is needed that aims to simplify any related data processes. The method used is the Promethee method (Preference Ranking Oranization Method For Enrichment Evaluation). Promethee is a sequencing method for multi-criteria analysis. The criteria used are occupation, income, number of dependents, condition of the house and assets owned

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