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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 19 Documents
 1   2 
Implementasi Metode Weighted Aggregated Sum Product Assesment (WASPAS) dalam Pemilihan Oli Mesin Sepeda Motor 150 CC Juniar Hutagalung; Ahmad Fitri Boy; M Arief Yahdie
Bulletin of Informatics and Data Science Vol 1, No 2 (2022): November 2022
Publisher : PDSI

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Abstract

There are many types and types of engine lubricating oil, so you must be selective in choosing the right lubricant (oil) to preserve the life time of the engine. With the oil, the friction between the components in the engine becomes smoother and makes it easier for the engine to reach the ideal temperature. Oil is often used to reduce friction (friction), if two surfaces that are attached to each other move, friction will arise. If the engine heat is not absorbed, the wear and tear of engine components will accelerate. The purpose of this study is to implement a decision support system using the Weighted Aggregated Sum Product Assessment (WASPAS) method in selecting the best motorcycle engine oil so that it can assist motorcycle riders in choosing the best engine oil. Motorcycle owners do not experience difficulties and do not need a long time in the selection of engine oil for their motorcycles. The Waspas method can be applied in solving the problem of determining the best lubricant (oil) for 150cc sport motorbikes. The best lubricant (oil) based on the calculation results of 5 alternatives with a value above 0.60, namely deltalube daily with the highest score of 0.6906, repsol mx25 with a value of 0.6902, ahm oil mpx 2 with a value of 0.6644, federal ultratec with a value of 0.6238 and shell advance ax5 with a value of 0.6097. With the application of the desktop-based Waspas method in decision making, it can make it easier for motorcycle owners to select the best lubricant (oil) for 150cc sport motorbikes.
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
Prediksi Jumlah Sampel Tes PCR Covid-19 Menggunakan Metode Single Moving Average Nilam Fadhilah; Rachman Arief
Bulletin of Informatics and Data Science Vol 1, No 2 (2022): November 2022
Publisher : PDSI

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Abstract

Covid-19 has spread all over the world. This virus was first discovered in the city of Wuhan, China. To avoid this virus, the community has implemented several strategies such as wearing masks, washing hands and conducting swab tests to determine whether the results are contaminated with the Covid-19 virus or not. In Indonesia, swab tests have been provided, such as the Antigen swab test and the PCR swab test. However, WHO recommends a PCR swab test because the results are more accurate. Until now, Indonesia has not been able to meet the minimum number of PCR test samples according to the WHO (World Health Organization) version, which is 1 per 1,000 people every week. Therefore, the purpose of this researcher is to create a system to predict the rise and fall of the number of daily PCR test samples at laboratories in West Java in the future. This research was conducted in West Java because the capacity of the number of PCR test samples was not optimal, only relying on manuals with limited human resources. Therefore, the authors are able to predict the number of PCR test samples in the future using the Single Moving Average method. This method takes a group of observations and looks for the average value of the daily development of the number of PCR test samples in West Java, as a forecast in the future. The number of Covid-19 PCR test samples from the MSE (Mean Square Error) calculation is 689,873. With the SMA method, it makes it easier for admins to see predictions for the number of PCR samples for the future.
Penerapan Metode Multi-Objective Optimization on the Basic of Ratio Analysis (MOORA) dalam Keputusan Penerimaan Siswa Baru Mesran Mesran, M.Kom; Juanda Hakim Lubis; Iwan Fitrianto Rahmad
Bulletin of Informatics and Data Science Vol 1, No 2 (2022): November 2022
Publisher : PDSI

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Abstract

This research was made so that the school can easily select new students who are running as students in a school. This selection is done based on the criteria that have been determined by the school. To solve this problem, a decision support system is needed using the Multi-Objective Optimization Method on The Basic of Ratio Analysis (MOORA). this method is also quite easy to use and the results are good by obtaining the best value of 0.2296 with alternative A1 and followed by alternative A5 with a preference value of 0.1383. So that the decision support system by applying the MOORA method can solve problems in the selection of new students who are accepted or declared graduated with a systematic and precise selection. The MOORA method can also be used in people who really need it
Estimasi Keberhasilan Siswa dalam Pemodelan Data Berbasis Learning Menggunakan Algoritma Support Vector Machine Suryani Suryani; Mustakim Mustakim
Bulletin of Informatics and Data Science Vol 1, No 2 (2022): November 2022
Publisher : PDSI

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Abstract

SMK Negeri 5 Pekanbaru aims to prepare competent graduates who can compete in the global market. The realization of these goals is influenced by student achievement at school. Student achievements determine the ability of students to work in certain fields. Based on observations, it is known that student achievement at SMK Negeri 5 Pekanbaru tend to be low. This is also shown by the data that has been collected through the Curriculum section. Based on the data, there can be extraction using the supervised learning method to make a classification model of student achievements. The supervised learning algorithm used in this research is a Support Vector Machine (SVM). The data used in this study are student's data grade X SMK Negeri 5 Pekanbaru in 2020 totaling 160 data. The classification process is carried out by applying the GridSearch method to find the best kernel to be implemented. Based on the implementation of GridSearch, the kernel to be used is Radial Basis Function (RBF) with Cost (C) and Gamma (?)  parameters. Based on 16 experiments with different parameter values, the best classification results are obtained using the value of  Cost (C) = 0.1 and the value of Gamma (?)  = 0.01, with accuracy values of 94%.
UMKM Class Determination Support System Using Profile Matching Setiawansyah Setiawansyah; Adhie Thyo Priandika; Bustanul Ulum; Ade Dwi Putra; Dyah Ayu Megawaty
Bulletin of Informatics and Data Science Vol 1, No 2 (2022): November 2022
Publisher : PDSI

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Abstract

UMKM are businesses run by individuals, households, or small business entities. The classification of MSMEs is usually carried out with limits on turnover per year, the amount of wealth or assets, and the number of employees. Determining the UMKM class using the profile matching method which can make effective decisions on existing problems. With the decision support system to determine the class of UMKM in determining the class of UMKM by looking at the highest value of the ranking results based on several aspects of the assessment including turnover, assets, human resources, marketing, and permits. The results of the calculation for the assessment of the Micro UMKM class for PT Hasta Karya Nugraha are 1.5275 for the Micro UMKM Class Appropriate because it passes the minimum standard value for Micro MSMEs, the Small MSME Class for PT Hasta Karya Nugraha is 2.2975 Appropriate because it passes the minimum standard value for Small UMKM, and The Small UMKM class for PT Hasta Karya Nugraha is 2.3 Not suitable because it does not pass the minimum standard value for Medium UMKM. As for the results of the calculation of the assessment of the Micro UMKM class for CV Permata Jaya, namely 0.54 the Micro MSME Class is Appropriate because it passes the minimum standard value for Micro MSMEs, the Small UMKM Class for CV Permata Jaya is Appropriate because it passes the Small MSME minimum standard value, and the Small UMKM Class for CV Permata Jaya. CV Permata Jaya which is 1.62 Appropriate because it passes the minimum standard value of Medium UMKM. The conclusion of the assessment results of the application of the profile matching method to determine UMKM to move up the class for PT Hasta Karya Nugraha is in the Micro class, and CV Permata Jaya is in the Middle class.

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