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All Journal Jurnal Sains dan Teknologi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pilar Nusa Mandiri Jurnal Ekobistek Sebatik MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Informasi dan Pendidikan Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat Majalah Ilmiah UPI YPTK Journal of Computer Scine and Information Technology Jurnal Ipteks Terapan : research of applied science and education Jurnal Komtekinfo SATIN - Sains dan Teknologi Informasi Journal Of Informatics And Busisnes Jurnal Teknik dan teknologi tepat guna The Indonesian Journal of Computer Science Jurnal TAM (Technology Acceptance Model)
Syafri Arlis
Universitas Putra Indonesia YPTK
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

 1 
Analysis of sales levels of pharmaceutical products by using data mining algorithm C45 Rini Sovia; Abulwafa Muhammad; Syafri Arlis; Guslendra Guslendra; Sarjon Defit
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp476-484

Abstract

This research was conducted to analyze the level of sales of pharmaceutical products at a Pharmacy. This is done to find out the types of products that have high and low sales levels. This study uses the C45 data mining algorithm concept that will produce a conclusion on the prediction of sales of pharmaceutical products through data processing obtained from sales transactions at pharmacies. This C45 algorithm will form a decision tree that provides users with knowledge about products that are in great demand by consumers based on sales data and predetermined variables. The final result of the C45 algorithm produces a number of rules that can identify the inheritance of a type of medicinal product. C45 algorithm is able to produce 20 types of categories that will be labeled goals based on the number of pharmaceutical products, since it can be concluded that C45 successfully defines 55% of the existing objective categories.
Implementation multiple linear regresion in neural network predict gold price Musli Yanto; Sigit Sanjaya; Yulasmi Yulasmi; Dodi Guswandi; Syafri Arlis
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1635-1642

Abstract

The movement of gold prices in the previous period was crucial for investors. However, fluctuations in gold price movements always occur. The problem in this study is how to apply multiple linear regression (MRL) in predicting artificial neural networks (ANN) of gold prices. MRL is mathematical calculation technique used to measure the correlation between variables. The results of the MRL analysis ensure that the network pattern that is formed can provide precise and accurate prediction results. In addition, this study aims to develop a predictive pattern model that already exists. The results of the correlation test obtained by MRL provide a correlation of 62% so that the test results are said to have a significant effect on gold price movements. Then the prediction results generated using an ANN has a mean squared error (MSE) value of 0.004264%. The benefits obtained in this study provide an overview of the gold price prediction pattern model by conducting learning and approaches in testing the accuracy of the use of predictor variables.
Automated model for identification on mastoid of temporal bone image Syafri Arlis; Sarjon Defit; Sumijan Sumijan
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp570-581

Abstract

Mastoiditis occurs due to inflammation that can affect the structure of the mastoid bone. The mastoid bone consists of the mastoid air cell system (MACS) which protects the ear structures and regulates air pressure in the ear and has different sizes and characteristics, making it very difficult to identify precisely. This study aims to identify and find the right MACS size by developing an automatic identification model and obtaining the optimal threshold value in the segmentation process using the extended adaptive threshold (eAT) method. The research dataset uses computed tomography (CT)-scan images of 308 slices of 12 patients indicated for mastoiditis. The results of this study provide identification that has the right MACS accuracy and size. Overall, the optimal segmentation process obtained the smallest threshold value of 57 and the largest threshold value of 63, the smallest MACS size is 4.025 cm2 and the largest is 8.816 cm2 with an accuracy rate of 93.4%. The smaller MACS size indicates inflammation in the mastoid area and these patients require more intensive treatment.
Effectiveness of VGG19 in deep learning for brain tumor detection Arlis, Syafri; Putra, Muhammad Reza; Yanto, Musli
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp1210-1218

Abstract

Image processing in the diagnosis of disease is one of the jobs that is currently developing in the world of health. Diagnosis is carried out by utilizing the role of image processing to provide a level of accuracy in diagnosis results and provide efficiency to medical personnel. This research aims to develop a brain tumor object detection process using a deep learning (DL) approach to magnetic resonance images (MRI) images. This development was carried out to optimize the brain tumor diagnosis process by playing the role of the image extraction process. This research dataset was sourced from the M. Djamil Padang Provincial General Hospital with a total of 3370 MRI images. The results of this work report show that DL performance is capable of carrying out the detection process automatically with an accuracy level of 97,83%. The results of the development of the extraction process can work effectively in ensuring brain tumor objects are precise and accurate. Overall, this research can make a major contribution to maximizing the diagnosis process and assisting medical personnel in the early treatment of brain tumor patients.
Co-Authors Agung Ramadhanu Andrian, Reski Aswandi, Nopan Candra Putra Darma Syahrullah Ekajaya Dodi Guswandi Doli Raharjo, Tio Edwar, Eggy Febyanti Fajrul Islami Febri Hadi Feri Pratama Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo, Gunadi Guslendra Guslendra Hanum, Luthfia Harkamsyah Andrianof Hendrik, Billy Johan Harlan Jufriadif Na`am, Jufriadif Larissa Navia Rani Larissa Naviarani M.Iqbal, M.Iqbal Mardison Mardison Marfalino, Hari Muhammad, Abulwafa Musli Yanto Nabila Frisca Oktavia Nur, Rofil M Nurcahyo, Yuhandri Olivia, Ladyka Febby Permana, Nabilah Putri Prayuda, Muhammad Hozi Putra, Deri Marse Putra, Muhammad Reza Ridwan, Ridwan Rini Sovia Rofil M. Nur Sahari Sahari Sahari Sahari Sahari Sarjon Defit Sarjon Defit SIGIT SANJAYA, SIGIT Sofika Enggari Sumijan Sumijan Sumijan Sumijan Supperianto, Bambang Syahputra, Afriadi Wahyu, Fungki Winda Sutra Amanda Yanto, Musli Yuhandri Yuhandri Yunus Yuhandri, Y Yulasmi