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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnas Nasional Teknologi dan Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Digital Zone: Jurnal Teknologi Informasi dan Komunikasi KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Sawerigading Jurnal Teknologi Informasi dan Pendidikan Jurnal Sistim Informasi dan Teknologi Jurnal Informasi dan Teknologi Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Infortech Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Applied Data Sciences Journal of Computer Scine and Information Technology Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat SmartComp
Yuhandri Yuhandri, Yuhandri
Unknown Affiliation
Aerospace Engineering Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Penerapan Algoritma C4.5 untuk Klasifikasi Data Rekam Medis berdasarkan International Classification Diseases (ICD-10) Yudha Aditya Fiandra; Sarjon Defit; Yuhandri Yuhandri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 1 No 2 (2017): Agustus 2017
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (579.053 KB) | DOI: 10.29207/resti.v1i2.48

Abstract

Abstract The medical record data is the patient's current record of medical records, the medical record data only being data stacked and not traced to generate useful knowledge for the hospital. This study can process the medical record data to classify the disease that occurs in sleeping sickness based on ICD-10. The method used in this research is C4.5 algorithm method by using attribute of international disease code as attribute of destination label as many as 21 international disease group, that is: A00-B99 up to Z00-Z99. This study yields a decision of the value code, C4.5 code can represent as many as 14 attribute values ​​of disease code objectives and data percentage that read more than 66%. The conclusion of this research is C4.5 algorithm help classify international disease code based on ICD-10 and decision tree making which can give information of any disease that often happened at hospital Keywords: data mining, classification, C4.5, medical records, ICD-10
Pengukuran Tinggi Sebenarnya Objek pada Foto Digital Menggunakan Euclidean Distance Rakhmad Kuswandhie; Jufriadif Na’am; Yuhandri Yuhandri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 2 No 1 (2018): April 2018
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.58 KB) | DOI: 10.29207/resti.v2i1.334

Abstract

Digital photos are generated from the camera. In the photo there are some object that can be observed. The object in images is a representation of the fact that in the real world. The size of an object in a digital image can represent the true size of an image object with a certain size scale. The actual size of the object in the photo can not be known directly. Digital photos used in the research is the image generated from the camera phone with 8MB resolution and the distance of the camera to photo objects as far as 1, 3 and 5 meters with 3 different objects, ie gallons, chairs and legs. The size of objects in a digital image will be measured using an application created with the C # programming language. Measuring objects in photos using Euclidean Distance. Next is calculated the actual size of the object that is in the photo by using trigonometric function. The test result of 3 objects on digital photos with 3 different distances obtained the actual object size with an accuracy are 99,993%.
Diagnosa Penyakit Osteoporosis Menggunakan Metode Certainty Factor Yuhandri Yuhandri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 2 No 1 (2018): April 2018
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (588.357 KB) | DOI: 10.29207/resti.v2i1.349

Abstract

The purpose of this research is to build an Expert System application for the diagnosis of Osteoporosis disease. This study uses Certainty Factor method because in this method there is a value of the value of trust (Measure Of Belief) and the value of distrust (Measure Of Disableief) on a symptom, where later the value can produce the value of CF (Certainty Factor) as a benchmark, the greater the value of CF (Certainty Factor) obtained the greater the chance that the disease will attack us, where the results are displayed in terms of user conditions associated with Osteoporosis. The results of this study also comes with disease and treatment solutions are displayed in the form of websites using PHP programming and is also useful to perform early diagnosis of a disease that is perceived by the userthus helping the user in recognizing the symptoms of Osteoporosis disease they feel, as well as with the existence of this expert system can be used as an alternative solution for the community to make early diagnosis of the symptoms of Osteoporosis disease they feel before doing direct consultation with experts in this case specialist bone. This system is able to store expert knowledge representation based on certainty factor with accuracy of 80%.
Peramalan Penjualan Pada Toko Retail Menggunakan Algoritma Backpropagation Neural Network Musli Yanto; Eka Praja Wiyata Mandala; Dewi Eka Putri; Yuhandri Yuhandri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 2, No 3 (2018): Juli 2018
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v2i3.811

Abstract

Retail is one or more activities that add value to the product to the consumer either for family needs or for personal use. Retail can sell products depending on current market needs. The goods we enjoy today are not apart from retail services, retail helps producers / distributors and consumers so that every need will be fulfilled. In this problem the author tries to do retail store research in the city of Padang. This research aims to help retail stores to forecast procurement of goods. Artificial Neural Network Backpropagation can make the forecasting process for procurement of goods for the next period of time on each item on the retail and will ultimately be useful for retail store managers. The forecasting process begins with determining the variables that will be required in the network pattern, then the pattern of established network will be continued on the network training process by using backpropagation algorithm. After doing the network training process the researchers will do a comparison with some pattern of network that has been formed. The last process undertaken in this research is the process of determining the best network pattern of the average value of errors obtained from each training network pattern. In the final result of the forecasting process, the results of the calculation have a total error of = 3.57%. Judging from the forecasting process that will be done not only used to predict the procurement of goods but also can predict sales figures in retail stores. In principle, this research can help to determine the procurement of goods in the sales process that will minimize the losses that occur in every sales activity.
Analisis Penurunan Gradien dengan Kombinasi Fungsi Aktivasi pada Algoritma JST untuk Pencarian Akurasi Terbaik Anjar Wanto; Jufriadif Na`am; Yuhandri Yuhandri; Agus Perdana Windarto; Mesran Mesran
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2509

Abstract

There are many training function methods for gradient descent (gradient descent) and activation functions (transfer functions) that can be used in the ANN algorithm, especially the backpropagation algorithm. Therefore the aim of this paper is to analyze the best gradient descent that can be used as a reference for use in the ANN algorithm, especially the backpropagation algorithm in data prediction, classification and pattern management problems. The gradient descent methods to be analyzed include; Gradient descent backpropagation (traingd), Gradient descent with momentum backpropagation (traingdm), Gradient descent with adaptive learning rate backpropagation (traingda), and Gradient descent with momentum and adaptive learning rate backpropagation (traingdx). The training function will be combined with the activation function (transfer function) of bipolar sigmoid (tansig), linear transfer (purelin) and binary sigmoid (logsig). The sample data used for the analysis process is the time-series data for the Human Development Index in Indonesia, which is obtained from the Central Bureau of Statistics (BPS). Architectural models used for gradient descent analysis include: 6-10-15-1, 6-15-20-1, 6-20-25-1 and 6-25-30-1. Based on the analysis results, the best training function is traingda with an architectural model of 6-15-20-1 which produces an accuracy rate of 91% and MSE testing is 0.000731529 (smaller than other methods)
Sistem Pendukung Keputusan SNMPTN Jalur Undangan Dengan Metode Electre Lidia K Simanjuntak; Tessa Y M Sihite; Mesran Mesran; Nuning Kurniasih; Yuhandri Yuhandri
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 3 (2018): Edisi Juli
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v3i0.63

Abstract

All colleges each year organize the selection of new admissions. Acceptance of prospective students in universities as education providers is done by selecting prospective students based on achievement in school and college entrance selection. To select the best student candidates based on predetermined criteria, then use Multi-Criteria Decision Making (MCDM) or commonly called decision support system. One method in MCDM is the Elimination Et Choix Traduisant la Reality (ELECTRE). The ELECTRE method is the best method of action selection. The ELECTRE method to obtain the best alternative by eliminating alternative that do not fit the criteria and can be applied to the decision SNMPTN invitation path.
Algoritma Backpropagation Prediksi Harga Komoditi terhadap Karakteristik Konsumen Produk Kopi Lokal Nasional Petti Indrayati Sijabat; Yuhandri Yuhandri; Gunadi Widi Nurcahyo; Anita Sindar
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 11 No. 1 (2020): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (781.869 KB) | DOI: 10.31849/digitalzone.v11i1.3880

Abstract

Kopi bagian penting dari komoditi pasar nasional maupun internasional. Secara nasional jenis kopi lokal beragam sesuai nama daerah penghasil mengalami naik turun harga Perlu perencanaan teknologi untuk mengetahui harga kopi ke depan. Peramalan atau prediksi dalam ilmu komputer berkaitan dengan perkiraan berkala produksi, penawaran dan permintaan pada masa tertentu menggunakan alat ukur yang akurat dan teruji. Metode Backpropagation digunakan untuk prediksi harga. Proses algoritma backpropagation antara lain input data, melakukan tahap normalisasi /transformasi data, iterasi, pelatihan dan menentukan parameter jaringan, kalkulasi error, mendapatkan hasil prediksi. Perancangan arsitektur JST, dilakukan penentuan jumlah layer pada lapisan input, lapisan tersembunyi dan lapisan output. Penelitian ini menggunakan Matlab R2013a dengan metode Backpropagation. Pengambilan input, penelusuran error dan penyesuaian bobot berguna untuk menghasilkan nilai prediksi harga kopi. Hasil prediksi harga kopi dari harga aktual 74205 ke hasil harga prediksi 73668 dengan akurasi 99.9928, harga aktual 73892 ke harga prediksi 73175 dengan akurasi 99.9903, harga aktual 77981 ke hasil prediksi 77481 akurasi 99.9936. Kata Kunci: Syaraf Tiruan, Prediksi, Harga Kopi, Backpropagation Abstract Coffee is an important part of the national and international market commodity. Nationally, the types of local coffee vary according to the name of the producing region experiencing ups and downs in price. It needs technology planning to find out the price of coffee going forward. Forecasting or prediction in computer science is related to periodic estimates of production, supply and demand at certain times using accurate and tested measuring tools. Backpropagation method is used for price prediction. The backpropagation algorithm process includes inputting data, performing the normalization / transformation of data, iterating, training and determining network parameters, calculating errors, getting predictive results. The design of the ANN architecture determines the number of layers in the input layer, the hidden layer and the output layer. This research uses Matlab R2013a. Taking input, tracking errors and adjusting weights are useful for producing predictive value of coffee prices. Coffee prediction results from actual prices 74205 to the predicted price of 73668 with an accuracy of 99.9928, the actual price of 73892 to the predicted price of 73175 with an accuracy of 99.9903, the actual price of 77981 to the predicted result of 77481 with an accuracy of 99.9936. Keywords: Neural Networks, Predictions, Coffee Prices, Backpropagation
Hybrid Thresholding Method in Detection and Extraction of Brain Hemorrhage on the CT-Scan Image S Sumijan; Y Yuhandri; Wendi Boy
Journal of Computer Scine and Information Technology Volume 7 Issue 2 (2021): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v7i2.2

Abstract

Brain bleeding can occur because of the outbreak of the blood vessels in the brain which culminated into hemorrhagic stroke or stroke due to bleeding. Hemorrhagic Stroke occurs when there is a burst of blood vessels result from some trigger factor. Segmentation techniques to Scanner computed tomography images (CT scan of the brain) is one of the methods used by the radiologist to detect brain bleeding or congenital abnormalities that occur in the brain. This research will determine the area of the brain bleeding on each image slice CT - scan every patient, to detect and extract brain bleeding, so it can calculate the volume of the brain bleeding. The detection and extraction bleeding area of the brain is based on the hybrid thresholding method.
Implementasi E-Commerce Untuk Memperluas Pangsa Pasar Hasil Kerajinan UMKM Komunitas Hobi Kayu Padang Febri Hadi; Yuhandri Yuhandri; Liga Mayola
JDISTIRA - Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Vol. 1 No. 1 (2021)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1022.177 KB) | DOI: 10.58794/jdt.v1i1.31

Abstract

Setiap UMKM sebenarnya sudah mempunyai ciri khas dari masing-masing produknya, terlebih lagi cara pengolahan kerajinan kayu. Tetapi yang perlu dilakukan disini adalah bagaimana produk milik UMKM tersebut dapat dipasarkan secara nasional maupun internasional dengan memanfaatkan E-Commerce. Selain itu dengan sosialisasi strategi pemasaran produk ini, tentunya juga bisa membantu meningkatkan penjualan UMKM tersebut. Terlebih Kota Padang merupakan Ibukota Sumatera Barat yang mana banyak dikunjungi oleh para wisatawan dari berbagai daerah di Indonesia.
Application Of Weight Sum Model (WSM) In Determining Special Allocation Funds Recipients Dikki Handoko; Mesran Mesran; Surya Darma Nasution; Yuhandri Yuhandri; Heri Nurdiyanto
The IJICS (International Journal of Informatics and Computer Science) Vol 1, No 2 (2017): September 2017
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (461.472 KB) | DOI: 10.30865/ijics.v1i2.528

Abstract

In the management of education is not uncommon educational institutions sometimes receive sources of funds from outside, one of which comes from the Department of Education in the implementation of its duty to provide one allocation of funds called Special Allocation Fund (DAK). This assistance is from APBN revenues to areas devoted to schools to help fund special activities such as the addition or improvement of school facilities and infrastructure. The application of this special allocation grantee needs to use a Decision Support System (CMS) to allow decisions to be generated in favor of the DAK beneficiary. In the application of SPK required MCDM method, the Weight Sum Model (WSM), which is a simple method and able to generate ranking from the proposer alternatives in a special allocation fund.
Co-Authors Afifah Cahayani Adha Agus Perdana Windarto Akbar Iskandar Aldi Muharsyah Aldi, Febri Andrean, Fajri Ilhami Anita Sindar Ardiyan, Destio Arif Budiman Aulia, Allans Prima Budayawan, Khairi Chandra, Mrs Montesna Dahria, Muhammad Devita, Retno Dewi Eka Putri Dikki Handoko Dolly Indra Dwi Narulita Dwika Assrani Efori Buulolo Eka Praja Wiyata Mandala Esa Kurniawan Fauzan, Yuniko Febri Hadi Feri Irawan Finny Fitry Yani Firzada, Fahmi Fuad El Khair Gayatri, Satya Gemilang, Fhajri Arye Gunadi Widi Nurcahyo Hartomi, Zupri Henra Hendrick, H Idun Ariastuti Iftitah, Hasanatul Iskandar Fitri, Iskandar Jaya, Budi Jufriadif Na`am, Jufriadif Juledi, Angga Putra Julius Santony Julius Santony Julius Santony Kadrahman, Kadrahman Kurniawan, Jefdy Lidia K Simanjuntak Liga Mayola M Ikhsan Setiawan M, Mutia Maharani Maharani, Maharani Malik, Rio Andika Mesran, Mesran Musli Yanto Na'am, Jufriadif Natalia Silalahi, Natalia Nelly Astuti Hasibuan Nuning Kurniasih Nurdiyanto, Heri Permana, Randy Petti Indrayati Sijabat Pohan, Yosua Ade Purnomo, Nopi Putra, Heru Rahmat Wibawa Putra, Rafi Septiawan Putri, Stefani Rahayu, Rita Rahmad Dian Rakhmad Kuswandhie Ronda Deli Sianturi S Sumijan Sagala, Gamrina Salmiati, S Sarjon Defit Sarjon Defit Septiana, Vina Tri Setiawan, Adil Sisi Hendriani Siska, Ayu Prima Soraya Rahma Hayati Sovia, Rini Sri Dewi Stephano, Rivo Sugiarti, Sugiarti Suginam Suhaidir, Lc Granadi Sumijan Sumijan Sumijan Sumijan Sumijan, S Surya Darma Nasution Sutiksno, Dian Utami Syafrika Deni Rizki, Syafrika Deni Syaiffullah, Afif Tajuddin, Muhammad Takyudin, Takyudin Tessa Y M Sihite Tukino, Tukino Virgo, Ismail Vratiwi, Septiana Wanto, Anjar Wendi Boy Winanda, Teddy Yanto, Musli Yendi Putra Yeni, Nasma Yenila, Firna Yolla Rahmadi Helmi Yudha Aditya Fiandra Zikir Risky, Muhammad Arif