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Vision Transformer untuk Identifikasi 15 Variasi Citra Ikan Koi Uthama, Rayhan; Yuhandri; Billy Hendrik
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6711

Abstract

This research aims to classify various types of koi fish using Vision Transformer (ViT). There is previous research [1] using Support Vector Machine (SVM) as a classifier to identify 15 types of koi fish with training and testing datasets respectively of 1200 and 300 images. This research was continued by research [2] which implemented a Convolutional Neural Network (CNN) as a classifier to identify 15 types of koi fish with the same amount dataset. As a result, the research achieved a classification accuracy rate of 84%. Although the accuracy obtained from using CNN is quite high, there is still room for improvement in classification accuracy. Overcoming obstacles such as limitations in classification accuracy in previous studies and further exploration of the use of new algorithms and techniques, this study proposes a ViT architecture to improve accuracy in Koi fish classification. ViT is a deep learning algorithm adopted from the Transformer algorithm which works by relying on self-attention mechanism tasks. Because the power of data representation is better than other deep learning algorithms including CNN, researchers have applied this Transformer task in the field of computer vision, one of the results of this application is ViT. This study was designed using class and number datasets retained from two previous studies. Meanwhile, the koi fish image dataset used in this research was collected from the internet and has been validated. The implementation of ViT as a classifier in koi classification in this research resulted in an accuracy level that reached an average of 89% in all classes of test data.
Penerapan Convolutional Neural Network pada Klasifikasi Citra Pola Kain Tenun Melayu Mukhlis Santoso; Sarjon Defit; Yuhandri
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6713

Abstract

The use of electronic computerized media is growing along with advances in hardware and software as an analytical tool with various algorithms and methods for classifying and measuring objects in various contexts. This progress aims to overcome the weaknesses that exist in conventional methods used in the identification process. The identification process can be applied to various objects, one of which is an image object. An image is a visual representation of an object formed through a combination of RGB (red, green, blue) colors. RGB color components or features have a range of values from 0 to 255 in an image. Weaving is a type of fabric that is specially made with distinctive motifs. Malay weaving motifs have a lot of diversity, this diversity makes it difficult to distinguish the motifs of these fabrics.This study aims to recognize and distinguish the pattern of Malay woven fabric. The method used in this research is Convolutional Neural Network (CNN). The CNN method has several stages, namely Convolution Layer, Pooling Layer, Rectifed Linear Unit (ReLU) Function, Fully-Connected Layer, Transfer Learning, Optimizer and Accuracy. The dataset used in this research is sourced from Tenun Putri Mas Bengkalis. The dataset used consists of 1000 images of weaving motifs which are divided into 80% training data and 20% testing data, from the existing dataset divided into three categories of weaving motifs namely pucuk rebung, elbow clouds and elbow keluang. The results in this study are considered good because they produce accuracy with a result of 95% with an epoch value of 15. From the results of good enough accuracy, it is hoped that it can help the community in recognizing Malay weaving motifs.
Penetapan Penerimaan Besaran Pembiayaan pada KPN Syariah dengan Metode AHP Hasni, Salmi; Nurcahyo, Gunadi Widi; Yunus, Yuhandri
Jurnal Informasi dan Teknologi 2019, Vol. 1, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v1i4.7

Abstract

The financing approval process for the Al-Ikhlas Sharia Civil Servant Cooperative (KPN) of the Batusangkar State Islamic Institute (IAIN) is still carried out by manual review, making it difficult to receive financing quickly and accurately. As a solution to these problems, we need a decision support system that can help in determining the amount of financial revenue. Analytic Hierarchy Process (AHP) is one of the multi-criteria problem solving models used in this study. The criteria used in determining the amount of financing received at the Al-Ikhlas IAIN Sharia Batusangkar KPN are character, capital, capacity, condition, and collateral. This study produces a weighting matrix of results, with KS as the member who gets the highest score of 95.3% and can apply for financing with a maximum amount.
Analisa Data Profil Pelanggan Menggunakan Algoritma FP-Growth Suryani, Vivi; Defit, Sarjon; Yunus, Yuhandri
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i1.8

Abstract

The number of bouquet orders is quite varied sometimes increased and decreased. The number of hikes certainly carries the goodness but the amount of decline certainly has an impact for Wawa Florist because it can not fulfill the number of bouquet order. The purpose of this research is to know how Data Mining techniques with Fp-Growth algorithm methods and designing the grouping of customer data of Wawa Florist with the FP-Growth algorithm method to obtain better and more effective analysis results. The result of the order data of the wreaths in Wawa Florish can be obtained which area information most booked wreaths, the most ordered bouquet of flowers are: D02 (Lubuk Buaya), D04 (Lubuk Minturun), D01 (Pariaman) and D03 (Lubuk Alung ). These results are obtained based on the appearance of the itemset of the bouquet booking data. Meet minimum confidence 60%.
Implementasi Metode Elimination Et ChoixTraduisant La Realite (ELECTRE) dalam Penentuan Pegawai Berprestasi Delmayanti, Vera; Yunus, Yuhandri; Santony, Julius
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i1.9

Abstract

The Kerinci Regency Cooperatives, Industry and Trade Office has a variety of employees whose competencies in their fields are for that purpose in improving an employee's performance by determining outstanding employees who aim to motivate and reward them for improving employee work performance. In determining this outstanding employee the data used are 3 samples of employee names as alternatives and some of the criteria on which decisions are made include Service Orientation, Integrity, Commitment, Discipline, and Cooperation. The results of the process of the ELECTRE method is to compare one employee with another employee and provide the results of priority value output in the form of assessment results or based on criteria that have been determined by the Office. The results of this process are recommended as outstanding employees at the Kerinci Regency Cooperatives, Industry and Trade Office.
Simulasi Monte Carlo untuk Memprediksi Hasil Ujian Nasional (Studi Kasus di SMKN 2 Pekanbaru) Yusmaity; Santony, Julius; Yunus, Yuhandri
Jurnal Informasi dan Teknologi 2019, Vol. 1, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v1i4.21

Abstract

Basically grades that do not meet graduation criteria are phenomenon for schools. Which can cause a lack of school quality. One such phenomenon is the National examination Score which is the value of determining graduation for students. Vocatonal High School (SMK) Negeri 2 Pekanbaru is a formal education unit as the organizer of the Teaching Learning Process (TLP), for student afterc ompleting education can go directly to employment or the industrial world and can continue their education. Where the test csores obtained by student are inseparable from the school graduation criteria.To deal whith probalytic situations like this we need a method for analyzing or predict likely in the future. One method that can be used is Monte Carlo Simulation. By using Monte Carlo Simulation to the national exam in this study is expected to holp to find out the acquition of student grades for the future. The csores are taken fom the national exam result obtained from the curriculumsection of the last 3 academic years, namely TP 2016/2017 to TP 2018/2019. This scores is simulationted whith PHP programming as a data implementation system. Simulation result from this studyobtained an accuracy level of 86,68%. By getting a greater degree of accuracy, this method is appropriate to be predict the National Exam Scores for the future.
Pemilihan Supplier Obat yang Tepat Menggunakan Metode Multi Attribut Utility Theory Djasmayena, Selvia; Yunus, Yuhandri; Putra, Rezi Elsya
Jurnal Informasi dan Teknologi 2019, Vol. 1, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v1i4.27

Abstract

Drug suppliers are those who sell and distribute drugs to pharmacies or sections that carry out pharmaceutical activities. Selection of the right supplier can support the operational activities of the pharmacy. Pharmacists must know the right criteria in choosing a supplier. Criteria determined by pharmacies not all suppliers can fulfill it. Overcoming this decision support system is very necessary in the selection of suppliers. Multi-Attribute Utility Theory is a ranking method that helps in supporting supplier selection decisions at Pekanbaru Assyafni Pharmacy. Supplier selection uses 15 sample supplier data and 5 criterion data used as a basis for supplier selection. Such as drug production, delivery time, quality stability, service response, and guarantee. The results of the study get a high degree of accuracy that is 86.67% of the right suppliers and in accordance with the realization of test data. So this research is very important in choosing the right supplier.
Identifikasi Sistem Operasi Prosedur Tingkat Penanganan Penyakit pada Anak Balita Samosir, Khairunnisa; Yunus, Yuhandri
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i2.31

Abstract

Children at the age of 1 year (toddlers) are more susceptible to the disease, parents must always give more attention to their children with poor health conditions, of course it will be very important for the growth of children. Application of an expert system to diagnose digestive diseases by using the forward chaining method can help parents in knowing the state of children's health. This research is an applied technology product that can provide benefits as a media or instructor in handling patients. The design of this system has been carried out through data activities, rule design, process design and system testing. From data and information found handling facts. The results obtained from system testing using the PHP MySQl application indicate that the results of diagnoses and pediatric diseases at Tanjung Balai General Hospital, have as many as 10 patient data that have been examined by experts and have conducted system checks to achieve 80% accuracy, from the conclusions that can be concluded data obtained from experts developed using the Forward Chaining Method are appropriate in determining the symptoms and diseases obtained from experts.
Prediction of the Number of Arrivals of Training Students With the Monte Carlo Method Sapriadi, Sopi; Yunus, Yuhandri; Dari, Rahmatia Wulan
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.168

Abstract

The simulation of predicting student arrivals for training is an estimate of the calculation of the arrival rate of students in a period to conduct training. The number of student visits is too many, sometimes inversely proportional to the programmers who carry out learning, this causes the ongoing service to be less than optimal. This study aims to predict student arrivals in the future better. The data processed in this study were 3 periods sourced from the administration of a private company in West Sumatra. The data will be processed and calculated using the Monte Carlo method. The data were tested with various possible elements using a random sample. A powerful numerical calculation tool by simulating statistical data, this simulation obtains accurate values ​​​​accurately from the physical form of the system that can be observed. The calculation implementation will be developed using an application-based system that will be built with the Hypertext Preprocessor (PHP) programming language. The system developed is easier and more relevant by applying Information Technology. The results obtained in predicting are 80% for 2017 and 84% for 2018. From the results of 80% accuracy in 2017 and 84% 2018 the system works very well to implement. Based on the results of data processing with the Monte Carlo method, it can be predicted that the number of student arrivals for training, as well as a good and fast decision-making process in the future.
Optimization of the Activation Function for Predicting Inflation Levels to Increase Accuracy Values Windarto, Agus Perdana; Rahadjeng, Indra Riyana; Siregar, Muhammad Noor Hasan; Yuhandri, Muhammad Habib
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7776

Abstract

This study aims to optimize the backpropagation algorithm by evaluating various activation functions to improve the accuracy of inflation rate predictions. Utilizing historical inflation data, neural network models were constructed and trained with Sigmoid, ReLU, and TanH activation functions. Evaluation using the Mean Squared Error (MSE) metric revealed that the ReLU function provided the most significant performance improvement. The findings indicate that the choice of activation function and neural network architecture significantly influences the model's ability to predict inflation rates. In the 5-7-1 architecture, the Logsig and ReLU activation functions demonstrated the best performance, with Logsig achieving the lowest MSE (0.00923089) and the highest accuracy (75%) on the test data. These results underscore the importance of selecting appropriate activation functions to enhance prediction accuracy, with ReLU outperforming the other functions in the context of the dataset used. This research concludes that optimizing activation functions in backpropagation is a crucial step in developing more accurate inflation prediction models, contributing significantly to neural network literature and practical economic applications.
Co-Authors - Hendrick - Khairiazaz AA Sudharmawan, AA Aal, Defrizal Abda Abda Abdul Azis Said Achmad Fauzan Syaputra Ade Dwi Dayani Afifah Cahayani Adha Aggy Pramana Gusman Agung Ramadhanu Agus Perdana Windarto Akbar Iskandar Akbari Wafridh Aldi Muharsyah Alfallah, Fadhly Alifcha Ghazian Alifia Restu Selvanda Allans Prima Aulia Andema, Henky Andre Rahmat Kurniawan Andrean, Fajri Ilhami Angga Putra Juledi Anita Sindar Anjun Dermawan Antoni Antoni Aprilian Gevindo Ardiyan, Destio Arif Budiman Arika Juwita Z Ariza Ikhlas Asyhari, Ahmad Aulia, Allans Prima Auriga, Wira Ayu Prima Siska Bambang Supperianto Billy Hendrik Borianto, B Budayawan, Khairi Budi Jaya Budi Permana Putra Chairul Imam Chairul Imam, Chairul Chandra, Mrs Montesna Dahria, Muhammad Dari, Rahmatia Wulan Darnis, Rahmi Delmayanti, Vera Dendi Ferdinal Deno Yulfa Ardian Desi Laidawati Devi Maryuni Dewi Eka Putri Dian Maharani, Dian Dikki Handoko Djasmayena, Selvia Djesmedi, Dinda Dodi Andre Putra Dolly Indra DWI JULISA UTARI Dwi Narulita Dwika Assrani Dzaki Al Fikri Effendy, Geraldo Revanska Efori Buulolo Eggy Febyanti Edwar Eka Naufaldi Novri Eka Praja Wiyata Mandala Eka Ramadhani Putra Eka Sofianti Elpina, Elpina Sari Dewi Hasibuan Eriyanto, Joko Erizke Aulya Pasel Esa Kurniawan Esa Kurniawan Eska, Juna Eva Rianti Fachrul Ilmawan Fadil Idensia Fahmi Firzada Fajri Ilhami Andrean Fauzan, Yuniko Febri Aldi Febri Hadi Feri Irawan Fernando Ramadhan Fhajri Arye Gemilang Finny Fitry Yani Firna Yenila Firzada, Fahmi Fitra, Ilham Fuad El Khair Gayatri, Satya Gemilang, Fhajri Arye Gunadi Dwi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo, Gunadi Hadi Syahputra Hadrila P A Halifia Hendri Harkamsyah Andrianof Hartika Zain, Ruri Hartika Hartomi, Zupri Henra Hasanatul Iftitah Hasni, Salmi Hasri Awal Hendrick, H Hendro Zalmadani Henky Andema Hermanto Heru Rahmat Wibawa Putra Ibnu Luthfi Idir Fitriyanto Idir Idun Ariastuti Ikhlas, Muhammad Ilham Asy'ari Ilham Fitra Indah Dwi Putri Indah Permata Sari Indra Riyana Rahadjeng Irvan Okta Mazhona Iskandar Fitri, Iskandar Ismail Virgo Jaya, Budi Jefdy Kurniawan Jhon Veri Johan Danu Wijaya Jufriadif Na`am, Jufriadif Juledi, Angga Putra Julius Santony Julius Santony Julius Santony Julius Santony Julius Santony Julius Santony K Kadrahman Kadrahman, Kadrahman Karseno, Doni Khairani, Maisan Dewi Puspa Khairiazaz Kurniawan, Jefdy Laidawati, Desi Larissa Navia Rani, Larissa Lc Granadi Suhaidir Lidia K Simanjuntak Liga Mayola Lova Endriani Zen Lusi Kestina M Ikhsan Setiawan M Ilham Aldyno M Mutia M, Mutia M.Iqbal, M.Iqbal Maharani Maharani, Maharani Majid Rahman Aziz Mardayulis, Mardayulis Mardison Mardison Mardison Meiditra, Irzon Mesran, Mesran Mey Yuki Lestari Mifthahul Rahmi Mohammad Guntur Montesna Muhammad Abrar Masril Muhammad Amin Muhammad Amin Muhammad Arif Zikir Risky Muhammad Ihksan Muhammad Noor Hasan Siregar Mukhlis Santoso Na'am, Jufriadif Nabilla Yasmin Nandra Sunaryo Nasma Yeni Nasution, Annio Indah Lestari Natalia Silalahi, Natalia Negoro, Wahyu Saptha Nelly Astuti Hasibuan Nissa, Ika Ima Nuning Kurniasih Nurdiyanto, Heri Olivia, Ladyka Febby Ondra Eka Putra P, Prihandoko Permana, Randy Petti Indrayati Sijabat Pohan, Yosua Ade Pratama , Abdul Hanif Pratama, Muhammad Harits Pratiwi, Fitri Prestian Ramadhan Prihandoko Prihandoko Prihandoko Prihandoko, P Pulungan, Akhiruddin Purnomo, Nopi Putra, Heru Rahmat Wibawa Putra, Rafi Septiawan Putra, Rezi Elsya Putri, Stefani R Rahmiyanti Rafi Septiawan Putra Ragil Ardiansyah Rahayu, Rita Rahmad Dian Rahmad Dian Rahmansyah, Rizky Rakhmad Kuswandhie Resnawita Retno Devita Riadi, Rahadatul ‘Aisy Riati, Itin Ridho, Ridho Afwan Rifky, Muhammad Rio Andika Malik Ririn Violina Riski Randa Hidayatullah Rita Sari Rita Sari Rivo Stephano Roby Nurbahri Romi Hardianto Romzi Rahman Ronda Deli Sianturi Rovidatul Rubiati, Nur Rusydi, Rezki S Salmiati Sabri T Rahman Sagala, Gamrina Sahat Sonang Sitanggang Sahri, Alfi Said, Abdul Azis Sajida, Mayang Salman Alfarisi Salimu Salmiati, S Samosir, Khairunnisa Saputra, Randy Sari, Fitri P. Sarjon Defit Seni Oknora Firza Septiana Vratiwi Septiana, Vina Tri Setiawan, Adil Setiawan, Adil Silfia Andini Siregar, Diffri Sisi Hendriani Siska, Ayu Prima Soeheri Soeheri Sonang, Sahat Sonia Indhira Sopi Sapriadi Soraya Rahma Hayati Sovia, Rini Sri Amalia Harahap Sri Dewi Sri Dewi Sri Rahmawati Stefani Hardiyanti Putri Stephano, Rivo Subrianto Chandra Sugiarti, Sugiarti Suginam Suhaidir, Lc Granadi Sukardi Sulastri Sulastri Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan, S Sunaryo, Nandra Supriyanto, Boby Surya Darma Nasution Suryani, Vivi Sutiksno, Dian Utami Syafri Arlis Syafrika Deni Rizki Syafril Syafril Syahid Hakam Abdul Halim Syahputra, Afriadi Syaiffullah, Afif Syaljumairi, Raemon Syaputra, Eka B. Tajuddin, Muhammad Takyudin, Takyudin Tamin, Zulfiqar Taufik Nur Zam Zam Teddy Winanda Teguh Junaidi Teri Ade Putra Tessa Y M Sihite Toti Sri Mulyati Tri Agusti Farma Triyolla Ivandina Tukino, Tukino Uthama, Rayhan Veri, Jhon Very, Jhon Virgo, Ismail Vratiwi, Septiana Wanto, Anjar Wendi Boy Wenni Afrodita Willy Eka Septian Winanda, Teddy Winarto Winarto Wira Apriani Wira, M Wira Sanjaya Wirahmadayanti, Isna Yanti, Salma Nofri yanto, heri Yanto, Musli Yanto, Musli Yendi Putra Yendi Putra Yeni, Nasma Yolla Rahmadi Helmi Yosua Ade Pohan Yuda Irawan Yuda, Fitra Yuda Yudha Aditya Fiandra Yudha Aditya Fiandra Yundari, Yundari Yuniko Fauzan Yusma Elda Yusmaity Zalmadani, Hendro ZH, Lina Alfaridah. Zufari, Faisal Zupri Henra Hartomi