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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics JUITA : Jurnal Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi Bulletin of Electrical Engineering and Informatics Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Jurnal Teknik Komputer AMIK BSI Jurnal Khatulistiwa Informatika Paradigma Ekspektra: Jurnal Bisnis & Manajemen JITK (Jurnal Ilmu Pengetahuan dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer SEINASI-KESI International Journal for Educational and Vocational Studies Jurnal Mantik Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) Jurnal Bumigora Information Technology (BITe) Akrab Juara : Jurnal Ilmu-ilmu Sosial Jurnal Sistem Informasi IAIC Transactions on Sustainable Digital Innovation (ITSDI) Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Journal Software, Hardware and Information Technology International Journal of Basic and Applied Science Reputasi: Jurnal Rekayasa Perangkat Lunak Jurnal Sains Informatika Terapan (JSIT) INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH Paradigma Indonesian Journal Computer Science (ijcs) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi International Journal of Enterprise Modelling Jurnal Teknoinfo

Mochamad Wahyudi

Universitas Bina Sarana Informatika

Author-ID : 2543080

Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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SISTEM INFORMASI AKADEMIK BERBASIS WEB PADA SMA BUDI MULIA DI TANGERANG Andri Amico; Mochamad Wahyudi; Sumanto
Jurnal Sistem Informasi Vol 3 No 1 (2014): JSI Periode Februari 2014
Publisher : LPPM STMIK ANTAR BANGSA

Abstractâ€” With growing world of technology, especially Internetbased technologies like Web site where all the desired information can be easily and cheaply obtained. The presence of this academic information system website, is expected to help teachers, students, parents, and communities to obtain actual information about the SMA BUDI MULIA at TANGERANG. In building this system I use support tools with object-oriented methodology is UML because UML supports object-oriented programming languages or OOP (Object Oriented Programming), web applications, PHP and MySQL, while for the photo editor I use Adobe Photoshop CS3 and Adobe Dreamweaver CS3 media to write PHP scripts. Browser, function to view the PHP commands that have been run on a web server. Examples of browsers are: Internet Explorer, Netscape Navigator, Opera, Firefox in this case I use Mozilla Firefox. The system generated from the tools above will be much better in terms of efficiency, effectiveness, reliability and flexibility because UML is an object-oriented programming language. And other tools that are easy to understand because it is easy to learn.

PERANCANGAN SISTEM INFORMASI PENERIMAAN SISWA BARU (PSB) ONLINE PADA MADRASAH TSANAWIYAH (MTs) AL GOTSIYAH JAKARTA Fajar Akbar; Mochamad Wahyudi; Sumanto
Jurnal Sistem Informasi Vol 3 No 1 (2014): JSI Periode Februari 2014
Publisher : LPPM STMIK ANTAR BANGSA

Abstract -New Student Accepting System on MTs Al Gaotsiyah Jakarta all this time still utilizes manually, So slows process that happens with about problem aught. About problem which emerges is its a lot of prospective registrant which want to do registration and there are many prospective registrant which just wants to ask information therefore causative bustle happening out of focus service, and less research it officers in does penginputan data. psb's information system online offer trouble-shooting that adequately correct reduce aught constraint, psb's information system online it berbasiskan web becomes each information can at access wherever and whenever, so each student candidate that wants to register while wants to do registration can do online ala, so can settle constraint and ketrbatasan whatever available on MTs Al Gaotsiyah Jakarta.

OPTIMIZATION OF THE NUMBER OF CLUSTERS ON K-MEDOIDS USING CHEBYCHEV AND MANHATTAN ON GOLD SELLING GROUPING Dedi Triyanto; Deny Kurniawan; Mochamad Wahyudi
Jurnal Mantik Vol. 5 No. 3 (2021): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Gold is a type of precious metal that can maintain value and can be used for exchange. Gold has attractive properties, so many people like to buy gold for jewelry and also for investments that can be resold when they need money quickly. During the COVID-19 pandemic, some sales sectors experienced a decline but gold was still selling well. M. Siregar Gold Shop serves gold jewelry sales. Gold jewelery sales transactions at the M. Siregar gold shop are stored in the database. Every day the transaction data is increasing, so the data is getting more and more. From the mountains of data we can dig up information or generate knowledge. M. Siregar's gold shop has difficulty in knowing the type of gold that is selling well, making it difficult for gold shop owners to determine the right gold supply. This study aims to classify gold sales at the M. Sisregar gold shop so that it is known which types of gold are selling well. This grouping uses the K-Medoids method with the calculation of the distance between the Chebychec distance and the Manhanttan distance. The data is taken from the sales of gold at the M. Siregar store from November 2021 to March 2022. To produce an optimal grouping, this grouping is tested with several number of clusters by calculating the distance between Chebycev distance and Manhattan distance by calculating the DBI value of each number of clusters. . The result of the optimal grouping of gold sales is the K-Medoids method with the calculation of the Chebycev distance with the number of clusters = 2 with DBI value = 0.024.ns.

COMPARISON OF EUCLIDEAN DISTANCE, CAMBERRA DISTANCE, AND CHEBYCHEV DISTANCE IN K-MEANS ALGORITHM BASED ON DBI EVALUATION Deny Kurniawan; Dedi Triyanto; Mochamad Wahyudi
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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During the COVID-19 pandemic, almost all businesses experienced difficulties. But not all businesses experience difficulties. Cosmetics is a product category that still exists during the pandemic. Many customers buy cosmetics through online sales. Devi Cosmetics is a trading business which is engaged in selling cosmetics. Due to the large number of sales transactions recorded in the neglected database, it is difficult for business managers to find out which cosmetic products are in high demand by customers and make it difficult for business managers to determine the inventory of cosmetic goods correctly. Determination of the incorrect supply of cosmetics resulted in the loss of the store manager, namely many customers who canceled buying cosmetics due to empty supplies. This study uses the K-Means algorithm to classify sales of cosmetic goods. To find out the best grouping results, it is necessary to compare several distance calculation methods. The distance calculation method here uses three methods, namely Euclidean Distance, Camberra Distance, and Chebychev Distance by finding the DBI value of the three methods. The smallest DBI value is the chebychev distance calculation method with a DBI value = 0.254.

Determination of the Best Accuracy Model for Predicting Average Years of Schooling using the Fletcher Reeves Algorithm Ihsan Daulay; Mochamad Wahyudi; Solikhun; Lise Pujiastuti
International Journal of Basic and Applied Science Vol. 11 No. 1 (2022): June: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v11i1.78

The average length of schooling is an important and significant factor in looking at the quality of an individual human being, with increasing the quality of human resources it can increase access to decent work which also promises a stable economic income, and to some extent affects the economy in a country. Therefore, a prediction was made. This prediction method uses the Fletcher Reeves algorithm which is an artificial neural network algorithm method for data prediction. However, this paper does not discuss the results of the prediction, but discusses the ability of the Fletcher Reeves neural network algorithm to predict data. The research dataset used in this study is data on the average length of schooling in North Sumatra Province from 2015-2020, this dataset was taken from BPS North Sumatra. The data is then formed into 5 models, namely 2-10-1, 2-15-1, 2-20-1, 2-25-1, 2-30-1. -30-1 with an MSE value of 0.000430727. With these results the 2-30-1 architectural model gets the lowest score, so it can be concluded that the model can be used to predict the average length of schooling in North Sumatra Province.

Mushroom Production Prediction Model using Conjugate Gradient Algorithm Yosua Chandra Simamora; Solikhun Solikhun; Lise Pujiastuti; Mochamad Wahyudi
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Mushrooms are heterotrophic living things that act as saprophytes on dead plants. Mushrooms contain many important substances such as protein, amino acids, lysine, histidine, etc. Mushrooms tend to be better consumed than animal meat, even the content of lysine and histidine contained in mushrooms is greater than eggs. In recent years the volume of Mushroom Demand has increased, while production has decreased, especially on the island of Sumatra, namely in 2020 and 2021. Therefore, it is necessary to predict the estimated production of mushroom plants on the island of Sumatra so that the government on the island of Sumatra has clear data references to determine policies and make the right steps so that the production of mushroom plants on the island of Sumatra does not continue to decline. The method used in predicting is one of the ANN methods, namely the Conjugate Gradient Algorithm. The data used in this paper is Vegetable Crop Production data from 2014-2021 which was obtained from the website of the Central Statistics Agency. Based on this data, network architecture models such as 3-10-1, 3-15-1, 3-20-1, 3-25-1, 3-30-1, will be formed and defined. From the five models, training and testing values were obtained which showed that the most optimal architectural model was 3-10-1 with a Performance/MSE test value of 0.00055034. This value is the smallest of the 5 architectural models after the training and testing process. From this it can be concluded that this model can be applied to predict mushroom production on the island of Sumatra

Application of Neural Network Variations for Determining the Best Architecture for Data Prediction Mochamad Wahyudi; Firmansyah; Lise Pujiastuti; Solikhun
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 5 (2022): Oktober 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

This study focuses on the application and comparison of the epoch, time, performance/MSE training, and performance/MSE testing of variations of the Backpropagation algorithm. The main problem in this study is that the Backpropagation algorithm tends to be slow to reach convergence in obtaining optimum accuracy, requires extensive training data, and the optimization used is less efficient and has performance/MSE which can still be improved to produce better performance/MSE in this research—data prediction process. Determination of the best model for data prediction is seen from the performance/MSE test. This data prediction uses five variations of the Backpropagation algorithm: standard Backpropagation, Resistant Backpropagation, Conjugate Gradient, Fletcher Reeves, and Powell Beale. The research stage begins with processing the avocado production dataset in Indonesia by province from 2016 to 2021. The dataset is first normalized to a value between 0 to 1. The test in this study was carried out using Matlab 2011a. The dataset is divided into two, namely training data and test data. This research's benefit is producing the best model of the Backpropagation algorithm in predicting data with five methods in the Backpropagation algorithm. The test results show that the Resilient Backpropagation method is the best model with a test performance of 0.00543829, training epochs of 1000, training time of 12 seconds, and training performance of 0.00012667.

Peningkatan literasi digital remaja dalam masa PPKM level 4 Nurhasanah Halim; Susilawati Susilawati; Retno Dwigustini; Mochamad Wahyudi
Lumbung Inovasi: Jurnal Pengabdian kepada Masyarakat Vol. 7 No. 4 (2022): December
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/linov.v7i4.884

Literasi digital saat ini menjadi topik yang tengah menghangat diperbincangkan. Sayangnya banyak lapisan masyarakat yang belum mendapat pencerahan mengenai literasi digital, khususnya mereka yang berada di bawah lembaga keagamaan yang bersifat non-formal. Tujuan pengabdian pada masyarakat ini adalah untuk memperkenalkan sekaligus meningkatkan pemahaman literasi digital kepada siswa TPA dan Majlis Ta’lim Faizul Haq, Ciputat, Tangerang, di masa PPKM (Pemberlakuan Pembatasan Kegiatan Masyarakat) level 4. Metode penelitian yang digunakan adalah community-based research yang menekankan pada peningkatan atau perubahan positif mengenai literasi digital di masyarakat; dalam hal ini anggota majlis ta’lim dan TPA. Hasil penelitian ini menunjukkan adanya peningkatan literasi digital pada remaja anggota majlis taklim dan TPA di masa PPKM level 4. Selain itu, para remaja ini juga menunjukkan respon yang positif terhadap proses pengenalan literasi digital dalam bentuk pengabdian pada masyarakat ini. Karenanya, kegiatan pengenalan lebih lanjut mengenai literasi digital seyogyanya dilaksanakan secara berkesinambungan dalam rangka membekali remaja menghadapi era yang serba digital ini. Promoting Adolescent Digital Literacy in PPKM Level 4 Digital literacy is currently a trending topic of discussion. However, many levels of society have not received enlightenment regarding digital literacy, especially those who are under non-formal religious institutions. The purpose of this community service is to introduce and promote understanding of digital literacy to TPA and Majlis Ta'lim Faizul Haq students, Ciputat, Tangerang, during PPKM (Implementation of Restrictions on Social Activities) level 4. The research method employed is community-based research that emphasizes improvement or positive change. regarding digital literacy in society; in this case, the members of the ta'lim council and the TPA. The results of this study indicate that there is an increase in digital literacy among teenage members of the majlis taklim and TPA during PPKM level 4. In addition, these teenagers also show a positive response to the process of introducing digital literacy in the form of community service. Therefore, further introduction activities regarding digital literacy should be carried out continuously in order to equip teenagers to face this all-digital era.

Komparasi K-Means Clustering dan K-Medoids Clustering dalam Mengelompokkan Produksi Susu Segar di Indonesia Berdasarkan Nilai DBI Mochamad Wahyudi; Solikhun Solikhun; Lise Pujiastuti
Jurnal Bumigora Information Technology (BITe) Vol 4 No 2 (2022)
Publisher : Prodi Ilmu Komputer Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v4i2.2104

The purpose of this study was to find the optimal grouping from the comparison of the two methods in grouping fresh milk production using the K-Means algorithm and the K-Medoids algorithm. To find optimal grouping, the authors compare the grouping results by looking for the smallest DBI (Davies Bouldin Index) value. The data used in this study is data on fresh milk production in Indonesia which is sourced from the Indonesian Central Bureau of Statistics for 2018-2020. Evaluation of the DBI value for the K-Means Clustering algorithm is 0.094 and the DBI value for K-Medoids Clustering is 0.072. Therefore, grouping fresh milk production using the K-Medoids algorithm has better results than using the K-Means Clustering algorithm, because the K-Medoids Clustering algorithm has a smaller DBI value of 0.072. The benefit of this study is to obtain optimal clusters in classifying fresh milk in Indonesia to provide information to the government in increasing fresh production in Indonesia in the future.

Development of Quantum Circuit Architecture on Quantum Perceptron Algorithm for Classification of Marketing Bank Data　 Mochamad Wahyudi; Solikhun Solikhun
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i1.4526

The creation of quantum circuit architecture based on the quantum perceptron algorithm to classify marketing bank data is proposed in this work. A quantum circuit is a quantum gate made up of two quantum gates. Quantum bits are used in this study's computation. The primary proposed learning method was not ideal, which is the context of this study. The percentage of qubits measurement value is still 90.7 percent. It is essential to raise the value of the qubit rate. Using the IBM Quantum Experience quantum computer, researchers measured, trained, and tested the quantum circuit architecture. Bank marketing data from the UCI Machine Learning Repository was used. A quantum circuit architecture model results from this research the quantum circuit measurement results.

Co-Authors Abdurrachman, Qais Ade Budiman, Ade Adi Supriyatna Akbar, Habibullah Ali Haidir Alpha Ariani, Alpha Andri Amico Atrinawati, Lovinta Happy Azis, Munawar Abdul Azkia, Farah Diba Barreto Jose da Conceição Budiman, Ade Surya Dedi Triyanto Dedi Triyanto Dedi Triyanto Deni Kurniawan, Deni Dennis Gunawan, Dennis DENY KURNIAWAN Deny Kurniawan Dewi, Revinta Arrova Dimas Trianda Doni Purnama Alam Syah, Doni Purnama Dwi Arum Ningtyas Efendi, Syahril Faiz Djarot, Raihan Jamal Fajar Akbar Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Freshtiya Beby Larasati Fristi Riandari Fuad Nur Hasan Ganda Wijaya Ganda Wijaya, Ganda Givan, Bryan Hartama, Dedy Hengki Tamando Sihotang Herman Mawengkang Husain Husain Husain Husain Ihsan Daulay Ikhwan, Subaiki Imam Sutoyo Indra Chaidir, Indra Khoirun Nisa KHOIRUN NISA Kotjek, Rafie Laksono, Andriansyah Tri Lestari Yusuf Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Merio Hengki Muhammad Safii Muhammad Zarlis Mukhtar, Mukhneri Noviyanto Nurajijah Nurajijah Nurhasanah Halim Oktaviany, Venny Pricillia Pujiastuti , Lise Pujiastuti, Lise Rachmat Adi Purnama Rahmansyah Siregar, Muhammad Rani, Maulidina Cahaya Retno Dwigustini Reynaldi , Reynaldi Rifani Haikal Riska Aryanti Riski Wulandari Rugaiyah Safii Safii Sfenrianto Sfenrianto Siregar, Muhammad Rahmansyah Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun, Solikhun SUMANTO Sumanto Sumanto Sumanto, Sumanto Sunu Sugi Arso Susilawati Susilawati Sutarman Sutarman Syarifah Putri Agustini Tantrisna, Ellen Vinsensia, Desi Wijaya, Filzah Yahya Mara Ardi Yosua Chandra Simamora Yudha, Satria Wira Yuni Eka Achyani, Yuni Eka Zidan, Muhammad

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