Article Per Year (5 Year)
p-Index From 2021 - 2026
6.951
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 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) ILKOM Jurnal Ilmiah 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 International Transactions on Artificial Intelligence (ITALIC) Jurnal Teknoinfo
Mochamad Wahyudi
Universitas Bina Sarana Informatika
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

Published : 82 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 82 Documents
Search

 3   4   5   6   7 
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

Abstract

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.
Fletcher-reeves algorithm for predicting the quantity of production tomato plants in indonesia Rifani Haikal; Mochamad Wahyudi; Lise Pujiastuti; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 3 (2022): November: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v11i3.47

Abstract

The growth of Indonesia's tomato plants continues to increase, and this increase needs to be balanced, according to data from 2015 to 2020. Tomatoes should be used all the time, even in Indonesia. Tomatoes are not only edible but also good for your health and appearance. For the government and various conferences to include this as a point of view in dealing with this problem, it is important to look at the amount of tomato production in Indonesia. Data from the Central Statistics Agency was used to obtain statistics on tomato plant cultivation in Indonesia from 2015 to 2020. This data is solved using the Fletcher-Reeves algorithm using architectural models 2-10-1, 2-20-1, 2-30-1, and 2-35-1. Model 2-10-1 is the best architectural model to predict the amount of tomato production compared to other models, according to the training and testing results of the four models. Model 2-10-1 is used to measure the accuracy of the Fletcher-Reeves method, with MSE Training set at 0.00008463 and MSE Testing at 0.0006094.
Implemetasi algoritma fletcher-reeves dalam menganalisa nilai ekspor menurut golongan sitc Riski Wulandari; Mochamad Wahyudi; Lise Pujiastuti; Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 3 (2022): November: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v11i3.48

Abstract

Indonesia has a lot of natural resources, so Indonesia uses them by conducting trade activities between countries. Export is a movement to sell or send goods from within the country to abroad. Conjugateigradient Fletcher-Reeves Algorithm According to some references, it is an appropriate development technique compared to the backpropagation strategy because this strategy can speed up the preparation time to arrive at the minimum convergence value. Furthermore, this research shows whether the algorithm performs well and can provide productive assembly results when used to solve problems because the value corresponds to the Standard International Trade Classification (SITC) class. The prediction models used are 5-10-1, 5-15-1, 5-20-1, 5-25-1 and 5-30-1. MSE of 0.00287273, the minimum among the other four models. The model can be used because it produces a fast combination and a fairly short period
A stochastic approach for evaluating production planning efficiency under uncertainty Mochamad Wahyudi; Hengki Tamando Sihotang; Syahril Efendi; Muhammad Zarlis; Herman Mawengkang; Desi Vinsensia
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5542-5549

Abstract

Planning production is an essential component of the decision-making process, which has a direct bearing on the effectiveness of production systems. This study’s objective is to investigate the efficiency performance of decision-making units (DMU) in relation to production planning issues. However, the production system in a manufacturing environment is frequently subject to uncertain situations, such as demand and labor, and this can have an effect not only on production but also on profit. The robust stochastic data envelopment analysis model was proposed in this study with maximizing the number of outputs as the objective function thus means of handling uncertainty in input and output in production planning problems. This model, which is based on stochastic data envelopment analysis and a method of robust optimization, was proposed with the intention of providing an efficient plan of production for each DMU of stage production. The model is applied to small and medium-sized businesses (SMEs), with inputs consisting of the cost of labor, the number of customers, and the quantity of raw materials, and the output consisting of profit and revenue. It has been demonstrated through implementation that the proposed model is both efficient and effective.
Robust mathematical model for supply chain optimization: A comprehensive study Lise Pujiastuti; Mochamad Wahyudi; Barreto Jose da Conceição; Fristi Riandari
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 2 (2023): June : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v6i2.137

Abstract

This research provides a comprehensive review of existing literature and research on supply chain optimization, aiming to capture the advances made in the field and identify emerging perspectives. Supply chain optimization plays a vital role in improving operational efficiency, reducing costs, and enhancing customer satisfaction. By analyzing a wide range of studies, this review examines various approaches, models, and techniques used in supply chain optimization, including mathematical programming, stochastic programming, simulation, and metaheuristic algorithms. The review also encompasses key aspects such as demand forecasting, inventory management, production planning, transportation, and distribution network design. Furthermore, the study investigates recent trends, such as incorporating sustainability considerations, addressing uncertainties and risks, and utilizing real-time data and decision support systems. By identifying the gaps and limitations in the existing research, this review sets the stage for future investigations and provides valuable insights for researchers and practitioners seeking to advance supply chain optimization efforts. The findings of this review contribute to enhancing the understanding of supply chain optimization and provide a roadmap for future research directions in this dynamic and critical field
The Digital Economy's Use of Big Data Mochamad Wahyudi; Vivi Meilinda; Alfiah Khoirunisa
International Transactions on Artificial Intelligence Vol. 1 No. 1 (2022): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i1.167

Abstract

The function of Big Data technology and Data Science in the contemporary digital economy is examined in this article. According to the author, large and medium-sized businesses in the retail and service sectors have a greater interest in utilizing them. Banks, mobile operators, and major manufacturing firms actively employ these technologies (Artificial Intelligence) to evaluate data on equipment failures and minimize downtime, which enables cost-reduction. Big Data technology serves as a liquid product and a prerequisite for boosting business profitability through individualized customer care and predictive analytics. It is crucial to ensure the formation of unique data exchanges and legalize a single definition of big data for the modern digital economy.
COMBINATION OF LOGARITHMIC PERCENTAGE CHANGE AND GREY RELATIONAL ANALYSIS FOR BEST ADMINISTRATION STAFF SELECTION Sumanto Sumanto; Mochamad Wahyudi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 1 (2024): JITK Issue August 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i1.5564

Abstract

The best administrative staff are individuals who are able to maintain the smooth operation of the organization with high efficiency and precision. One of the main problems is subjectivity in assessment that can cause dissatisfaction among employees. Sometimes, assessments are based more on personal relationships than objective performance, thus creating a sense of unfairness. The purpose of this study, using a combination of LOPCOW and GRA in determining the best administrative staff to develop a holistic and data-driven evaluation approach for the optimal administrative staff selection process. This process involves a comprehensive assessment based on various criteria, including work efficiency, accuracy, multitasking ability, and excellence in communication and problem solving. LOPCOW provides a strong objective basis by considering significant changes in performance data through logarithmic percentage changes, while GRA helps in identifying and understanding the relationship of similarities and differences between alternatives based on given criteria. By integrating these two methods, organizations can combine the advantages of LOPCOW's objectivity with the power of GRA's relational comparison analysis, resulting in a more comprehensive and accurate performance evaluation. The results of the ranking of the selection of the best administrative staff show that the first best administrative staff was obtained by Staff Name AH with a GRG value of 0.1666, the second best administrative staff was obtained by Staff Name RW with a GRG value of 0.1569, the third best administrative staff was obtained by Staff Name ES with a GRG value of 0.1266.
Enhancing Multiplication Skills: The Way Modeling Method and Mathchess Games in Educational Practice Pujiastuti, Lise; Wahyudi, Mochamad
International Journal of Enterprise Modelling Vol. 17 No. 3 (2023): September: Enterprise Modelling
Publisher : International Enterprise Integration Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/emod.v17i3.78

Abstract

This research delves into the exploration of an innovative educational approach aiming to enhance multiplication skills among students. The study investigates the combined efficacy of the Way Modeling Method, utilizing visual representations, and Mathchess games, a gamified learning approach, in improving multiplication proficiency. Through a quasi-experimental design involving a control and experimental group, elementary school students aged 8 to 10 were exposed to either traditional instruction or the combined intervention. Pre-tests and post-tests were administered to measure changes in multiplication skills, accompanied by qualitative assessments through participant feedback and observations. The results unveiled significant improvements in the experimental group, indicating a substantial enhancement in accuracy, comprehension, engagement, and confidence in solving multiplication problems. Comparative analysis between groups highlighted the distinct effectiveness of the combined methodology, aligning with cognitive learning theories and emphasizing the potential for dynamic and interactive pedagogical approaches in fostering mathematical skills. These findings present implications for educational practice, advocating for the integration of diverse teaching methodologies catering to varied learning styles. Furthermore, they pave the way for future research in optimizing these approaches and exploring their broader applications in mathematical education.
Comparison of Supervised Learning Classification Methods on Accreditation Data of Private Higher Education Institutions Noviyanto; Wahyudi, Mochamad; Sumanto, Sumanto
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 1 (2024): March 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i1.3306

Abstract

This research aims to analyze and compare supervised learning classification methods using a case study of accreditation data for private higher education institutions within the LLDikti Region III contained in BAN-PT. In addition, this research also uses Weka machine learning software in its calculations. The initial step taken is to prepare the software used for supervised learning analysis, then pre-processing the data, namely labeling data that has a categorical data type, after that determining data for testing data. The next step is to test each classification method. The methods used for comparison are logistic regression, K-nearest neighbor, naive bayes, super vector machine, and random forest. Based on the calculation results, the Kappa Statistic and Root mean squared error values obtained are 1 and 0 for the logistic regression method, 0.979 and 0.0061 for the K-nearest neighbor method, 1 and 0.2222 for the super vector machine method, 0.969 and 0.0341 for the naive bayes method, 1 and 0 for the decision tree method, and 0.5776 and 0.1949 for the random forest method, respectively. The logistic regression and decision tree methods in this study get Kappa Statistic and Root mean squared error values of 1 and 0 respectively so that they are said to be good and acceptable, thus the two classification methods are the most appropriate methods and are considered to have the highest accuracy.
Penerapan Metode Rapid Application Development Dalam Pengembangan Aplikasi Persediaan Material Panel Listrik Berbasis Web Azis, Munawar Abdul; Wahyudi, Mochamad; Aryanti, Riska
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 2 (2023): November 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v4i2.2496

Abstract

PT Indomitra Global is a company engaged in electrical contracting services and provides various types of electrical panels needed by clients. Electrical panels require many important materials, for example mcb, sockets, cables, and many other important components. The material inventory system carried out at PT Indomitra Global still uses a manual method in the material inventory system. This process has several obstacles, namely not having a centralized database that makes material inventory data vulnerable to loss and there are often differences in the suitability of the amount of material in the warehouse with the amount in Microsoft Excel, because data management is still not easy enough and due to human error or input errors. On the basis of this problem, a web-based material inventory application was made using the Rapid Application Development (RAD) method. The material inventory system produced in this study is able to handle material data management which previously was still not easy enough to do, such as searching for data, managing incoming and outgoing material transaction data and making it easier to generate incoming and outgoing material reports based on time periods
Co-Authors Abdurrachman, Qais Ade Budiman, Ade Adi Supriyatna Akbar, Habibullah Alfiah Khoirunisa 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 Gerhard-Wilhelm Weber 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 Lise Pujiastuti Merio Hengki Muhammad Safii Muhammad Zarlis Mukhtar, Mukhneri Munawar Abdul Azis 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 Sintagel br Sianipar, Imeldi Siregar, Muhammad Rahmansyah Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun, Solikhun Sumanto Sumanto Sunu Sugi Arso Susilawati Susilawati Sutarman Sutarman Syarifah Putri Agustini Alkadri Tantrisna, Ellen Vinsensia, Desi Vivi Meilinda Wijaya, Filzah Yahya Mara Ardi Yosua Chandra Simamora Yudha, Satria Wira Yuni Eka Achyani, Yuni Eka Zidan, Muhammad