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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Bulletin of Electrical Engineering and Informatics Jurnal Infinity Journal of Telematics and Informatics SAMUDERA Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Jurnal Teknologi Informasi dan Komunikasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Jurnal Inotera MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JISTech (Journal of Islamic Science and Technology) Building of Informatics, Technology and Science Jurnal Mantik MES: Journal of Mathematics Education and Science Jurnal Varian International Journal of Advances in Data and Information Systems Computer Science and Information Technologies Randwick International of Social Science Journal Journal of Research in Mathematics Trends and Technology Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Journal for Lesson and Learning Studies International Journal of Humanities Education and Social Sciences Jurnal MathEducation Nusantara International Journal of Community Service Implementation Jurnal Infinity

Herman Mawengkang

Faculty Of Matthematics And Natural Science Universitas Sumatera Utara, Medan, 20155, Indonesia

Author-ID : 2378804

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Analisis Accelerated Learning Pada Algoritma Backpropagation Menggunakan Adaptive Learning Rate Ermawati, Ermawati; Nababan, Erna Budhiarti; Mawengkang, Herman
SAMUDERA Vol 8, No 1 (2014)
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar

Jaringan syaraf tiruan backpropagation merupakan algoritma pembelajaran yang terawasi dimana output dari jaringan dibandingkan dengan target yang diharapkan sehingga diperoleh error output. Banyak model pembelajaran yang menggunakan algoritma backpropagation. Namun algoritma backpropagation mempunyai keterbatasan yaitu laju konvergensi yang cukup lambat. Pada penelitian ini penulis menambahkan parameter learning rate secara adaptif pada setiap iterasi dan koefisien momentum untuk menghitung proses perubahan bobot. Dari hasil simulasi komputer maka diperoleh perbandingan antara algoritma backpropagation standar dengan backpropagation adaptive learning. Untuk algoritma backpropagation standar kecepatan konvergensi mencapai 1000 epoch dengan nilai Mean Square Error (MSE) yang dihasilkan adalah 0,00044 sedangkan untuk algoritma backpropagation adaptive learning hanya 72 epoch dengan nilai Mean Square Error (MSE) yang dihasilkan 0.0000036. Hal ini menunjukkan bahwa algoritma backpropagation adaptive learning lebih cepat mencapai konvergensi daripada algoritma backpropagation standar.

Uncertainty Ontology for Module Rules Formation Waterwheel Control Azmi, Zulfian -; Nasution, Mahyuddin K. M.; Mawengkang, Herman; Zarlis, M
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14188

Implementation of Uncertainty model has not given maximum result in forming rule on an inference of a case. For testing to determine whether water quality is high, medium and low. The input variables used are temperature, pH, salinity and Disolved Oxygen. Testing is done by looking at the water turbidity change in the shrimp pond, to determine the water quality. Its water quality determines in the control module of the waterwheel rotation.Rolling the waterwheel moves quickly if pond water quality is low, moving slowly if water quality is medium and immobile if water quality is good. And the establishment of the rule with the approach of knowledge of Ontology to determine the relation between several variables (temperature, Ph, Disolved Oxygen and salinity). Each variable is set to its certainty value in the form of fuzzy value. Next is determined the relation of the four variables for the formation of rule.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14188

Perbandingan Algoritma Stochastic Gradient Descent dan Naïve Bayes Pada Klasifikasi Diabetic Retinopathy Hadistio, Ryan Rinaldi; Mawengkang, Herman; Zarlis, Muhammad
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 1 (2022): Januari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i1.3426

The purpose of this research is to compare the performance of the Stochastic Gradient Descent and Naïve Bayes algorithms in classifying Diabetic Retinopathy. Diabetic retinopathy is a complication of diabetes that causes damage to the retina of the eye. These disturbances can be detected by early detection through data extracted from eye images. This research uses source data from the UCI Machine Learning Repository, namely Diabetic Retinopathy Debrecen, totaling 1,151 data records with 19 attributes consisting of 18 attributes and 1 target attribute. The validation test uses the Cross Validation method with a total of 10 k. From the comparison of the two proposed methods, the Stochastic Gradient Descent algorithm produces an average test accuracy of 70.16%, while Naïve Bayes produces an average accuracy of 56.74%. From the comparison of the two algorithms, the Stochastic Gradient Descent algorithm is known to be superior in classifying the Diabetic Retinopathy Debrecen Dataset.

Analysis of earthquake hazards prediction with multivariate adaptive regression splines Dadang Priyanto; Muhammad Zarlis; Herman Mawengkang; Syahril Efendi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2885-2893

Earthquake research has not yielded promising results, either in the form of causes or revealing the timing of their future events. Many methods have been developed, one of which is related to data mining, such as the use of hybrid neural networks, support vector regressor, fuzzy modeling, clustering, and others. Earthquake research has uncertain parameters and to obtain optimal results an appropriate method is needed. In general, several predictive data mining methods are grouped into two categories, namely parametric and non-parametric. This study uses a non-parametric method with multivariate adaptive regression spline (MARS) and conic multivariate adaptive regression spline (CMARS) as the backward stage of the MARS algorithm. The results of this study after parameter testing and analysis obtained a mathematical model with 16 basis functions (BF) and 12 basis functions contributing to the model and 4 basis functions not contributing to the model. Based on the level of variable contribution, it can be written that the epicenter distance is 100 percent, the magnitude is 31.1 percent, the location temperature is 5.5 percent, and the depth is 3.5 percent. It can be concluded that the results of the prediction analysis of areas in Lombok with the highest earthquake hazard level are Malaka, Genggelang, Pemenang, Tanjung, Tegal Maja, Senggigi, Mangsit. Meninting, and Malimbu.

THE DIFFERENCE OF STUDENTS’ ACHIEVEMENT IN MATHEMATICS BY USING GUIDED-DISCOVERY LEARNING MODEL AND COOPERATIVE LEARNING MODEL JIGSAW TYPE Anna Angela Sitinjak; Herman Mawengkang
Jurnal Infinity Vol 7, No 1 (2018): Volume 7 Number 1, INFINITY
Publisher : IKIP Siliwangi and I-MES

The type of this study is a quasi-experiment study with its purpose to know any difference in students’ achievement in mathematics which using the model of guided discovery learning with cooperative learning model JIGSAW type. The population of this study is all students in SMA N 3 P. Siantar. The sampling technique applied was cluster random sampling. The experimental class I that chosen is X-1 consisted of 36 students, meanwhile, the experimental class II that chosen is X-6 consisted of 36 students. The instrument used to measure the students’ mathematics achievement was an essay test. The normality test used was Lilliefor’s test, get that data is normal and the homogeneity test by using Fisher test, get that data is homogeny. The data analysis technique was t-test at the level of significance α = 5%.The study result showed that there is the difference of students’ achievement in mathematics which using the guided discovery learning model with cooperative learning model JIGSAW type in grade X SMA N 3 P. Siantar where obtained tcalculation = 2.504 at a = 0.05 and ttable = t(0.975,70)= 1.995, then tcalculation = ttable

Neuron Model for Input Uncertainty Zulfian Azmi; Erna B N; Herman Mawengkang; M Zarlis
Journal of Telematics and Informatics Vol 6, No 2: June 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v6i2.

The application of the Neuron Network model has not given optimal results on learning with input values that are not binary, uncertain and varied. Variable inputs are not only 1 and 0 but allow between 0 and 1. and linguistic input and output and non-linear models. And the verification process for reviewing feasibility is reviewed from network, unit, behavior and procedural aspects. Further validation is done on the control module of the waterwheel rotation with dissolved oxygen input, water pH, salinity and water temperature varies. With such neuron models being the solution to varied and uncertain neuron models. The simulation is done withMatrix Laboratory software. Keywords: Neuron, Uncertainty, Waterwheel.

Heuristic algorithm for portfolio selection with minimum transaction lots . Afnaria; Herman Mawengkang
Proceedings of The Annual International Conference, Syiah Kuala University - Life Sciences & Engineering Chapter Vol 3, No 2 (2013): Engineering
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (171.531 KB)

Portfolio selection problem was first formulated in a paper written by Markowitz, where investment diversification can be translated into computing. Mean-variance model he introduced has been used and developed because of it’s limitations in the larger constraints found in the real world, as well as it’scomputational complexity which found when it used in large-scale portfolio. Quadratic programming model complexity given by Markowitz has been overcome with the development of the algorithm research. Theyintroduce a linear risk function which solve the portfolio selection problem with real constraints, i.e. minimum transaction lots. With the Mixed Integer Linear models, proposed a new heuristic algorithm that starts from the solution of the relaxation problems which allow finding close-to-optimal solutions. This algorithm is built on Mixed Integer Linear Programming (MILP) which formulated using nearest integer search method.

The Influence of the Approach of Realistic Mathematics and Motivation to Learn Mathematics Students On the Ability of Mathematical Modeling Students On Cubes and Beams in MTs Al-Majidiyah Herman Mawengkang
International Journal Of Humanities Education and Social Sciences (IJHESS) Vol 1 No 1 (2021): IJHESS - AGUSTUS 2021
Publisher : CV. AFDIFAL MAJU BERKAH

This study aims to determine: (1) Whether the increased ability of the mathematical modeling of students who are taught with Realistic Mathematics learning is higher than students taught by expository (2) Whether there is interaction between learning motivation of student learning on the ability of the mathematical modeling students (3) How the process of resolving questions related to the ability of the mathematical modeling of the students on the Realistic Mathematics learning and expository. This research is a quasi experiment with research population is all students of class VIII MTs Al-Majidiyah Chart Stone. The sample in this research is class VIII A and VIII class B. The instrument used consisted of: (1) test the ability of mathematical modeling with the material of the cube and beam (2) pieces of the Question. The Data in this research were analyzed by using descriptive statistical analysis, analysis and parametric statistics. Statistical analysis of data was done with the t test analysis and anova 2 lines. The results showed that: (1) Increase the ability of the mathematical modeling of students who are taught with learning PMR higher than students taught by expository (2) there is No interaction between the learning that is used with the learning motivation of the students to the ability of the mathematical modeling student (3) the Process of the completion of the answers of students who are taught by using learning model PMR is better compared to the expository

Data driven approach for stochastic data envelopment analysis Hengki Tamando Sihotang; Syahril Efendi; Muhammad Zarlis; Herman Mawengkang
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3660

Decision making based on data driven deals with a large amount of data will evaluate the process's effectiveness. Evaluate effectiveness in this paper is measure of performance efficiency of data envelopment analysis (DEA) method in this study is the approach with uncertainty problems. This study proposed a new method called the robust stochastic DEA (RSDEA) to approach performance efficiency in tackling uncertainty problems (i.e., stochastic and robust optimization). The RSDEA method develops to combine the stochastics DEA (SDEA) formulation method and Robust Optimization. The numerical example demonstrates the performance efficiency of the proposed formulation method, with the results performing confirmed that the efficiency value is 89%.

Co-Authors , Rahmad Sembiring Abi Rafdi Afdhaluzzikri, Afdhaluzzikri Afnaria, Afnaria Aghni Syahmrani Ahmad Zaki Mubarak, Ahmad Zaki Al Khowarizmi Anggi Anatasia Kinanti Anugreni, Fera Arjon Turnip Azmi, Zulfian - Badawi, Afif Buaton, Relita Budhiarti, Erna Christefa, Dea Christian Sinaga, Christian Dadang Priyanto Dedi Siswo Defri Muhammad Chan Deny Jollyta Efendi, Syahril Elly Rosmaini Elvina Herawati Ermawati Ermawati Erna B N Erna Budhiarti Nababan Fatma Sari Hutagalung Firmansyah Firmansyah Hadistio, Ryan Rinaldi Handayani, Sri Hartama, Dedy Hengki Tamando Sihotang Hengki Tamando Sihotang Heni Pujiastuti Heri Gustami Husain Husain Husain Husain Ignazio Ahmad Pasadana Iin Parlina Indah Purnama Sari Juanda Hakim Lubis Lestari, Valencya lili Tanti Lismardiana Lismardiana Lusi Herlina Siagian M Safii M Zarlis Mahyuddin K. M Nasution Mardiningsih Mardiningsih, Mardiningsih Marpongahtun Marwan Ramli Maya Silvi Lydia Mochamad Wahyudi Muhammad Arif Satria Nasution Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis, Muhammad Muliawan Firdaus Napitupulu, Fajrul Malik Aminullah Nuraini Nuraini Oktaviana Bangun Opim Salim Sitompul Ovirianti, Nurul Huda Pasaribu, Suhendri Poltak Sihombing Prandana, Randy Putri, Mimmy Sari Syah Rahman, Silvi Anggraini Resti, Lady Ichwana Roma Rezeki Ryan Rinaldi Hadistio Saib Suwilo Saib Suwilo Santoso, Ahmad Imam Sarif, Muhammad Irfan Sawaluddin Nasution Sawaluddin Sawaluddin, Sawaluddin Sugiyarmasto Sugiyarmasto Sutarman Sutarman Sutarman Sutarman Syahputra, Muhammad Romi Syahril Effendi Tanjung, Ilyas Tulus Tulus Tulus Tulus Vinsensia, Desi Weber, Gerhard Wilhelm Wiryanto Wiryanto Wisnu Irsandi Pratama Zakarias Situmorang Zarkasyi, Muhammad Imam Zarlis, M Zarlis, M Zoelkarnain Rinanda Tembusai Zulfian Azmi

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