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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Technology and Computer Science JAST : Jurnal Aplikasi Sains dan Teknologi Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika

Imam Cholissodin

Universitas Brawijaya

Author-ID : 437952

Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Other

Published : 42 Documents Claim Missing Document

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Articles

Title

Selection and Recommendation Scholarships Using AHP-SVM-TOPSIS Putra, M Gilvy Langgawan; Ariyanti, Whenty; Cholissodin, Imam
Journal of Information Technology and Computer Science Vol. 1 No. 1: June 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. Gerakan Nasional Orang Tua Asuh Scholarship offers a number of scholarship packages. As there are a number of applicants, a system for selection and recommendation is required. we used 3 methods to solve the problem, the methods are AHP for feature selection, SVM for classification from 3 classes to 2 classes, and then TOPSIS give a rank recommendation who is entitled to receive a scholarship from 2 classes. In testing threshold for AHP method the best accuracy 0.01, AHP selected 33 from 50 subcriteria. SVM has highest accuracy in this research is 89.94% with Sequential Training parameter are Î» =0.5, constant of Î³ =0.01 , Îµ = 0.0001, and C = 1. Keywords: Selection, Recommendation, Scholarships, AHP-SVM-TOPSIS

Review: A State-of-the-Art of Time Complexity (Non-Recursive and Recursive Fibonacci Algorithm) Cholissodin, Imam; Riyandani, Efi
Journal of Information Technology and Computer Science Vol. 1 No. 1: June 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. Solving strategies in the computation the time complexity of an algorithm is very essentials. Some existing methods have inoptimal in the explanations of solutions, because it takes a long step and for the final result is not exact, or only limited utilize in solving by the approach. Actually there have been several studies that develop the final model equation Fibonacci time complexity of recursive algorithms, but the steps are still needed a complex operation. In this research has been done several major studies related to recursive algorithms Fibonacci analysis, which involves the general formula series, begin with determining the next term directly with the equation and find the sum of series also with an equation too. The method used in this study utilizing decomposition technique with backward substitution based on a single side outlining. The final results show of the single side outlining was found that this technique is able to produce exact solutions, efficient, easy to operate and more understand steps. Keywords: Time Complexity, Non-Recursive, Recursive, Fibonacci Algorithm

Optimizing SVR using Local Best PSO for Software Effort Estimation Novitasari, Dinda; Cholissodin, Imam; Mahmudy, Wayan Firdaus
Journal of Information Technology and Computer Science Vol. 1 No. 1: June 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. In the software industry world, itâ€™s known to fulfill the tremendous demand. Therefore, estimating effort is needed to optimize the accuracy of the results, because it has the weakness in the personal analysis of experts who tend to be less objective. SVR is one of clever algorithm as machine learning methods that can be used. There are two problems when applying it; select features and find optimal parameter value. This paper proposed local best PSO-SVR to solve the problem. The result of experiment showed that the proposed model outperforms PSO-SVR and T-SVR in accuracy. Keywords: Optimization, SVR, Optimal Parameter, Feature Selection, Local Best PSO, Software Effort Estimation

Optimization of Healthy Diet Menu Variation using PSO-SA Cholissodin, Imam; Dewi, Ratih Kartika
Journal of Information Technology and Computer Science Vol. 2 No. 1: June 2017
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. Optimal healthy diet in accordance with the allocation of cost needed so that the level of nutritional adequacy of the family is maintained. The problem of optimal healthy diet (based on family budget) can be solved with genetic algorithm. The algorithm particle swarm optimization (PSO) has the same effectiveness with genetic algorithm but PSO is superior in terms of efficiency, PSO algorithm has a lower complexity than genetic algorithm. However, genetic algorithms and PSO have a problem of local optimum because these algorithm associated with random numbers. To overcome this problem, PSO algorithm will be improved by combining it with simulated annealing algorithm (SA). Simulated annealing algorithm is a numerical optimization algorithms that can avoid local optimal. From our results, optimal parameter for PSO-SA are popsize 280, crossover rate 0.6, mutation rate 0.4, first temperature 1, last temperature 0.2, alpha 0.9, and generation size 100.Keywords: PSO, SA, optimization, variation, healthy diet menu.

Invigilator Examination Scheduling using Partial Random Injection and Adaptive Time Variant Genetic Algorithm Seisarrina, Maulidya Larasaty; Cholissodin, Imam; Nurwarsito, Heru
Journal of Information Technology and Computer Science Vol. 3 No. 2: November 2018
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. Examination for every semester is a routine activity for faculties to do. Academic division of faculty responsible to make the schedule for every subject that is going to be tested, and prepare rooms for the test. Meanwhile, coordinators of invigilator committee responsible to make the schedule in FILKOM UB. This research focuses on scheduling the invigilatorâ€™s schedule in FILKOM UB. Scheduling with conventional method or manual takes much time because it needs to consider many rules on scheduling it. That is the reason why we need a system to schedule it. The purpose of making this system is to help the committee to schedule their invigilatorâ€™s time line. This research offers a concept of solution from using genetic algorithm. Genetic algorithm is an algorithm to find the optimum solution. The system of scheduling that use this genetic algorithm method can produce invigilatorâ€™s schedule that is having the least troubles on the arrangement. The data that is used in this research is the final testâ€™s schedule of the odd semester in 2015/2016, lecturer and the employeeâ€™s data of FILKOM UB. The optimal genetic parameter that is obtained from the test consists of 900 population, 3000 generations, and a combination of crossover rate and mutation rate value which are 0,4 and 0,6. The system that is built in making this invigilatorâ€™s schedule is close to the optimum point with 0,877 fitness value.Keywords: scheduling, invigilator, partial random injection, adaptive time variant genetic algorithm.

Prediction of Rainfall using Simplified Deep Learning based Extreme Learning Machines Cholissodin, Imam; Sutrisno, Sutrisno
Journal of Information Technology and Computer Science Vol. 3 No. 2: November 2018
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Prediction of rainfall is needed by every farmer to determine the planting period or for an institution, eg agriculture ministry in the form of plant calendars. BMKG is one of the national agency in Indonesia that doing research in the field of meteorology, climatology, and geophysics in Indonesia using several methods in predicting rainfall. However, the accuracy of predicted results from BMKG methods is still less than optimal, causing the accuracy of the planting calendar to only reach 50% for the entire territory of Indonesia. The reason is because of the dynamics of atmospheric patterns (such as sea-level temperatures and tropical cyclones) in Indonesia are uncertain and there are weaknesses in each method used by BMKG. Another popular method used for rainfall prediction is the Deep Learning (DL) and Extreme Learning Machine (ELM) included in the Neural Network (NN). ELM has a simpler structure, and non-linear approach capability and better convergence speed from Back Propagation (BP). Unfortunately, Deep Learning method is very complex, if not using the process of simplification, and can be said more complex than the BP. In this study, the prediction system was made using ELM-based Simplified Deep Learning to determine the exact regression equation model according to the number of layers in the hidden node. It is expected that the results of this study will be able to form optimal prediction model.Keywords: prediction, rainfall, ELM, simplified deep learning

Audit System Development for Government Institution Documents Using Stream Deep Learning to Support Smart Governance Cholissodin, Imam; Soebroto, Arief Andy; Sutrisno, Sutrisno
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Document audit system is a means of evaluating documents on the results of delivering information, administrative documentary evidence in the form of texts or others. Currently, these activities become easier with the presence of computer technology, smartphones, and the internet. One of the examples is the documents created by various government institutions whether local, city and central government. The instance is online-published documents that are shaded by certain government institutions. Before the documents are published or used as an archive or authentic evidence for reporting or auditing activities, the documents must go through the editing stage to correct if there are errors and deficiencies such as spelling errors or incomplete information. In the editing process, however, a person may not be able to escape from making mistakes that result in the existence of writing errors after the editing process before the submission. Word spelling mistakes can change the meaning of the conveyed knowledge and cause misunderstanding of information to the readers, especially for assessors or the audit team. Based on the problem, the researcher intends to assist the work of the audit preparation team in document analysis by proposing a system capable of detecting word spelling errors using the Dictionary Lookup method from Information Retrieval (IR) and Natural Language Processing (NLP) science combined with Stream Deep Learning algorithms. Dictionary Lookup method is considered effective in determining the spelling of words that are true or false based on Lexical Resource. In addition, String Matching method that has been developed can correct word-writing errors correctly and quickly.Keywords: spelling mistake detection, dictionary lookup, audit of government institution documents, stream deep learning

Development of Big Data App for Classification based on Map Reduce of Naive Bayes with or without Web and Mobile Interface by RESTful API Using Hadoop and Spark Cholissodin, Imam; Seruni, Diajeng Sekar; Zulqornain, Junda Alfiah; Hanafi, Audi Nuermey; Ghofur, Afwan; Alexander, Mikhael; Hasan, Muhammad Ismail
Journal of Information Technology and Computer Science Vol. 5 No. 3: Desember 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Big Data App is a developed framework that we made based on our previous project research and we have uploaded it on github, which is developing lightweight serverless both on Windows and Linux OS with the term of EdUBig as Open Source Hadoop Distribution. In this study, the focus is on solving problems related to difficulties in building a frontend and backend model of a Big Data application which by default only runs scripts through consoles in the terminal. This will be quite a tribulation for the end users when the Big Data application has been released and mass produced to general users (end users) and at the same time how the end users test the performance of the Map Reduce Naive Bayes algorithm used in several datasets. In accordance to these problems, we created the Big Data App framework to make the end users, especially developers, feel easier to build a Big Data application by integrating the frontend using the Web App from Django framework and Mobile App Native, while for the backend, we use Django framework that is able to communicate directly with the script either hadoop batch, streaming processing or spark streaming very easily and also to use the script for pig, hive, web hdfs, sqoop, oozie, etc. the making of which is extremely fast with reliable results. Based on the test results, a very significant result in the ease of data computation processing by the end users and the final results showing the highest classification accuracy of 88.3576% was obtained.Keywords: big data, map reduce of naive bayes, serverless, web and mobile app, restful api, django framework

Co-Authors ., Maryamah A. N., Aditya Yudha Achmad Jafar Al Kadafi, Achmad Jafar Afida, Latansa Nurry Izza Agnes Rossi Trisna Lestari, Agnes Rossi Ahmad Afif Supianto AJI, IBRAHIM Alaydrus, Zaien Bin Umar Alexander, Mikhael Anang Hanafi, Anang Andy Soebroto, Arief Ardisa Tamara Putri, Ardisa Tamara Arief Andy Soebroto Arniantya, Raissa Asikin, Moh. Fadel Bayu Rahayudi Brigitta Ayu Kusuma Wardhany, Brigitta Ayu Kusuma Budi Darma Setiawan Caesar, Canny Amerilyse Candra Dewi Dahnial Syauqy Daisy Kurniawaty, Daisy Daneswara Jauhari, Daneswara Destyana Ellingga Pratiwi Dharmawan, Muhammad Robby Dinda Novitasari, Dinda Dyan Putri Mahardika, Dyan Putri Efi Riyandani, Efi Evanita, Felicia Marvela Fauzi, Handika Agus Fauziyah, Aprilia Nur Firmanda, Dwi Ady Firmansyah, Ilham Fitra Abdurrachman Bachtiar Ghofur, Afwan H, Luqman Hakim Hanafi, Audi Nuermey Harahap, Syazwandy Hasan, Muhammad Ismail Heru Nurwarsito Hidayatullah, Adam Syarif Husin Muhamad, Husin Idham Triatmaja, Idham Irawan, Fathony Teguh Irma Lailatul Khoiriyah, Irma Lailatul Istiana Rachmi, Istiana Jonemaro, Eriq Muhammad Adams Jupiyandi, Sisco Kartikasari, Oktavianis Ksatria, Willyan Eka Kurnianingtyas, Diva Lailil Muflikhah Latifah Hanum Listiya Surtiningsih, Listiya Luqyana, Wanda Athira M Gilvy Langgawan Putra, M Gilvy Langgawan Maâ€™rufi, Muhammad Rizal Mahardika, Guedho Augnifico Maria Tenika Frestantiya, Maria Tenika Mayangsari, Lintang Resita Muhammad Fhadli, Muhammad MUHAMMAD SYAFIQ Muzayyani, Muhammad Farid Najib, Mochammad Ainun Nanda Agung Putra, Nanda Agung Nur Firra Hasjidla, Nur Firra Nurul Hidayat Pardede, Andreas Prabowo, Dhimas Anjar Pramana, Firadi Surya Prasojo, Cahyo Adi Pratama, Andhica R, Bariq Najmi Rahardian, Brillian Aristyo Rahman, Edy Randy Cahya Wihandika Ratih Kartika Dewi Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rina Christanti, Rina Rizaldi, Hilmi Ilyas Robbana, Siti Saâ€™rony, Akhmad Salsabila, Rona Saniputra, Fadhil Rizqullah Santoso, Nurudin Sari, Selly Kurnia Satria, Arrofi Reza Seisarrina, Maulidya Larasaty Septino, Fernando Seruni, Diajeng Sekar Sugianto, Nur Afifah Sukmawati, Annisa Sunaryo, Aryeswara Sutrisno . Sutrisno, Sutrisno Tedjasulaksana, Jeffrey Junior Tusty Nadia Maghfira, Tusty Nadia Umi Rofiqoh, Umi Uswatun Hasanah Vivien Fathuroya, Vivien Wahyuditomo, Kukuh Wicaksono Wayan Firdaus Mahmudy Whenty Ariyanti Winda Cahyaningrum, Winda Winda Estu Nurjanah, Winda Estu Wulandari, Ulfa Lina Yuniarsa, M Fahrul Alam Yusuf Priyo Anggodo, Yusuf Priyo Zakiyyah, Rizka Husnun Ziya El Arief, Ziya El Zulianur Khaqiqiyah, Zulianur Zulqornain, Junda Alfiah

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