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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Ilmiah Kursor Journal of Innovation and Applied Technology International Journal of Local Economic Governance Journal of Environmental Engineering and Sustainable Technology Jurnal Pembangunan dan Alam Lestari Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Knowledge Engineering and Data Science Jambura Law Review Indonesian Journal of Electrical Engineering and Computer Science International Journal of Engineering, Science and Information Technology Indexia Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Bulletin of Culinary Art and Hospitality Bulletin of Social Informatics Theory and Application Jurnal ilmiah teknologi informasi Asia Signal and Image Processing Letters
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Evolution strategies based coefficient of TSK fuzzy forecasting engine Nadia Roosmalita Sari; Wayan Firdaus Mahmudy; Aji Prasetya Wibawa
International Journal of Advances in Intelligent Informatics Vol 7, No 1 (2021): March 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v7i1.376

Abstract

Forecasting is a method of predicting past and current data, most often by pattern analysis. A Fuzzy Takagi Sugeno Kang (TSK) study can predict Indonesia's inflation rate, yet with too high error. This study proposes an accuracy improvement based on Evolution Strategies (ES), a specific evolutionary algorithm with good performance optimization problems. ES algorithm used to determine the best coefficient values on consequent fuzzy rules. This research uses Bank Indonesia time-series data as in the previous study. ES algorithm uses the popSize test to determine the number of initial chromosomes to produce the best optimal solution for this problem. The increase of popSize creates better fitness value due to the ES's broader search area. The RMSE of ES-TSK is 0.637, which outperforms the baseline approach. This research generally shows that ES may reduce repetitive experiment events due to Fuzzy coefficients' manual setting. The algorithm complexity may cost to the computing time, yet with higher performance.
HOG Feature Extraction and KNN Classification for Detecting Vehicle in The Highway Firnanda Al Islama Achyunda Putra; Fitri Utaminingrum; Wayan Firdaus Mahmudy
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.54050

Abstract

Autonomous car is a vehicle that can guide itself without human intervention. Various types of rudderless vehicles are being developed. Future systems where computers take over the art of driving. The problem is prior to being attention in an autonomous car for obtaining the high safety. Autonomous car need early warning system to avoid accidents in front of the car, especially the system can be used in the Highway location. In this paper, we propose a vision-based vehicle detection system for Autonomous car. Our detection algorithm consists of three main components: HOG feature extraction, KNN classifier, and vehicle detection. Feature extraction has been used to recognize an object such as cars. In this case, we use HOG feature extraction to detect as a car or non-car. We use the KNN algorithm to classify. KNN Classification in previous studies had quite good results. Car detected by matching about trining data with testing data. Trining data created by extract HOG feature from image 304 x 240 pixels. The system will produce a classification between car or non-car.
PENERAPAN ALGORITMA GENETIKA UNTUK KOMPRESI CITRA FRAKTAL Putu Indah Ciptayani; Wayan Firdaus Mahmudy; Agus Wahyu Widodo
Jurnal Ilmu Komputer Vol. 2, No. 1 April 2009
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (116.392 KB)

Abstract

Fractal image compression is one of compression techniques which produce a high compression ratio with good quality of result image. But this method has weakness is the time to compress image is too long because checking domain and range block is done by brute force method. Because of it, necessary to get approach with genetic algorithm which genetic algorithm is an appropriate approach for complex combinatorial problem. Genetic algorithm play role in searching the matching domain and range block. Experiment is done by use three crossover and mutation method, the size of range block is 4, mutation probability is 0.1, crossover probability is 0.5, 0.6, 0.7, 0.8, 0.9 and 1.0. Maximal size of generations are 500. The best result of compression image has ratio 75.01% with compression time is 10.7 second and MSE is 0.158839.
Detecting Emotion in Indonesian Tweets: A Term-Weighting Scheme Study Kuncahyo Setyo Nugroho; Fitra A. Bachtiar; Wayan Firdaus Mahmudy
Journal of Information Systems Engineering and Business Intelligence Vol. 8 No. 1 (2022): April
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.8.1.61-70

Abstract

Background: Term-weighting plays a key role in detecting emotion in texts. Studies in term-weighting schemes aim to improve short text classification by distinguishing terms accurately. Objective: This study aims to formulate the best term-weighting schemes and discover the relationship between n-gram combinations and different classification algorithms in detecting emotion in Twitter texts. Methods: The data used was the Indonesian Twitter Emotion Dataset, with features generated through different n-gram combinations. Two approaches assign weights to the features. Tests were carried out using ten-fold cross-validation on three classification algorithms. The performance of the model was measured using accuracy and F1 score. Results: The term-weighting schemes with the highest performance are Term Frequency-Inverse Category Frequency (TF-ICF) and Term Frequency-Relevance Frequency (TF-RF). The scheme with a supervised approach performed better than the unsupervised one. However, we did not find a consistent advantage as some of the experiments found that Term Frequency-Inverse Document Frequency (TF-IDF) also performed exceptionally well. The traditional TF-IDF method remains worth considering as a term-weighting scheme. Conclusion: This study provides recommendations for emotion detection in texts. Future studies can benefit from dealing with imbalances in the dataset to provide better performance. Keywords: Emotion Detection, Feature Engineering, Term-Weighting, Text Mining
CAMPUS SENTIMENT ANALYSIS E-COMPLAINT USING PROBABILISTIC NEURAL NETWORK ALGORITHM Mohammad Zoqi Sarwani; Wayan Firdaus Mahmudy
Jurnal Ilmiah Kursor Vol 8 No 3 (2016)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v8i3.88

Abstract

E-complaint is one of the technologies which is used to collect feedback from customers in the form of criticism and suggestions using electronic systems. For some companies or agencies, ecomplaint is used to provide better services to its customers. This study is aimed to perform sentiment analysis of an e-complaint service, with the case of Brawijaya University. There are three main stages for the proposed system, i.e. Text Preprocessing, Text Weighting, and PNN forthe classification. Tokenization, filtering, and stemming are done in the text preprocessing. Resulted text from the preprocessing stage is weighting using Term Inverse Document Frequent (TFIDF). To classify the negative or positive complaints, PNN are used in the last stage. For the experiments, 70 data are used as the training data, and 20 data are used as the testing data. The experimental results based on the combination of the number of training and testing dataset, showed that the accuracy achieved up to 90%.
OPTIMASI FUNGSI MULTI-OBYEKTIF BERKENDALA MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DENGAN PENGKODEAN REAL Wayan Firdaus Mahmudy; Muh. Arif Rahman
Jurnal Ilmiah Kursor Vol 6 No 1 (2011)
Publisher : Universitas Trunojoyo Madura

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

Abstract

Multi-objective optimization problem is difficult to be solved as its objectives generally conflict with each other and its solution is not in the form of a single solution but a set of solutions. Genetic algorithms (GAs) is one of meta heuristic algorithms that may be used to solve this problem. However, a standard GAs is easily trapped in local optimum areas and searching process rate will be lower around the optimum points. This paper proposes a GAs with an adaptive mutation rate to balance the exploration and exploitation on the search space. A simple rule has been developed to determine wheter the mutation rate is increased or decreased. If a significant improvment of the fitness value is not achieved, the mutation rate is increased to enable the GAs exploring search space and escaping the local optimum area. In contrast, the mutation rate is decreased if significant improvment of the fitness value is achieved. This mechanism guide the GAs to exploit the local search area. The experiments show that by using the adaptive mutation, the GAs will move faster toward a feasible search space and achieving solutions on sorter time.
AN IMPROVED SIMULATED ANNEALING FOR THE CAPACITATED VEHICLE ROUTING PROBLEM (CVRP) Farhanna Mari; Wayan Firdaus Mahmudy; Purnomo Budi Santoso
Jurnal Ilmiah Kursor Vol 9 No 3 (2018)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v9i3.178

Abstract

In the industrial sector, in order to increase the company's competitive profit and ratio, must be able to suppress as much expenditure as possible. Product distribution is one of the logistics processes in the industry which consumes the most costs. Products must be distributed to customers in different locations and also with varying requests. The problem belongs to Capacitated Vehicle Routing Problem (CVRP) that is considered as one of the complex combinatorial optimization problems included in the NP-Hard Problem category, which is a problem that requires difficult computation and a lot of time along with the increasing size of the problem data. So, in this study improvisation will be carried out in the form of modifying the simulated annealing method to solve the combinatorial problem so that the optimal distance in the case of distribution will be obtained. In addition, in this study a comparison will be made between basic simulated annealing and also improved simulated annealing. Based on the results of the research it is proven that Improved Simulated Annealing can provide a better solution.
PRE-PROCESSED LATENT SEMANTIC ANALYSIS FOR AUTOMATIC ESSAY GRADING Ruth Ema Febrita; Wayan Firdaus Mahmudy
Jurnal Ilmiah Kursor Vol 8 No 4 (2016)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v8i4.110

Abstract

In education, essay is considered as the best tool to evaluate student’s high order thinking and understanding. In the other hand, manual processing and grading essay answers by a teacher need much time and tending to subjectivity grading. Meanwhile automatic essay grading in e-learning system find the difficulties in comparing model or key answer to student’s answer because student’s can answer the question with so various way. That means a right answer also can be so various, for they have same semantic meaning. This paper proposed automatic essay grading using Latent Semantic Analysis. But before the texts being scored, they will be pre-processed using stop words removal and synonyms checking. Calibration process implemented for dealing with the various possible right answer and help to simplify the term matrix. Implementation of this approach using Java Programming Language and WordNet as lexical database for searching the synonyms of every given words. The accuracy obtained by this method is 54.9289%.
IMPROVED SIMULATED ANNEALING FOR OPTIMIZATION OF VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW) Wayan Firdaus Mahmudy
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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Abstract

IMPROVED SIMULATED ANNEALING FOR OPTIMIZATION OF VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW) Wayan Firdaus Mahmudy Department of Computer Science, University of Brawijaya (UB) Email: wayanfm@ub.ac.id Abstrak Vehicle routing proble with time windows (VRPTW) merupakan permasalahan optimasi kombinatorial yang banyak ditemui pada sistem distribusi permasalahan ini berkaitan dengan pengalokasian sejumlah kendaraan umum untuk melayani sejumlah konsumen, sejumlah konsumen mempunyai rentang waktu kesediaan yang berbeda dan harus dilayani dalam waktu tersebut. Paper ini memaparkan penggunaan metode simulated annealing yang diperkaya dengan beberapa fungsi khusus untuk menghasilkan solusi tetangga yang digunakan pada penelusuran are pencarian solusi dari VRPTW. Serangkaian percobaan menunjukkan bahwa simulated annealing yang diperkaya dengan fungsi-fungsi khusus dapat menghasilkan solusi yang baik dalam waktu rata-rata 82.29 detik. Kata kunci: Vehicle Routing Problem with Time Windows (VRPTW), Permasalahan optimasi kombinatoria, Simulated annealing, solusi tetangga. Abstract The Vehicle Routing Problem with Time Windows (VRPTW) is a combinatorial optimization problem that exists in various distribution systems. The problem deals with allocation of vehicles to service several customers, each customer has different available time, and the vehicles must visit the customers in their available time.This paper addresses the VRPTW by using an improved simulated annealing algorithm. Special functions to effectively exploring neighborhood solutions are developed. The functions are required to deal with the large search space of the VRPTW and enhance the power of the simulated annealing to obtain better solutions. The proposed approach is evaluated in comparison with well-known benchmark problems available in the literature. A set of computational experiments prove that the improved simulated annealing could produce promising results in the average of computational time of 82.29 seconds. Keywords: Vehicle Routing Problem with Time Windows (VRPTW), combinatorial optimization problem, simulated annealing, neighborhood solution
OPTIMASI MULTI TRAVELLING SALESMAN PROBLEM (M-TSP) UNTUK DISTRIBUSI PRODUK PADA HOME INDUSTRI TEKSTIL DENGAN ALGORITMA GENETIKA Agung Mustika Rizki; Wayan Firdaus Mahmudy; Gusti Eka Yuliastuti
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 4, No 2 (2017)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v4i2.86

Abstract

In the field of textile industry, the distribution process is an important factor that can affect the cost of production. For that we need optimization on the distribution process to be more efficient. This problem is a model in the Multi Travelling Salesman Problem (M-TSP). Much research has been done to complete the M-TSP model. Among several methods that have been applied by other researchers, genetic algorithms are a workable method for solving this model problem. In this article the authors chose the genetic algorithm is expected to produce an optimal value with an efficient time. Based on the results of testing and analysis, obtained the optimal population amount of 120. For the optimal generation amount is 800. The test results related to the number of population and the number of generations are used as input to test the combination of CR and MR, obtained the optimal combination of CR = 0 , 4 and MR = 0.6 with a fitness value of 2.9964.Keywords: Textile Industry, Multi Travelling Salesman Problem (M-TSP), Genetic AlgorithmPada bidang industri tekstil, proses distribusi merupakan satu faktor penting yang dapat berpengaruh terhadap biaya produksi. Untuk itu diperlukan optimasi pada proses distribusi agar menjadi lebih efisien. Masalah seperti ini merupakam model dalam Multi Travelling Salesman Problem (M-TSP). Banyak penelitian telah dilakukan untuk menyelesaikan model M-TSP. Diantara beberapa metode yang telah diterapkan oleh peneiti lain, algoritma genetika adalah metode yang bisa diterapkan untuk penyelesaian permasalahan model ini. Dalam artikel ini penulis memilih algoritma genetika diharapkan dapat menghasilkan nilai yang optimal dengan waktu yang efisien. Berdasarkan hasil pengujian dan analisis, didapatkan jumlah populasi yang optimal sebesar 120. Untuk jumlah generasi yang optimal adalah sebesar 800. Hasil pengujian terkait jumlah populasi dan jumlah generasi tersebut dijadikan masukan untuk melakukan pengujian kombinasi  CR dan MR, didapatkan kombinasi yang optimal yakni CR=0,4 dan MR=0,6 dengan nilai fitness sebesar 2,9964.Kata kunci: Industri Tekstil, Distribusi, Multi Travelling Salesman Problem (M-TSP), Algoritma Genetika
Co-Authors A.N. Afandi Abdul Latief Abadi Abdul Latief Abadi Achmad Arwan Achmad Basuki Achmad Ridok Adimoelja, Ariawan Aditama, Gustian Adyan Nur Alfiyatin Agi Putra Kharisma, Agi Putra Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Agung Setia Budi Agus Naba Agus Wahyu Widodo Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Aji Prasetya Wibawa Al Khuluqi, Mabafasa Alauddin, Mukhammad Wildan Alfiani Fitri Alfita Rakhmandasari Alfiyatin, Adyan Nur Alqorni, Faiz Amalia Kartika Ariyani Amalia Kartika Ariyani Amalia Kartika Ariyani Anantha Yullian Sukmadewa Andi Kurniawan Andi Maulidinnawati A K Parewe Andi Maulidinnawati A. K. Parewe Andreas Nugroho Sihananto Andreas Pardede Andreas Patuan G. Pardede Andrew Nafalski Angga Vidianto Aprilia Nur Fauziyah Aprilia Nur Fauziyah Arief Andy Soebroto Arinda Hapsari Achnas Armanda, Rifki Setya Arviananda Bahtiar Arya, Putu Bagus Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi, Asyrofa Bagus Priambodo Bayu Rahayudi Binti Robiyatul Musanah Budi Darma Setiawan Burhan, M.Shochibul Cahya, Reiza Adi Cahyo Prayogo, Cahyo Candra Dewi Candra Fajri Ananda Cleoputri Yusainy Darmawan, Abizard Hashfi Dea Widya Hutami Dhaifullah, Afif Naufal Diah Anggraeni Pitaloka Didik Suprayogo Dinda Novitasari Dinda Novitasari, Dinda Diny Melsye Nurul Fajri Dita Sundarningsih Durrotul Fakhiroh Dyan Putri Mahardika Edi Satriyanto Edy Santoso Eko Widaryanto Elta Sonalitha Ervin Yohannes Evi Nur Azizah Fadhli Almu’iini Ahda Fais Al Huda Fajri, Diny Melsye Nurul Fatchurrochman Fatchurrochman Fatwa Ramdani, Fatwa Fauzi, Muhammad Rifqi Fauziatul Munawaroh Febriyana, Ria Fendy Yulianto Fitra Abdurrachman Bachtiar Fitri Anggarsari Fitria Dwi Nurhayati Gayatri Dwi Santika Ghozali Maski Grady Davinsyah Gusti Ahmad Fanshuri Alfarisy Gusti Ahmad Fanshuri Alfarisy, Gusti Ahmad Fanshuri Gusti Eka Yuliastuti Hafidz Ubaidillah Hamdianah, Andi Hanggara , Buce Trias Herman Tolle Hernando, Deo Heru Nurwarsito Hidayat, Luthfi Hilman Nuril Hadi Ida Wahyuni Imada Nur Afifah Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indriati Indriati Irvi Oktanisa Ishardita Pambudi Tama Ismiarta Aknuranda Jauhari, Farid Khozaimi, Ach. Kukuh Tejomurti, Kukuh Kuncahyo Setyo Nugroho Kuncahyo Setyo Nugroho Kurnianingtyas, Diva Lily Montarcih Limantara M Chandra Cahyo Utomo M Fadli Ridhani M Shochibul Burhan, M Shochibul M. Shochibul Burhan M. Zainal Arifin Mabafasa Al Khuluqi Mar'i, Farhanna Marji Marji Mayang Anglingsari Putri, Mayang Anglingsari Mochamad Anshori Moh. Khusaini Moh. Sholichin Moh. Zoqi Sarwani Mohammad Zoqi Sarwani Mohammad Zoqi Sarwani, Mohammad Zoqi Mu’asyaroh, Fita Lathifatul Muh. Arif Rahman Muhammad Ardhian Megatama Muhammad Faris Mas'ud Muhammad Halim Natsir Muhammad Isradi Azhar Muhammad Khaerul Ardi Muhammad Noor Taufiq Muhammad Rivai Muhammad Rofiq Nadia Roosmalita Sari Nadia Roosmalita Sari Nadia Roosmalita Sari Nadya Oktavia Rahardiani Nashi Widodo Ni Wayan Surya Wardhani Nindynar Rikatsih Novanto Yudistira Novi Nur Putriwijaya Nurizal Dwi Priandani Nurul Hidayat Oakley, Simon Oktanisa, Irvi Philip Faster Eka Adipraja Prayudi Lestantyo Purnomo Budi Santoso Putra, Firnanda Al Islama Achyunda Putri Hasan, Vitara Nindya Putu Indah Ciptayani Qoirul Kotimah Rachmansyah, Ghenniy Rachmawati, Christina Rani Kurnia Rayandra Yala Pratama, Rayandra Yala Retno Dewi Anissa Riani, Garsinia Ely Rifa’i, Muhaimin Rikatsih, Nindynar Rinda Wahyuni Rizal Setya Perdana Rizal Setya Perdana Rizdania, Rizdania Rizka Suhana Rizki Ramadhan Rody, Rafiuddin Ruth Ema Febrita Ryan Iriany S, M Zaki Samaher . Saragih, Triando Hamonangan Sari, Nadia Roosmalita Sari, Nadia Roosmalita Selly Kurnia Sari Setyawan Purnomo Sakti Sudarto Sudarto Sukarmi Sukarmi, Sukarmi Sulistyo, Danang Arbian Sutrisno . Sutrisno Sutrisno Syafrial Syafrial Syafrial Syafrial Syaiful Anam Syandri, Hafrijal Tirana Noor Fatyanosa, Tirana Noor Titiek Yulianti Titiek Yulianti Titiek YULIANTI Tomi Yahya Christyawan Tri Halomoan Simanjuntak Ullump Pratiwi Utaminingrum, Fitri Utomo, M. Chandra Cahyo Vivi Nur Wijayaningrum Wahyuni, Ida Widdia Lesmawati Windi Artha Setyowati Yeni Herawati Yogi Pinanda Yogie Susdyastama Putra Yudha Alif Aulia Yudha Alif Auliya Yudha Alif Auliya, Yudha Alif Yulia Trianandi Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo, Yusuf Priyo