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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Knowledge Engineering and Data Science

Agus Wahyu Widodo

Fakultas Ilmu Komputer, Universitas Brawijaya

Author-ID : 6132507

Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Profiling DNA Sequence of SARS-Cov-2 Virus Using Machine Learning Algorithm Lailil Muflikhah; Muh. Arif Rahman; Agus Wahyu Widodo
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3487

Corona virus disease-19 (COVID-19) is growing rapidly because it is an infectious disease. This disease is caused by a virus belonging to the type of DNA virus with very diverse genetics. This study proposes a feature extraction method using k-mer to obtain nucleotide frequencies in protein coding. In profiling viral DNA sequences, this study proposes to obtain similarity by country using hierarchical k-means, where the results are averaged by the hierarchical clustering method and then find the initial cluster center. The experimental results show that the silhouette, purity, and entropy are 0.867, 0.208, and 0.892, respectively. Then, we apply the Gini index feature selection to find the important components as characteristics in each country. The selected components are implemented using the ensemble method, Random Forest, to evaluate their performance. The experimental results showed high performance, including sensitivity, accuracy, specificity, and area under the curve (AUC).

Application of Density Based Spatial Clustering Application With Noise (DBSCAN) in Determining the Quality of Keprok Orange and Siam Orange Hybrid in the Research Center of Orange and Subtropic Plants Batu City Faiz Alqorni; Wayan Firdaus Mahmudy; Agus Wahyu Widodo
Journal of Information Technology and Computer Science Vol. 6 No. 1: April 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. One of the tasks of the Indonesian Citrus and Subtropical Research Institute is research on crossing between citrus varieties to produce saplings with the best quality products through observation of the fruit produced. Because the amount of fruit production studied is very large, it requires a fast and accurate observation process, one of which is the clustering method of data mining. Observations were made using a clustering process or grouping Density Based Spatial Clustering Application with Noise (DBSCAN) on fruit characteristics that indicate quality. DBSCAN works by grouping data based on density, so that it is expected to find several data groups that are close to each other which shows the tendency of the quality of the observed fruit data as well as labeling outlays for data that are too far from the crowd. The results of the grouping will be analyzed to find out the number and characteristics of the groups formed where the results of the grouping are assessed using the Silhouette Coefficient method to determine the best parameter values. The results obtained in this study are obtained three group results which will be divided into medium quality, good, and not so good. The quality of grouping using the Silhouette Coefficient value of 0.69.

Efficient Scheduling of Plantation Company Workers using Genetic Algorithm Wayan Firdaus Mahmudy; Andreas Pardede; Agus Wahyu Widodo; Muh Arif Rahman
Knowledge Engineering and Data Science Vol 3, No 2 (2020)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v3i22020p60-66

Workers at large plantation companies have various activities. These activities include caring for plants, regularly applying fertilizers according to schedule, and crop harvesting activities. The density of worker activities must be balanced with efficient and fair work scheduling. A good schedule will minimize worker dissatisfaction while also maintaining their physical health. This study aims to optimize workers' schedules using a genetic algorithm. An efficient chromosome representation is designed to produce a good schedule in a reasonable amount of time. The mutation method is used in combination with reciprocal mutation and exchange mutation, while the type of crossover used is one cut point, and the selection method is elitism selection. A set of computational experiments is carried out to determine the best parameters’ value of the genetic algorithm. The final result is a better 30 days worker schedule compare to the previous schedule that was produced manually.

Optimisation of Rice Fertiliser Composition using Genetic Algorithms Retno Dewi Anissa; Wayan Firdaus Mahmudy; Agus Wahyu Widodo
Knowledge Engineering and Data Science Vol 2, No 2 (2019)
Publisher : Universitas Negeri Malang

There are so many problems with food scarcity. One of them is not too good rice quality. So, an enhancement in rice production through an optimal fertiliser composition. Genetic algorithm is used to optimise the composition for a more affordable price. The process of genetic algorithm is done by using a representation of a real code chromosome. The reproduction process using a one-cut point crossover and random mutation, while for the selection using binary tournament selection process for each chromosome. The test results showed the optimum results are obtained on the size of the population of 10, the crossover rate of 0.9 and the mutation rate of 0.1. The amount of generation is 10 with the best fitness value is generated is equal to 1,603.

Deteksi Covid-19 pada Citra Sinar-X Dada Menggunakan Deep Learning yang Efisien Novanto Yudistira; Agus Wahyu Widodo; Bayu Rahayudi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7, No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020763651

Deteksi Covid-19 merupakan tahapan penting untuk mengenali secara dini pasien terduga Covid-19 sehingga dapat dilakukan langkah lanjutan. Salah satu cara pendeteksian adalah melalui citra sinar-x paru. Namun demikian, selain dibutuhkan suatu model algoritma yang dapat menghasilkan akurasi tinggi, komputasi yang ringan merupakan hal yang dibutuhkan sehingga dapat diaplikasikan dalam alat pendeteksi. Model deep CNN dapat melakukan deteksi dengan akurat namun cenderung memerlukan penggunaan memori yang besar. CNN dengan parameter yang lebih sedikit dapat menghemat storage maupun penggunaan memori sehingga dapat berproses secara real time baik berupa alat pendeteksi maupun sistem pengambilan keputusan via cloud. Selain itu, CNN dengan parameter yang lebih kecil juga dapat untuk diaplikasikan pada FPGA dan perangkat keras lainnya yang mempunyai kapasitas memori terbatas. Untuk menghasilkan deteksi COVID-19 pada citra sinar-x paru yang akurat namun komputasinya juga ringan, kami mengusulkan arsitektur CNN kecil namun handal dengan menggunakan teknik pertukaran channel yang disebut ShuffleNet. Dalam penelitian ini, kami menguji dan membandingkan kemampuan ShuffleNet, EfficientNet, dan ResNet50 karena mempunyai jumlah parameter yang lebih kecil dibanding CNN pada umumnya seperti VGGNet atau FullConv yang menggunakan lapisan konvolusi secara penuh namun mempunyai kemampuan deteksi yang mumpuni. Kami menggunakan 1125 citra sinar-x dan mencapai akurasi 86.93 % dengan jumlah parameter model yang 18.55 kali lebih sedikit dari EfficientNet dan 22.36 kali lebih sedikit dari ResNet50 untuk mendeteksi 3 kategori yaitu Covid-19, Pneumonia, dan normal melalui uji 5-fold crossvalidation. Memori yang diperlukan oleh masing-masing arsitektur CNN tersebut untuk melakukan sekali deteksi berhubungan secara linier dengan jumlah parameternya dimana ShuffleNet hanya memerlukan memori GPU sebesar 0.646 GB atau 0.43 kali dari ResNet50, 0.2 kali dari EfficientNet, dan 0.53 kali dari FullConv. Lebih lanjut, ShuffleNet melakukan deteksi paling cepat yaitu sebesar 0.0027 detik.AbstractCovid-19 detection is an important step in identifying early patients with suspected Covid-19 so that further steps can be taken. One way of detection is through pulmonary x-ray images. However, besides requiring an algorithm model that can produce high accuracy, lightweight computation is needed so that it can be applied in a detector. The deep CNN model can detect accurately but tends to require large memory usage. CNN with fewer parameters can save storage and memory usage so that it can process in real time both in the form of detection devices and decision-making systems via the cloud. In addition, CNN with smaller parameters can also be applied to FPGA and other hardware that have limited memory capacity. To produce accurate COVID-19 detection on x-ray images with lightweight computation, we propose a small but reliable CNN architecture using a channel shuffle technique called ShuffleNet. In this study, we tested and compared the capabilities of ShuffleNet, EfficientNet, and ResNet because they have a smaller number of parameters than usual deep CNN, such as VGGNet or FullConv which uses a full convolution layers with a robust detection capability. We used 1125 x-ray images and achieved an accuracy of 86.93% with a number of model parameters of 18.55 times less than EfficientNet and 22.36 times less than ResNet50 to detect 3 categories namely Covid-19, Pneumonia, and normal through the 5-fold cross validation. The memory required by each CNN architecture to perform one detection is linearly related to the number of parameters where ShuffleNet only requires GPU memory of 0.646 GB or 0.43 times that of ResNet50, 0.2 times of EfficientNet, and 0.53 times of FullConv. Furthermore, ShuffleNet performs the fastest detection at 0.0027 seconds.

Optimasi Derajat Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritma Genetika Untuk Diagnosis Penyakit Sapi Potong Diva Kurnianingtyas; Wayan Firdaus Mahmudy; Agus Wahyu Widodo
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 4, No 1: Maret 2017
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Sistem inferensi fuzzy bisa digunakan untuk diagnosis penyakit pada sapi potong. Untuk mendapatkan akurasi yang tinggi maka batasan fungsi keanggotaan fuzzy perlu ditentukan secara tepat. Penggunaan metode logika fuzzy untuk memperoleh hasil diagnosis penyakit pada sapi potong sesuai pakar berdasarkan batasan gejala penyakit dan aturan-aturan yang diperoleh dari pakar. Batasan tersebut bisa diperbaiki menggunakan Algoritma Genetika untuk mendapatkan akurasi yang lebih baik. Pengujian yang dilakukan pada 51 data dari beberapa gejala penyakit menghasilkan akurasi sebesar 98,04% dengan menggunakan parameter genetika terbaik antara lain ukuran populasi sebesar 80, ukuran generasi sebesar 15, nilai Crossover rate (Cr) sebesar 0,9, dan nilai Mutation rate (Mr) sebesar 0,06. Akurasi tersebut mengalami peningkatan sebesar 3,54% sesudah dilakukannya optimasi pada metode logika fuzzy.Kata kunci: diagnosis penyakit sapi potong, logika fuzzy, Algoritma GenetikaAbstract Fuzzy inference systems can be used to diagnose cattle disease. Prior to obtaining the most accurate of limitation, fuzzy membership functions must be defined precisely. Thus, the limits will be optimized along with Genetic Algorithm to get more accurate results. The function of fuzzy logic methods in the diagnosis of disease is relied upon the parametres set by experts. Tests that were performed on 51 data from some of the symptoms of the disease resulted in an accuracy of 98.04% using the best genetic parameters with the population size of 80, the size of the generation of 15, crossover rate value of 0.9, and the value of mutation rate of 0.06. The accuracy has increased by 3.54% compare to results before optimization. Keywords: cattle disease diagnosis, fuzzy logic, genetic algorithms

Optimasi Penjadwalan Mata Pelajaran Menggunakan Metode Tabu Search: STUDI KASUS: SMKN 2 SINGOSARI Olive Khoirul L.M.A.; Agus Wahyu Widodo; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 1 (2017): Januari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (859.119 KB)

Penjadwalan merupakan salah satu proses penting yang harus dilakukan oleh setiap organisasi untuk mencapai tujuan organisasi. Permasalahan penjadwalan dapat terjadi pada berbagai organisasi, terutama organisasi dengan sumber daya yang besar seperti perusahaan, pemerintahan,dan institusi pendidikan. Di SMKN 2 Singosari terdapat delapan jurusan, sehingga penjadwalan mata pelajaran menjadi salah satu masalah rumit yang selalu terjadi setiap awal semester. Selama ini proses penjadwalan yang berlangsung di SMKN 2 Singosari masih berjalan secara manual menggunakan bantuan Microsoft Excel. Sebuah sistem cerdas berbasis web dibuat untuk memudahkan proses penjadwalan di SMKN 2 Singosari. Sistem ini menggunakan algoritma Tabu Search untuk melakukan proses penjadwalan mata pelajaran. Dalam metode Tabu Search, solusi awal berupa jadwal dibangkitkan secara random, kemudian dicari solusi akhirnya dan yang menjadi Tabu List adalah kumpulan move berbentuk array yang merupakan solusi jadwal mata pelajaran dengan nilai total penalti paling kecil pada tiap iterasi. Hasil penjadwalan yang dibangkitkan memiliki total penalti sebesar 302 untuk penjadwalan pada 8 kelas.

Pemanfaatan Algoritma Genetika Untuk Optimasi 0/1 Multi-Dimensional Knapsack Problem Dalam Pendistribusian Produk (Studi Kasus UD.TOSA) Ryan Iriany; Agus Wahyu Widodo; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 4 (2017): April 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1062.046 KB)

As a distributor company, the cost of distribution is very influential on the benefits to be obtained UD.TOSA. The affect of distribution cost is the distance distribution. Besides affected by distance, cost is also influenced by the frequency of maintenance vehicles used in the distribution process. The more frequent occurrence of damage to the vehicle, it will increase the frequency of maintenance so that adds to the cost of distribution. One cause damage to the vehicle is because vehicles are often excess payload (overtonase). Excessive loads can also increase the potential for accidents that could result in damage to the product as well as the vehicle itself. This will result in reduced profits obtained. Products are distributed and used vehicles have their respective characteristics. Each vehicle has a limited capacity, so not all products can be loaded, the distributor can perform any combination of products that should be loaded in order to maximize cargo volume without exceeding the capacity of the vehicle. The combination of products in the distribution process is a complex combinatorial problems, problems of this combination into the multi-dimensional knapsack problem (MKDP). Utilization of genetic algorithms in multi-dimensional knapsack problem is to perform such optimization of capacity in the distribution process.The algorithm parameters used in this study is a population of 200, the generation of 100, cr by 0.9 and 0.1 mr. Excess load on the solutions produced by the system is equal to 0% of the maximum load capacity of the vehicle. Solutions generated by the system can be ensured not exceed the capacity, both of maximum space vehicles as well as the maximum load of the vehicle. It can reduce the risk of damage to the vehicle so that the frequency of maintenance is not too often.

Sistem Pakar Klasifikasi Permasalahan Berdasar AUM Menggunakan FCM-FIS Tsukamoto Ainun Najib Eka Christianto; Rekyan Regasari Mardi Putri; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 4 (2017): April 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (810.385 KB)

Alat ungkap masalah is an instrument in guidance and counseling are used to discover and understand any problems experienced by students. Alat ungkap masalah is used because of the lack of a deep understanding of teachers' guidance and counseling to students. Although already used alat ungkap masalah student counseling service process is still less than the maximum because of the lack of human resources that exist in schools and teachers' understanding of guidance and counseling about the tool according to the problems and issues faced by the students. Therefore, it is necessary to develop an expert system that can adopt the knowledge of an expert counseling in the process of recognition of the problem by using the tool revealed the problem. The purpose of this application is to help the teachers counseling to ease the process of guidance and counseling and facilitate students in recognizing the problems that it faces. This application uses the FCM Clustering as the generation process and FIS rules Tsukamoto as an inference engine, the application can generate an accuracy rate of 75.71% compared with the results of the expert diagnosis.

Deteksi Kesalahan Ejaan dan Penentuan Rekomendasi Koreksi Kata yang Tepat Pada Dokumen Jurnal JTIIK Menggunakan Dictionary Lookup dan Damerau-Levenshtein Distance Tusty Nadia Maghfira; Imam Cholissodin; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 6 (2017): Juni 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (786.853 KB)

Writing is a way to deliver and share information among people. It is now even easier to do because of the help of technology such as computers, smartphones and internet. For example, writing and publication of research journal is made to share and enhance knowledge. Generally, the publication of research journal is accommodated by educational institutions both national and international such as JTIIK (Jurnal Teknologi Informasi & Ilmu Komputer) Faculty of Computer Science UB. Before journal is published, a journal should pass editing process by editor to check if there is some mistake and deficiency such as spelling error. However, in their work, editor also accidentally making mistake that will lead to many error spelling that still exist even though editing process has been done. Some misspelled word can change the meaning of knowledge that the author want to deliver and cause misunderstanding of information among the readers. Based on these problems, researcher propose error spelling detection and correction system using Dictionary Lookup and Damerau-Levenshtein Distance. Dictionary Lookup method is considered effective in determining a word including validity or invalidity of the word based on availability or unavailability of the word in Lexical Resource. In addition, Damerau-Levenshtein Distance can provide better correction than Levenshtein Distance. The best precision and recall result for correction simultaneously are 0.78 and 1 from second test scenario.

Co-Authors Achmad Arwan Achmad Dewanto Aji Wibisono Adam Hendra Brata Adinugroho, Sigit Afrida Djulya Ika Pratiwi Aida Fitri Nur Amrina Ainun Najib Eka Christianto Aisha Laras Akmilatul Maghfiroh Al-Mar'atush Shoolihah Allifira Andara Hasna Ana Mariyam Puspitasari Andika Indra Kusuma Andreas Pardede Angelika Trivena Lodong Anggita Nurfadilla Mahardika Annisa Amalia Nur'aini Anto Satriyo Nugroho Ardiansyah Setiajati Arry Supriyanto Arya Agung Andika Aryu Hanifah Aji Asfie Nurjanah Ayu Anggrestianingsih Ayudiya Pramisti Regitha Ayustina Giusti Azizah Nurul Asri Bagas Laksono Bayu Rahayudi Beryl Labique Ahmadie Budi Darma Setiawan Budi Kurniawan Cahya Chaqiqi Candra Dewi Dani Devito Delischa Novia Sabilla Deo Hernando Dian Eka Ratnawati Diantarakita Diantarakita Diva Kurnianingtyas Dwi Retnoningrum Dyan Putri Mahardika Eko Wahyu Hidayat Erlyan Eka Pratiwi Faiz Alqorni Faizatul Amalia Fajar Pangestu Fajar Pradana Fajri Eka Saputra Farizky Novanda Pramuditya Femilia Nopianti Feris Adi Kurnia Sadiva Fitri Dwi Astuti Fransiskus Cahyadi Putra Pranoto Grace Theresia Situmorang Gusti Ngurah Wisnu Paramartha Hafid Satrio Priambodo Hardyan Zalfi Haris Bahtiar Asidik Harits Abdurrohman Herman Tolle Imam Cholissodin Indriati Indriati Irwan Shofwan Javier Ardra Figo Jefri Hendra Prasetyo Kholifa'ul Khoirin Lailil Muflikhah Latifa Nabila Harfiya Laviana Agata M. Ali Fauzi Maharani Tri Hastuti Maria Sartika Tambun Miftahul Arifin Muh Arif Rahman Muh Arif Rahman Muh. Arif Rahman Muh. Arif Rahman Muh. Ihsan As Sauri Muhamad Rendra Husein Roisdiansyah Muhammad Arif Rahman Muhammad Dimas Setiawan Sanapiah Muhammad Fahmi Hidayatullah Muhammad Fahmi Wibawa Muhammad Faiz Abdul Hamif Muhammad Fajriansyah Muhammad Heryan Chaniago Muhammad Ikhsan Nur Muhammad Rafi Farhan Muhammad Tanzil Furqon Muhja Mufidah Afaf Amirah Nabilla Putri Sakinah Nanda Dwi Putra Miskarana Ade Natassa Anastasya Naufal Sakagraha Kuspinta Nelli Nur Rahma Ni'mah Firsta Cahya Susilo Ningsih Puji Rahayu Nizar Riftadhi Prabandaru Novanto Yudistira Nur Afifah Sugianto Nur Faiqoh Laely Ambarwati Nur Firra Hasjidla Nur Kholida Afkarina Nurudin Santoso Nurul Hidayat Oktiyas Muzaky Luthfi Olive Khoirul L.M.A. Puteri Aulia Indrasti Putra Pandu Adikara Putri Bunga Rahmalita Putu Satya Cahyani Rahma Juwita Sany Randy Cahya Wihandika Rekyan Regasari Mardhi Putri Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Restu Widodo Resya Futri Hadi Febryana Retno Dewi Anissa Revan Yosua Cornelius Sianturi Ridho Saputra Rinindya Nurtiara Puteri Rizka Husnun Zakiyyah Rizki Aziz Amanullah Rosi Afiqo Rr Dea Annisayanti Putri Ryan Iriany Satria Habiburrahman Fathul Hakim Sayyidah Karimah Sindy Erika Br Ginting Sri Rahadian Ramadhan Sakti Susiawan Hastomo Ajie Talitha Raissa Tusiarti Handayani Tusty Nadia Maghfira Umar Zaki Izzuddin Utaminingrum, Fitri Vriza Wahyu Saputra Wayan Firdaus Mahmudy Wayan Firdaus Mahmudy Wenny Ramadha Putri Willy Karunia Sandy Winda Cahyaningrum Winda Ika Praseptiyana Witriana Sumarni Yane Marita Febrianti Yosafat Vincent Saragih Yuita Arum Sari Yunita Kristanti Emilia

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