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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Journal of Applied Engineering and Technological Science (JAETS)
Agus Wahyu Widodo
Fakultas Ilmu Komputer, Universitas Brawijaya
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing 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

Abstract

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).
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

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Abstract

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

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Abstract

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

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Abstract

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

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Abstract

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.
Prediksi Penerimaan Zakat menggunakan Metode Support Vector Regression (SVR) dengan Flower Pollination Algorithm (FPA) Tusiarti Handayani; Imam Cholissodin; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 7 (2017): Juli 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Payment and distribution of zakat in Indonesia managed by Badan Amil Zakat, which of one is Lembaga Amil Zakat Infaq and Shadaqah Muhammadiyah (LAZISMU) Malang. Fluctuations in the level of zakat fund received by LAZISMU Malang affect in the amount of zakat fund that can be distributed to communities in the all of Malang region. Zakat reception forecasting is so needed to determined the amount of zakat received, so that solution anticipation when the fund is less than the distribution target can be done as early as possible. Prediction are made on this research is using Support Vector Regression (SVR) with Flower Pollination Algorithm (FPA) method. SVR used to make prediction of zakat received based on historical data zakat received, and then FPA used to make optimization value from parameter to be used on SVR method. Data used as many as 64 historical data from Juli 2011 up to Oktober 2016 data received of zakat for the one of Lembaga Amil Zakat Nasional at Malang region that is LAZISMU Malang. The results of tests performed on the prediction zakat using SVR with FPA on zakat revenue data from 2011 to 2016 resulted value of 0.2497 in the fitness and 3.0048 in the MAPE which means average difference between of actual data and predict result is Rp144.741.
Optimasi Model Himpunan Keanggotaan Fuzzy Menggunakan Algoritme Evolution Strategies (Pada Data Diagnosis Penyakit Sapi Potong) Dyan Putri Mahardika; Wayan Firdaus Mahmudy; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 8 (2017): Agustus 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The increasing number of daily consumption of beef, it is need to monitoring the availability of good-quality beef, which is free from germs. In this research will be created a system that can be solve the subjective, unclear and vague problem, that is cattle disease diagnose, the existence of subjective information about the symptoms of the disease, then the diagnosis can be done using a fuzzy inference system. To obtaining the high accuracy, the set of fuzzy membership needs to be determined precisely. To get the best solution or in this case is the set of fuzzy membership can be done using Evolution Strategies method. The accuracy of the system is obtained by matching the results of the diagnosis and the diagnosis expert system using 51 generates test data accuracy rate of 95.49% using fuzzy. After optimization of the fuzzy set membership using evolution strategies (ES) produces better accuracy rate is 97.45% with the best parameters obtained ES is the population size of 80, offspring size of 10μ, and the amount of generation by 50.
Penggunaan Ciri Geometric Invariant Moment pada Pengenalan Tanda Tangan Rahma Juwita Sany; Agus Wahyu Widodo; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Signature as a personal attribute is one of the person's identity verification equipment that is accepted widely by the society. The process of signature recognition starts from starts from preprocessing, which consist of filtering, thresholding, thinning, cropping and resizing. After preprocessing continued by feature extraction process using Geometric Invariant Moment to get the value of a feature that will be used for the classification process using K-Nearest Neighbour. The variations Geometric Invariant Moment feature that has the smallest of FAR value and FRR value on each data source are different. For data from Indonesia the smallest FAR obtained while using moment 7 with value is 7% and the smallest FRR obtained while combining moment 1,2,3,6 and 7 and using all of the moment with each value is 61.5%. For data from Spain the smallest FAR obtained while combining moment 3,4,5 and 7, moment 1,3,4,5 and 7 and combining 1,3,4,5,6 and 7 with each value is 7% and the smallest FRR obtained while combining moment 2,3,4,5,6 and 7 and using all of the moment with each value is 72%. For data from Persia the smallest FAR obtained while combining moment 3 and 5 and combining moment 3,5 and 6 with each value is 9.5% and the the smallest FRR obtained while combining moment 1,2,3,4,6 and 7 with value is 37%. The testing results of FAR and FRR is inversely proportional. The system can recoginize the fake signatures well that proven by getting FAR value is relatively small on all of data sources. But the system can't recognize the original signatures well that proven by getting the high FRR value on all data sources. Features of Geometric Invariant Moment that applied globally on an image don't provide high accuracy. Perhaps, it happened because when apply global feature, the local features can't recognize properly. It occurs on the original signature image, while the application of the features of Geometric Invariant globally on the fake signature image provide high accuracy.
Analisis Perbandingan Metode K-Means Dengan Improved Semi-Supervised K-Means Pada Data Indeks Pembangunan Manusia (IPM) Gusti Ngurah Wisnu Paramartha; Dian Eka Ratnawati; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (983.505 KB)

Abstract

At this time with the growing amount of information, the concept of data mining getting known as an important tool in the management information. Refers to the concept of data mining, the most popular concept in data mining is a clustering technique. One well known clustering method is k-means traditional. But in its application, k-means method has some problems such as determining the value of K cluster and determining the initial cluster centers were done randomly making process was inconsistent and the results of the cluster becomes worse. Therefore, there is a method to overcome these problems are improved semi-supervised k-means clustering. With improved semi-supervised method that combines the supervised and unsupervised method, users only need to label a bit of data that has not been labeled, then the labeled data is used to find the optimal value of initial cluster center and K cluster that will optimizes the process and result of clustering process. On implementation, this research combine k-means algorithm and improved semi-supervised k-means to clustering human development index (HDI) data. HDI data chosen because it has the right characteristics for clustering such amounts of data and the data is divided into several clusters. On the testing improved semi-supervised k-means method giving out the average accuracy of 90.3%, better than k-means clustering that giving 73.7% accuracy. In the second testing, improved semi-supervised k-means method produces an average time for one convergent 1222.9959 seconds, better than k-means with 1504.75 seconds. The third testing, improved semi-supervised k-means generates an average number of iterations for one convergent more efficient than k-means with the number of iterations of 7.11 compared 9.72. Last, on the cluster quality testing using silhouette coefficient, improved semi-supervised k-means method giving average value 0.69880, better than the traditional k-means with an average value of 0.62734.
Optimasi Multiple Travelling Salesman Problem Pada Pendistribusian Air Minum Menggunakan Algoritme Particle Swarm Optimization (Studi Kasus: UD. Tosa Malang) Rinindya Nurtiara Puteri; Agus Wahyu Widodo; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (776.05 KB)

Abstract

If the distribution application was not run optimally ,it can obstruct the distribution of drinking water process.The tardiness of drinking water transmission become an obstacle in the process and it is also effected by many factors, such as sales ignorance about the shortest path to where the customers are.So this system can lead and make the process easier to determine the shorthest path. In that Distribution obstacle we called it Multiple Travelling Salesman Problem because implicate more than one factor .One of the main purpose from this research is to determine the shortest path for every saleses.This thesis uses Particle Swarm Optimization Algorithm. There were some thesis talked about Multiple Travelling Salesman Problem but to PSO method is scarce. Particle Swarm Optimization is one of the method that solved M-TSP which is that method will gives some effective solutions.Based on the background,researcher choose to use The optimization of Multiple Travelling Salesman Problem application,and in drinking water distribution use Particle Swarm Optimization Algorithm. The result that had been proved show the route sequence that used is better from optimum parameter made 30 iterations and with 90 particle.
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 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. Ihsan As Sauri Muhamad Rendra Husein Roisdiansyah 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, oktiyas muzaky 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