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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Achmad Arwan
Teknik Informatika, Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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Optimization of Genetic Algorithm Performance Using Naïve Bayes for Basis Path Generation Achmad Arwan; Denny Sagita Rusdianto
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 2, No 4, November-2017
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (722.536 KB) | DOI: 10.22219/kinetik.v2i4.370

Abstract

Basis path testing is a method used to identify code defects. The determination of independent paths on basis path testing can be generated by using Genetic Algorithm. However, this method has a weakness. In example, the number of iterations can affect the emersion of basis path. When the iteration is low, it results in the incomplete path occurences.  Conversely, if iteration is plentiful resulting to path occurences, after a certain iteration, unfortunately, the result does not change. This study aims to perform the optimization of Genetic Algorithm performance for independent path determination by determining how many iteration levels match the characteristics of the code. The characteristics of the code used include Node, Edge, VG, NBD, and LOC. Moreover, Naïve Bayes is a method used to predict the exact number of iterations based on 17 selected code data into training data, and 16 data into test data. The result of system accuracy test is able to predict the exact iteration of 93.75% from 16 test data. Time-test results show that the new system was able to complete an independent search path being faster 15% than the old system.
Sistem Pakar Diagnosis Penyakit Demam: DBD, Malaria dan Tifoid Menggunakan Metode K-Nearest Neighbor - Certainty Factor Elsa Nuramilus Shofia; Rekyan Regasari Mardi Putri; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 5 (2017): Mei 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Fever is one of the health problems that disrupt everyone's productivity, even it can cause death and remain a health problem in Indonesia. There are several types of fever that needs to be wary, it includes dengue, malaria and typhoid. These three diseases have similar symptoms, so many medical personnel and doctors internship often make mistakes in diagnosing the disease. Therefore, an expert system is required to resolve the issue. The method used to support the expert system is K-Nearest Neighbor - Certainty Factor which is a merger of two methods in which the classification results of K-Nearest Neighbor to be rated certainty by a Certainty Factor method and resulting a diagnosis of the disease. In this study, the training data and test data used were 143 data. Based on test results obtained K value variation accuracy of 88.37%. On testing variations training data obtained an accuracy of 86.04%. In testing the ratio of training data and test data obtained an accuracy of 95%. In testing the variation of the number of test data obtained an accuracy of 90%. In testing the variety of test data obtained an average accuracy of 97.22%. In comparison testing method, the method k-nearest neighbor certainty factor gets an accuracy of 84.79%.
Aplikasi Perangkat Bergerak Untuk Pencarian Tempat Parkir di Lingkungan Kampus Universitas Brawijaya Adi Cahya Hermawan; Agi Putra Kharisma; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Parking lot is one of many facilities owned by all faculties in Brawijaya University. But, usually the available parking space is full at certain times. So, the students usually have to search for the empty parking slots by them selves. Currently in Universitas Brawijaya there is no application that can provide information about the parking lot that still has empty space. This research aims to make a mobile device application to provide recommendation of parking lot which still have empty space. This application uses longitude and Latitude of Google API fiture and tested using blackbox method. From the validation tests performed, the features in the application work well with a 100% percentage. Beside validation testing, there also performed quisionaire tests and field tests which results are considered as good. For each question, there is 20% rate for very good, 60% for good, and 20% for fair on average. This application can be used to help users, both students and parking officers to conduct business processes in the parking lot of Universitas Brawijaya.
Pembangunan Aplikasi Sistem Informasi Pergudangan pada Rumah Sakit Umum Daerah Dr. Murjani Sampit Kabupaten Kotawaringin Timur Hidayatullah Agung Prasetyo; Bayu Priyambadha; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1771.794 KB)

Abstract

The information technology development is growing rapidly and the main problem is how to process data to give useful information and easy to use by user. Warehouse management system that curently used on Dr. Murjani Sampit hospital is manual. Data recording done by write on books and excel files, with the number of in and out of goods makes record and search for data become inefficient in term of time and effort. Assigning tasks to someone who did this manual system led to possible errors in writing and data processing. From these problems it is necessary to develop an information system application that can handle recording, storing, processing and reporting automatically to make work easier and reduce data processing error. Research was done by Iterative Life Cycle and system builted using PHP, MySQL, and Javascript technology. Compatibility testing showed system running well on Google Chrome and Firefox Mozzila later on white-box testing showed from 20 test cases 100% result is valid and from black-box testing obtained from 65 test cases 100% result is valid. The results of these tests indicate that the system successfully analyzed its needs and implemented according with the design.System implementation may resolve the manual system problem which occur at the hospital.
Optimasi K-Nearest Neighbour Menggunakan Particle Swarm Optimization pada Sistem Pakar untuk Monitoring Pengendalian Hama pada Tanaman Jeruk Kukuh Wiliam Mahardika; Yuita Arum Sari; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Orange in Indonesia is one of the national commodities have the potential of high competitiveness in the local economy to abroad. The production of Indonesian Orange from 2006 to 2015 has decreased. One of the causes of this decline is pests. Therefore we need a system that can identify pests in citrus plants. The PSO-KNN method is one method that can be used to solve classification problems with many features. This method is a combination of 2 methods namely K-Nearest Neighbour and Particle Swarm optimization. K-Nearest Neighbors (KNN) are used to classify pests based on similarity calculations from existing data. Particle swarm optimization (PSO) is used to perform k value optimization and feature selection on KNN dataset and then evaluate the accuracy generated on KNN. From the results of tests that have been done can be concluded that the value of the best PSO parameter iteration is 151, popsize is 25, the value of c1 is 1, the value of c2 is 1.2 and w is 0.9. There was an increase in accuracy before and after optimization that is the highest accuracy of KNN reaches 90%, and the highest accuracy of PSO-KNN reached 96.25%. Improved accuracy indicates that the PSO algorithm is able to correct the deficiency that exist in KNN.
Seleksi Fitur Information Gain untuk Klasifikasi Penyakit Jantung Menggunakan Kombinasi Metode K-Nearest Neighbor dan Naive Bayes Syafitri Hidayatul Annur Aini; Yuita Arum Sari; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (764.756 KB)

Abstract

Heart disease is one of the non contagious diseases that can lead to death. This disease occurs because of the narrowing of blood vessels that cause impairment of heart function. The death rate that caused by a heart disease is continuing increase and according by the Ministry of Health of the Republic of Indonesia research, in 2030 it reach 23.3 million peoples. It should be anticipated because the number of cardiologists in Indonesia is still very minimal. This research proposes framework Information Gain selection features with combination K-Nearest Neighbor and Naive Bayes to overcome the problems on the effectiveness and accuracy in classification heart disease. Information Gain algorithm used for reduce variable dimention to get relevant variables. After Information Gain selection features process is completed, the next process is classify numeric atributes with KNN and categorical atributes with Naive Bayes. The results of this research indicate an accuracy of 92.31% when the class distribution testing is balanced using 6 features with value of K=25 and when the class distribution testing is not balanced using 4 features with value of K=35. Based on these results, can be concluded that features selection Information Gain with combination KNN and Naive Bayes algorithm can be used for classifying heart disease.
Sistem Pendukung Keputusan Pemilihan Varietas Unggul Jagung Hibrida Menggunakan Metode AHP-SMART R Moh Andriawan Adikara; Muhammad Tanzil Furqon; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Corn proudction in Indonesia is still continue to rise. Although in 2016 Indonesian corn production is currently at 17 million tons, it is still behind the United States with 365 million tons in corn production. The amount of corn production will affect the level of exports and imports that directly affect the country's economy. Increased corn production can be done in various ways, one of which is the improvement of cultivation techniques with the use of superior varieties. According to available data from the Indonesian Ministry of Agriculture, there are 100 hybrid corn varieties, but of the many varieties of corn, there are still varieties that have not been able to increase the corn's production significantly. Selection of corn varieties becomes a problem because there are many criteria to consider. Solutions from the selection of corn varieties can be solved by decision support system method called AHP and SMART method. The AHP method is used to give weighting to the criteria used in the SMART method. The SMART method is used to rank superior corn varieties. Both methods are selected for being able to produce accurate and fast computing decisions. The result of the system is in the form of rank of corn varieties ranging from the best to the worst.System validation is done by using Spearman Rank correlation with = 0,99754 which means a relationship between result system and expert result is near perfect.
Pembangunan Sistem Pemetaan Berbasis Web-Gis Untuk Analisis Potensi Usaha Di Kabupaten Malang Menggunakan Metode Analytical Hierarchy Process (AHP) (Studi Kasus: Badan Perencanaan Pembangunan Daerah Kabupaten Malang) Ihwan Latif; Denny Sagita Rusdianto; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (423.005 KB)

Abstract

The choice of strategic business locations will affect the success of business activities that will be implemented. While, the people often gets some problems when they are determining the right business potential in the search location. These problems occurred in Malang Regency, when people or investors are determining potentially business areas, they don't have any consideration for the appropriate and profitable locations from existing land resources. For example, they are currently not able to get any informations about the mapping of the business potential digitally (spatial data). To solve these problems, a system that can provide geographic information as well as perform analysis for making decision about recommendations of business potential location is required. That information can be realized by utilizing Geographichs Information System (GIS) technology and Analytical Hierarchy Process (AHP) method. This system has been successfully tested using the white-box testing method for unit testing and the result is there are 6 independent-paths from Analisis Kriteria Class, 6 independent-paths from Analisis Alternatif Class, and 14 independent-paths from Ranking Class while the black-box testing method used for validation testing and the result is very good 100% (valid).
Penerapan Algoritme Genetika Untuk Optimasi Penyusunan Barang Dalam Mobil Box Fitria Dwi Nurhayati; Wayan Firdaus Mahmudy; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1008.886 KB)

Abstract

As the industry grows massively, the profits sought are also maximized by minimizing the cost of expenditure. One of the company's activities in minimizing the cost of expenditure is by optimizing the goods distribution process. Looking for patterns of arrangement of goods in the optimal goods distribution process is necessary to avoid the cost of such expenses incurred additional vehicle accommodation costs, overload of goods or even require more time if not using the system. Therefore, this research is done to overcome the problem of the preparation of goods in the car box for optimal use of genetic algorithm. Genetic algorithm is chosen because it can solve complex problems with a relatively fast time. In this study begins with initial individualization with random raised. The representation used is an integer representation. Then the process of reproduction of crossover and mutation. The crossover and mutation methods used by Partially Mapped Crossover and Reciprocal Exchange Mutation. Next is the selection process using Elitsm Selection. Based on the results of the tests that have been done, obtained accuracy of 84,6% with the best parameters that is on the population amount of 100, cr 0.6, mr 0.4 and generation 90. The final result obtained is optimization recommendations optimize the preparation of goods.
Pengembangan Aplikasi Manajemen Notula Rapat Menggunakan Google Speech API Berbasis Android Roliand Prasetya; Fajar Pradana; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1077.651 KB)

Abstract

In an organization, the number of mindsets of each member causes a difference of opinion. In order to unite the opinion together, it is necessary to conduct deliberation. one of the form of deliberation is by meeting. Faculty of Computer Science Universitas Brawijaya (FILKOM UB) is an organization that runs in education. FILKOM UB has a complex problem causing the meeting to be done repeatedly. One of solution is with the secretary which makes the notes of the meeting. However, the creation of meeting notes is still done manually so there is a possibility that meeting information can be lost. The Google Speech API is a speech recognition and can be used to record voice and convert to text to help creating meeting notes. Automatic Text Summarization with Term Frequency-Inversed Document Frequency method is automatic text summary which can be used to make conclusions from meeting notes that have been made by calculating the value or weight of a word in the document. Systems that include all the features that fit the requirements are implemented in the form of database structures, implementation of classes with Java language and interface implementation using XML language. This meeting notes management system has been successfully tested using white box testing method on unit testing and black box testing for validation testing. From these tests proves that the meeting notary management system can be used to assist the secretary in making meeting notes..
Co-Authors Abi Sajiwo Binar Swandito Adi Cahya Hermawan Aditya Rachmadi Aditya Yusril Fikri Agi Putra Kharisma Agus Wahyu Widodo Ahmad Fathur Rahman Ahmad Wildan Mukafi Aizul Faiz Iswafaza Alif Prasetyo Aji Alvin Naufal Wahid Amalia Safitri Hidayati Ananda Putra Alfa Robby Andra Pargiyani Anugrah Rasisputra Arda Firdaus Ramadhan Arief Andy Soebroto Arlian Gutama Bagas Andaryanto Bagus Aryo Herlambang Benyamin Fajri Chavindro Bunga Mardiasto Choirul Ichsan Basuki Citra Nadya Dwi Irianti Clara Pusparani Dedin Anike Putra Della Fauziah Denny Sagita Rusdianto Djoko Pramono Dwi Jan Prayogi Edy Santoso Elkaf Fahrezi Soebianto Putra Elsa Nuramilus Shofia Erine Ajeng Pratiwi Eriq Muhammad Adams Jonemaro Fachril Rachma Zulfidar Fadel Muhammad Hasanuddin Fahrir Rijal Fahmi Maulana Fairuz Zaki Faizatul Amalia Fajar Pradana Farid Widyatama Fatimatuz Zahro Febiyana Nur Yahya Fegreit Rizda Wibowo Fitra Abdurrachman Bachtiar Fitria Dwi Nurhayati Hafidz Aulia Setijadi Hario Budiharjo Helfi Pangestu Hidayatullah Agung Prasetyo Hugo Ghally Imanaka Husniyah Lisan Ihwan Latif Ilyas Abdi Nugraha Imam Cholissodin Indriati Indriati Irma Nurdianingtyas Johan Andi Saputra Josua Fernando Komang Candra Brata Kukuh Wiliam Mahardika Leny Mirta Sari Lutfi Fanani Mahardeka Tri Ananta Maulidiya Qurrota Ayun Meidina Masruria Primada Meidita Famirah Michelle Larassati Ayusmara Latukolan Miftah Muhammad Farhan Mikail Afghan Baihaqy Moch Ilham Nurmansyah Muhammad Faris Auzan Muhammad Iqbal Alvin Harlia Rahman Muhammad Kevin Andhiya Rizky Muhammad Rayyan Abhad Muhammad Tanzil Furqon Nadir Basalamah Nizar Rahman Kusworo Nur Afdaliyah Anwar Nurudin Santoso Priyambadha, Bayu R Moh Andriawan Adikara Rakha Fakhruddin Randy Cahya Wihandika Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Retno Inten Fitria Febri Reza Faridh Mashyuri Richa Amalia Permatasari Rizki Aziz Amanullah Rizky Ramadhana Riznin Ayustya Imandiena Robi Hidayat Roliand Prasetya Sueddi Sihotang Taruna Makki Satyanugraha Vicky Anggara Wayan Firdaus Mahmudy Widya Saptiani Yan Aditiya Nugraha Yoga Saputra Hariyanto Kusumo Yoshua Omega Maurya Yufita Berliana Putridewati Yuita Arum Sari