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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer JPSriwijaya Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi
Fakultas Ilmu Komputer Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Neuroscience Public Health

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Pembangkitan Nilai Belief Pada Dempster-Shafer Dengan Particle Swarm Optimization (PSO) Untuk Penentuan Pasal Kasus Penganiayaan Merry Gricelya Nababan; Rekyan Regasari Mardi Putri; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 10 (2017): Oktober 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The crime against the body and life continues to increase every year, judges as decision makers against criminal defendants have a very important role in providing decisions. However, there are some things that the judge needs to consider in making decisions, so that the problem of uncertainty can be a judge's obstacle. The author applies a method that can solve the problem of this uncertainty is Dempster-shafer (D-S). D-S algorithm has belief value that serves to determine the influence between symptoms obtained from an expert. In this case the expert can not give the value of belief karana must be in accordance with the evidence and real sanctions. So with Particle Swarm Optimization algorithm (PSO) belief value will be raised as well as doing optimization to get maximum results. In accordance with the test conducted from the case data of the penganiaayan obtained maximum belief value based on PSO parameter test. The result of system accuracy calculation by using belief value that has been optimized with D-S on 29 cases of abuse shows accuracy of 13.79%. The result of this accuracy is not maximal due to complex problems with the output (Output) of the system more than one. For further research, we can use Artificial Neural Network (ANN) method or with algorithm Analytic Hierarchy Process (AHP).
Optimasi Biaya Pemenuhan Asupan Gizi pada Makanan bagi Anak-Anak Menggunakan Metode Simpleks Dua Fase Pratomo Adinegoro; Rekyan Regasari Mardi Putri; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 10 (2017): Oktober 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Children are part of a group of human age classification which are 0 - 12 years old. Fulfilling the nutrition requirement for the children is really important for their healthy life. One of the best way to fulfilling the nutrition requirement is by fulfilling the requirement of macronutrients. However, the ability of fulfilling the nutrition requirement is depending on how much they should spend their money on. Therefore, the optimization is needed to determine the best combination of food which can fulfil the nutrition requirement for the children and have a minimum cost. Simplex two-phase is one of optimization method from linear programming study. Simplex two-phase will minimize the cost to fulfil the nutrition requirement for the children. The outcome of this method calculation will be the quantity of food and the cost of it. The result show that the existence of feasible solution is determined by the selected foods and their cost which build the constraint function. Then, 0.1(or 1.5 gram) is the value of amount of food variable which has the minimum cost.
Peramalan Dosis Pupuk Berdasarkan Karakteristik dan Lingkungan Tanaman Jeruk Siam Menggunakan Metode Backpropagation Muhammad Najmi Ridhani; Rekyan Regasari Mardi Putri; Sutopo Sutopo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Citrus is one of the horticultural plants which are popular in Indonesia but the citrus production from year to year has fluctuated. There are some main causes that affected to the fluctuation of national production of citrus which are climate, environment, and diseases. One way to overcome the climate, environment, and diseases of citrus production is to provide fertilizer at the right dose and proportional to that matched with the environment and its characteristics. This study aims to forecast the dosage of citrus fertilizer according to the characteristics and environment. This study uses Artificial Neural Network (ANN) backpropagation. The architecture a network of 3 nueron input layer that represents the related parameters is width of the canopy, soil texture and rainfall, one hidden layer, and 3 nueron output layer that represents the composition of the fertilizer that is nitrogen, phosphorus, and potassium. The best network architecture design for forecasting doses of citrus fertilizer are 3 input neurons, 5 nueron hidden layer and 3 output neurons. The value of the learning rate used is 0.3 with the maximum iteration of 500 and the training data is 56 and the test data 8. The Mean Absolute Precentage Error (MAPE) evaluation value of the composition data of the fertilizer dose is 9.178% obtained from average error of dose of nitrogen, phosphorus, and potassium fertilizer.
Sistem Pakar Diagnosis Penyakit Schizophrenia Menggunakan Metode Bayesian Network Rima Diah Wardhani; Rekyan Regasari Mardi Putri; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Schizophrenia is a severe mental disorder that contains thoughts, language, perceptions, and self-awareness. There are several types of schizophrenia. The relationship between the type of schizophrenia and its symptoms has uncertainty, where a symptom A is not necessarily only result in schizophrenia type X, but can lead to schizophrenia type Y. In rural areas, mental health facilities are still inadequate, so that the people there treat patients with schizophrenia with unnatural as at the brackets even in stocks. Actually, people with schizophrenia can be handled with the provision of drugs and psychological therapy with regular. Based on these problems, the authors create expert systems that are able to find solutions as do an expert in diagnosing and providing treatment solutions in patients with schizophrenia. Thus, general practitioners in small community clinics or hospitals in small areas can diagnose patients suffering from the schizophrenia. This expert system uses Bayesian Network method, PHP programming language and MySQL database. Experimental functional test results show all functional requirements can run well. In addition, the highest accuracy test results in testing the variation of training data is 92.86%. With the results of such accuracy, this expert system has a good performance to make the diagnosis of schizophrenia disease
Implementasi Metode Profile Matching untuk Seleksi Penerimaan Anggota Asisten Praktikum (Studi Kasus : Laboratorium Pembelajaran Kelompok Praktikum Basis Data FILKOM) Fran's Dwi Saputra Atmanagara; Rekyan Regasari Mardi Putri; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Practicum is a learning method that is attempted to learners to better understand about the related learning materials. With practicum activities are expected learners can be more exploration about the material being studied. One of the factors so that learners can follow practicum activities well is with the guidance of a practicum assistant who has human resources (HR) quality. The selection process at the time of admission of a practicum assistant member is needed to find qualified human resources assistant assistant. The acceptance of a practicum assistant member is not expected to be subjective so that the quality of the assistant laboratory assistant obtained can be in line with expectations, so that no one will be harmed and more easily perform the task as a member of the practicum assistant. Profile Matching is one of the most suitable decision-making methods for selecting membership acceptance according to the required criteria. Profile Matching is a decision-making mechanism by assuming that there is an ideal predictor variable level that must be owned by an individual, not a minimum level that must be met or skipped. The result of system accuracy calculation by implementation Profile Matching method shows an accuracy of 86.6% in the recruitment stages of new members and 83.3% in the division placement stages. The performance of a designed system can be used to make a member accept decision with output in the form of ranking based on the highest end value to the lowest final value.
Penentuan Kelayakan Lokasi Usaha Franchise Menggunakan Metode AHP dan VIKOR Vienticentia Imanuwelita; Rekyan Regasari Mardi Putri; Faizatul Amalia
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Franchise is a type of businesses that offers various benefits such as the good reputation and the stability of operating procedures. Nevertheless, the franchise business could be closed to bankruptcy, one aspect which influences that fact is the location factor. Site selection that does not meet certain criteria has a direct impact on the failure of the franchise business. The determination of the business location feasibility for the object under study has a computational pattern that is not clear, not directional and not concrete. Therefore, it is important to establish the appropriate business location feasibility supported by proper calculation patterns. This research proposes AHP and VIKOR methods to build system that can answer Multi Criteria Decision Making (MCDM) problem for feasibility of franchise business location. The AHP method is used to derive the weighting value of all criterias, while VIKOR focuses on the ranking of alternative business locations and proposes compromise solution. Based on the testing performance, the highest accuracy obtained is 85% with threshold value of 0,56. The sensitivity of VIKOR value while value is changed derived four alternatives that are sensitive to that change. The final result obtained is the eligibility status of each proposed business location.
Penerapan Bayesian Network Pada Sistem Pakar Ekspresi Wajah dan Bahasa Tubuh Melalui Pengamatan Indra Penglihatan Pada Foto Muhammad Adiputra; Rekyan Regasari Mardi Putri; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Facial expression and body language is a non-verbal language that can describe the real emotion in a person. Movement on facial expressions and body language shown by humans not only contains. Other than that, for some cases it needs a combination of facial expressions with body language to know the hidden meaning in it. The expert system of facial expression and body language is the application of probabilistic theory and graph theory on the bayesian network method. The purpose of making this expert system is to identify the meaning of emotion that a person shows through facial expression and body language. There are 7 expressions of feelings and emotions that becomes the system output, that are: lie, honest, angry, sad, fear, happy, and suprised. Based on testing of variation data training, it was found that the amount of data training and variation of it also affected the accuracy of the system result. In addition, it is also known that more data training used and more varied, it will increase the level of accuracy. While based on the results of the test using the f-measure method conducted on 5 cases containing 28 images, where each picture shows facial expression and body language of 5 different people, obtained the average of 80.47% precision, 86.34% recall, and an accuracy level for f-measure is 80.31%.
Sistem Pakar Diagnosis Penyakit Mulut menggunakan Metode Bayessian Network Ridho Adi Febrian; Rekyan Regasari Mardi Putri; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Oral ulcer is a condition that occurs around the oral cavity that can be caused by several factors such as fungi, bacteria, viruses, anti immune, and allergies. The problems are symptoms of oral ulcer between diseases in the same category have a high similarity that required knowledge and expert experience to diagnose the disease. Based on these problems, researchers designed a system of oral ulcer experts who have expert knowledge to obtain a diagnosis of oral ulcer along with medical treatment required by the patients. The method used in the knowledge base of this expert system is bayessian network with PHP programming language and using mySQL database. Based on the results of functional testing using blackbox test method obtained all functions can run well and in accordance with the design. While the accuracy test obtained the best accuracy of 86.13% through 3 experiments with different variations using 23 test data. With a fairly high accuracy results then the oral disease expert system using Bayessian network method is concluded to have good performance.
Implementasi Algoritme Support Vector Regression Pada Prediksi Jumlah Pengunjung Pariwisata Mimin Putri Raharyani; Rekyan Regasari Mardi Putri; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tourism has an important role for the economic growth of a region. One of the factors affecting the tourism revenue sector is the number of visitors. The more number of visitors can increase revenue, if the number of visitors decreased it will have an impact on the development of tourist attractions that can harm the manager of tourism. The prediction system of the number of visitors is needed as an illustration of the level of the number of tourism visitors for the period to come and can provide information to the managers of tourism to prepare better facilities and infrastructure and able to manage income and expenses to minimize losses. The prediction of the number of visitors to tourism can be done by applying the Support vector regression algorithm. Support vector regression algorithm is a method that can solve regression problems and produce good performance in the solution. In this study data used 72 data on the number of visitors monthly on tourism from 2010 to 2015. Test results show that the average value of MAPE minimum generated is 9,16% and the best MAPE value obtained is 6,98% which means The average difference between the predicted result and the actual data is 115 visitor number with sigma parameter = 925,8409 lambda = 0,3868, cLR = 0,0802, epsilon = 1,27E-10, complexity = 3234,539, maximal iteration 5000.Keywords: prediction, tourism, visitor number, support vector regression
Penerapan Metode K-Means-ACO Untuk Pengelompokan Biji Wijen Berdasarkan Sifat Warna Cangkang Biji Pangestu Ari Wijaya; Rekyan Regasari Mardi Putri; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sesame is one kinds of the groceries that produce vegetable oil. Nowadays, the needs of sesame is increasing so it is necessary to pick a good quality in producing sesame. To conduct sesame plants crossing, the color of sesame seed shell is very infuential on its quality. Several previous studies used in this research has been done to cluster sesame seed with qualitative and quantitative method. The qualitative method in this research is conducted by field observation while the quantitative method is conducted by processing the sesame data from measurement result by using chromameter which resulted of an L*, a* and b* color. Several previous studies has successfully done the clustering by using qualitative method namely IWOKM, PSOKM and GAKM method. This study will categorize and compare the result of sesame data with same of data by using K-Means-ACO method with the previous method. From several journals, the method is proved that K-Means-ACO method has optimal results because in the analysis step combined the optimization and clustering algorithm method. Based on the test results of the K-Means-ACO method compared with the previous method, the good result of clustering sesame seed based on the color of the seed shell. It is proven by the grouping result is 233:58. After all, this research could be concluded that the K-Means-ACO method could be used as the alternative method to conduct the sesame seed classification based on its seed shell color.
Co-Authors Achmad Arwan Agung Setia Budi, Agung Setia Agus Wahyu Widodo Ahmad Izzuddin Ainun Najib Eka Christianto Akbar, Muhammad Faithur Adel Patria Albert, Muhammad Zaidan Aldo, Muhammad Alhasyimi, Dana Mustofa Alqadri, Aikal Ichsan Annuranda, Ramansyah Eka Aulady, Fadhli Barlian Henryranu Prasetio Budi Darma Setiawan Candra Dewi Candra Dewi Chusnah Puteri Damayanti Dahnial Syauqy Dharmawan, Fakhriz Thoriqo Dian Eka Ratnawati Edy Santoso Eko Setiawan Eko Setiawan Elsa Nuramilus Shofia Endah Utik Wahyuningtyas Faizatul Amalia Fajar, Sanhnai Fathirul Firdaus, Muhammad Alifiansyah Firza Zamzani, Muhammad Fitra Abdurrachman Bachtiar Fitriyah, Hurriyatul Fran's Dwi Saputra Atmanagara Frans Agum Gumelar Gembong Edhi Setyawan Haqiqi, Farih Akmal Herlambang, Romario Yudo Hisdianton, Oktavian Hurriyatul Fitriyah, Hurriyatul Ichsan , Mochammad Hannats Hanafi Imam Cholissodin Indriati Indriati Irfan Muzakky Nurrizqy Iunike Kartika Dewi Karuniawan Susanto Khoirin Nisa Fitrianur Kurniawan, Rafi Athallah Kusuma, Aji Ranca Lailil Muflikhah Luthfi Anshori M. Ali Fauzi Mahar Beta Adi Sucipto, Ekmaldzaki Royhan Malik, Hifdzul Manoeroe, Gregorio Maryamah Maryamah Merry Gricelya Nababan Merry Gricelya Nababan, Merry Gricelya Mimin Putri Raharyani Moch. Maulana Alrizzaqi Muhammad Abduh Muhammad Adiputra Muhammad Najmi Ridhani Muzayyin, Asep Niken Hendrakusma Wardani Ningsih Puji Rahayu Nurkhoyri, Ageng Nurrizqy, Irfan Muzakky Nurul Auliyah Pamungkas, Gilang Alif Pangestu Ari Wijaya Pardamean, Yohanes Pratama, Muhammad Naufal Rafi Pratomo Adinegoro Pricillia, Lidya Ruth Rakhmadhany Primananda, Rakhmadhany Rakhmadina Noviyanti Ramadhan, Wafdannur Ramadhani, Roihaan Randi Pratama Nugraha Randy Cahya Wihandika Randy Cahya Wihandika Ridho Adi Febrian Rima Diah Wardhani Rizal Maulana, Rizal Rizqi Muh. Muqoffi Ashshidiqi Satria Dwi Nugraha Satrio Agung Wicaksono Sevtyan Eko Pambudi Siswanti Supraptoa Supraptoa Sutopo Sutopo Sutrisno Sutrisno Syahwanto, Virandy Bagaskara Tegar Assyidiqi Nugroho Tibyani Tibyani Utaminingrum, Fitri Vienticentia Imanuwelita Wijaya Kurniawan Yusi Tyroni Mursityo Yusuf Priyo Anggodo, Yusuf Priyo Zahra Swastika Putri Zarkasyi, Muhammad Rifky Irfan Zultoni Febriansyah