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All Journal Jurnal POINTER Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Reformasi : Jurnal Ilmiah Ilmu Sosial dan Ilmu Politik Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Bulletin of Culinary Art and Hospitality
Edy Santoso
Fakultas Ilmu Komputer , Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Klasifikasi Dokumen Tumbuhan Obat Menggunakan Metode Improved K-Nearest Neighbor Arinda Ayu Puspitasari; Edy Santoso; Indriati Indriati
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

The high utilization rates of medicinal plants is leading to increase the studies on it. Those studies certainly require documentation that contains information about medicinal plants. The large and scattered documentation cause difficulties in searching for information about medicinal plants. To overcome these problems a system that can classify the document automatically is needed to make the information search work more effective and efficient. K-Nearest Neighbor is the algorithm often used to classify text, but has a weakness in accuracy because of the fixed k values for each category. K values is the amount of the closest training data to the test data. Improved k-Nearest Neighbour is the algorithm used in this study to overcome the problem where the different k values will be applied based on the amount of the training data for each category. The average accuracy for the k values testing is 70,99%. The training data variation testing shows that the bigger amount of training data the higher average accuracy will be. The unbalanced data testing showed that the balance data training category has 1,9% better accuracy than the unbalanced category.
Pemodelan Sistem Pakar Untuk Menentukan Penyakit Diabetes Mellitus Menggunakan Metode Naive Bayes Studi Kasus : Puskesmas Poncokusumo Malang Irwan Andriyanto; Edy Santoso; 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

Preventation of diabetes mellitus bale to do if the patient knows the signs of diabetes mellitus. But people has difficulties to find it's signs. Because the expert in this subject is very less and the cost so expensive. That's why people need to help to prevent this deases by knowing it's signs by using expert system. One of method can use to know diabetes mellitus is Naive Bayes. Naive Bayes a statistic approach to do induction inferency in classification matter. This methode use probability. The basic of Naive Bayes is Training Data. Training Data is Diabetes Mellitus and it's signs that get from research object. The result comes from the biggest probability. Functional test gets 100%. It's means that the system works well. Bigger training data will get higher system accuration. The best accuration is 100% comes from 140 data training.
Sistem Pendukung Keputusan Untuk penentuan mustahik (Penerima Zakat) Menggunakan Metode Fuzzy AHP (F-AHP) Roma Akbar Iswara; Edy Santoso; Bayu Rahayudi
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

Rumah Zakat Malang City is one of the non-governmental organization of zalcat managers who receive and distribute zakat to mustahik. In the process of determining mustahik, the Rumah Zakat Kota Malang checks the data of the recipient to know some criteria that is Child Status, Total Income, Total Dependent and Child Raport Value. The criterion will determine which one gets the most zakat funds. However, the work done by Rumah Zakat in sorting the data is still done manually so it can cause the possibility of not exist in determining which side is more main to receive zakat because of its subjective nature and also need much time selection process that mustahik. Analytical Analytical Process Analytical Hierarchy is one of the better methods in the problem. From the results of calculations from 60 data, obtained the feasibility 91.67% where 5 different data generated with data from the home side of zakat malang. The AHP Fuzzy Method can be used in the determination of mustahik (zakat receiver).
Implementasi Metode Dempster-Shafer untuk Diagnosa Defisiensi (Kekurangan) Vitamin pada Tubuh manusia Yudha Eka Permana; Edy Santoso; Candra Dewi
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

In modern times, many people do not pay attention to the intake of nutrients in their daily food cosumption, especially the vitamin content. Vitamin is a complex substance that is needed by our body that serves to help the process of body activities. Vitamin deficiency can lead to an increase in the chances of getting disease in our body and allow the body functions not to work optimally. Checking the level of vitamin deficiency is very rarely done by the community, because it needs a blood test and the cost for the test is quite expensive. In this study the problems are solved by creating an expert system, a system that can diagnose the type of vitamin deficiency in the human body, so it can easily be known which type of vitamin deficiency suffered by the users. This system is implemented using Dempster Shafer method. Testing is done by comparing the conformity of the output of the system to the expert diagnosis. From the test of 30 case data obtained an accuracy of 87%. After testing by increasing the weight value of the symptoms, the accuracy rate increased to 90%. So this expert system can be used to assist users in making a diagnosis of deficiency or vitamin deficiency.
Implementasi Metode Ensemble K-Nearest Neighbor untuk Prediksi Nilai Tukar Rupiah Terhadap Dollar Amerika Rezza Hary Dwi Satriya; Edy Santoso; Sutrisno Sutrisno
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

The exchange rate is the currency unit price agreed by each country as a means of payment or transaction. The most used exchange rate in Indonesia is the rupiah exchange rate against the dollar. The dollar is the most stable currency in the economy. The high or low of the rupiah exchange rate is influenced by rates of interest, inflation, exports, imports, and sovereign debt. The exchange rate also has an important role in determining economic policy. In order to obtain an appropriate economic policy in the future situation and conditions, it is necessary to use a solution by using Ensemble kNN algorithm to predict the future rupiah exchange rate. The count of data was used in this research are 24 data training and 12 data testing. The data training and testing consists of 5 parameters, such as BI rate, Inflation, Export, Import, and sovereign debt. The Ensemble kNN algorithm uses a supervised learning, which the data testing is classified based on the majority of classes on kNN. The principle of kNN is to find the K variable from the data training which having closest similarity to the data testing. Ensemble technique is used to optimize kNN algorithm to get more accurate result. The result from this prediction system was evaluated by using MAE, MAPE and RMSEP. The obtained value of MAE buy = 456.56, selling MAE = 460.96, MAPE buy = 3.47%, MAPE selling = 3.47%, and RMSEP buy = 534.88, RMSEP selling = 540.07. The final result is the conformity of result and the pattern which produced between the predicted data and the actual data.
Sistem Pendukung Keputusan Penentuan Guru Berprestasi Menggunakan Fuzzy-Analytic Hierarchy Process (F-AHP) (Studi Kasus : SMA Brawijaya Smart School) Dewan Rizky Bahari; Edy Santoso; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Brawijaya Smart School (BSS) Senior High School Malang in producing competent and achieving students in both academic and non-academic fields requires educators / teachers with good competence in the field of education. In educational institutions, the process of determining outstanding teachers has been done relatively, school requires a certain standard in setting requirements for a teacher to get an allowance or to occupy a particular position. In addition, this assessment aims to evaluate and improve teacher's competence. In this research, a decision support system for assessment of teacher's performance using Fuzzy-Analytic Hierarchy Process (F-AHP) case study of SMA Brawijaya Smart School using six criteria there are pedagogic competence, professional competence, innovation development competence, technology utilization competence, social competence , and personality competence. The result from testing shown accuracy of system up to 82.501% with six criteria. Results of calculation, the application of Fuzzy-Analytic Hierarchy Process (F-AHP) method is expected to help the process for determining of teacher achievement in Brawijaya Smart School Malang Senior High School.
Penentuan Pemenang Tender Menggunakan Kombinasi K-Neareast Neighbor dan Cosine Similarity (Studi Kasus PT. Unichem Candi Indonesia) Surya Dermawan; Edy Santoso; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In decision of determination of auction in PT. Unichem Candi Indonesia is still manual. Due to this lack of knowledge in decision making. Data mining is also referred to as a series of processes to explore the added value of knowledge that has so far not been known manually from a data set. One of the technology that can be used for information system of tender winner determination is K-NN and cosine similarity which this technology become efficient and effective when applied to problem in PT. Unichem Candi Indonesia. The K-NN algorithm is a method that uses a supervised algorithm, where. The K value is the amount of nearest training data to the test data. From the test results the effect of the value of k obtained accuracy of 73% where the highest value, ie k = 2. Testing with the amount of trainee data and test data are balanced will affect the amount of accuracy that will be obtained. Based on the test results with the amount of training data and test data obtained an accuracy value of 83% where the highest value, ie k = 4. Keywords: Data Mining , k-nn Algorithm, Cosine Similarity.
Sistem Pakar Diagnosis Penyakit Hepatitis Menggunakan Metode Dempster Shafer Ayu Tifany Novarina; Edy Santoso; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Hepatitis is an inflammation of the liver. Inflammation is characterized by elevated liver enzyme levels, due to liver membrane damage or damage. There are two factors that cause the factors of infection and non-infectious factors. There are 5 main hepatitis viruses, referred to as types A, B, C, D and E. These 5 types are of greatest concern because of the burden of illness and death they cause and the potential for outbreaks and epidemic spread.There are many other viruses that potentially cause hepatitis such as adenoviruses, herpes simplex, HIV, rubella, and others. The problems that often occur today is still a lot of ordinary people who lack understanding of health. In fact, not infrequently people do not realize when they get the disease because they do not know the symptoms that cause patients late to handle early. In this study the problems are solved by creating a system by implementing the Dempster-Shafer method to diagnose the types of hepatitis disease suffered by humans, so the system is expected to assist users in diagnosing hepatitis disease in misery since early. Based on the results of system accuracy testing with 20 data samples obtained an accuracy of 90%. Inaccuracy of 10% is caused by several things, among others, the subjectivity of the expert in determining the disease and in the calculations performed using the Dempster-shafer method that uses the highest value without any optimization of the density value on any symptoms.
Sistem Absensi Menggunakan Teknologi Location Based Service (LBS) Muhammad Dimyathi; Edy Santoso; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Unichem Candi Indonesia (UCI) is a consumer good company with salt consumption product branded "refina". In the management regulation of PT. UCI there is a procedure attendance hours work hours at 08.00 WIB and come home from work at 16.00 WIB for Monday to Friday, while on Saturday at 08.00 to 14.30 WIB. Currently the Presence Employee attendance process has been using the Fingerprint Presence machine. Every employee in and out of the office without exception marketing personnel must do the Presence. Given this rule, marketing personnel objected. Due to within one business day, marketing personnel can go in and out of the office more than 3 times. The problem that often happens is to forget to do Presence, so that marketing personnel get a reprimand from superiors and penalty sanctions. As a solution to the problems that occur, the need for Presensi applications using Location Based Service technology (LBS). Where this technology becomes efficient and effective when applied to problems in PT.UCI. By using this application, marketing personnel no longer need to do Presence via fingerprint machine, but only need to bring a smartphone device that has been installed this application. This app works based on where the employee is located. When the employee is in coordinate office area then Presence status is enter office, while when the employee is outside the office area Presence status is out of office. Benefits derived from the results of this study is the marketing force no longer need to do Presence through the device fingerprint machine, but simply bring the Android smartphone device that has been installed by this application, so it can be marketing presence in the field.detected Presence status when out of office. In addition, the management can monitor the location
Sistem Pendukung Keputusan Untuk Penentuan Jumlah Produksi Nanas Menggunakan Metode Fuzzy Tsukamoto Agus Prayogi; Edy Santoso; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Great Giant Pineapple is one of the agro industry companies. This company performs activities ranging from pineapple cultivation to canning process. The problem faced by PT.Great Giant Pineapple is if there is excessive production then the pineapple will be placed in the storage warehouse as the supply and the pineapple has a consumption period that does not last long and can not be consumed because the pineapple has expired due to pineapple production in the storage warehouse too long. If there is a shortage of pineapple production then customers will be disappointed because the pineapple you want to buy is up. So, with it the company will lose customers and lose. Tsukamoto's method is an extension of monotonous reasoning. In the Tsukamoto method, every consequence of the IF-THEN rules must be represented by a fuzzy set with membership function. As a result, the inference output of each rule is given explicitly (crisp) based on the α-predicate (fire strength). The raw material inventory and the number of requests are used as variables that will be represented by the fuzzy membership function. Furthermore, fuzzy Tsukamoto method to determine the amount of production applied in Decision Support System (SPK), then SPK will process the data with Tsukamoto method and will display the output (output) in the amount of goods to be produced. Based on the results of accuracy testing obtained error value of small forecasting results that is 0,0607%. The results given by the Fuzzy Tsukamoto method are in conformity with the results of the data of PT. GGC with error value 0,0607%..
Co-Authors Abdul Juli Andi Gani Achmad Arwan Achmad Ridok Adam Hendra Brata Adhi Mulhaq Adhie Indi Arsyanto Adhipramana Raihan Yuthadi Adinugroho, Sigit Aditya Sudarmadi Agung Dwi Budiarto Agus Prayogi Ahmad Faizal Akbar Imani Yudhaputra Akhsana Zufar Masyhuda Alif Fachrony Alif Prasetyo Aji Andriko Hedi Prasetyo Annam Rosyadi Annisa Puspitawuri Arief Andy Soebroto Arinda Ayu Puspitasari Aulia Dinia Ayu Tifany Novarina Bagus Aryo Herlambang Bayu Rahayudi Bregaster Bregaster Brigitta Ayu Kusuma Wardhany Caesaredi Rama Raharya Candra Dewi Charisma Amadea Putri Dayu Aprellia Dwi Putri Dendry Zeta Maliha Denis Ahmad Ryfai Denny Sagita Rusdianto Dewan Rizky Bahari Dhatu Kertayuga Dian Eka R Dicky Manda Putra Sidharta Dimas Prenky Dicky Irawan Dino Keylas Dwi Tyas Fitriya Ningsih Dytha Suryani Edwar Budiman Ega Ajie Kurnianto Elkaf Fahrezi Soebianto Putra Elna Diaz Pradini Fahri Ariseno Faizatul Amalia Fajar Pradana Faldo Sabillah Shidqi Faris Dinar Wahyu Gunawan Faturrahman Muhammad Suryana Febri Fahrizal Freddy Ajax Pratama Galih Aulia Rahmadanu Genjah Amartha Gora Ghiffary Rizal Hamdhani Greviko Bayu Kristi Habib Putra Kusuma Negara Hafshah Durrotun Nasihah Heny Dwi Jayanti Herlina Devi Sirait Heru Nurwasito Heryadi Mochamad Ramdani Hinandy Nur Anisa Imam Cholisoddin Imam Cholissodin Indriati Indriati Irwan Andriyanto Ivan Agustinus Jauhar Bariq Rachmadi Jeffrey Simanjuntak Jodi Irjaya Kartika Jojor Yeanesy Sinaga Kenty Wantri A Khairinnisa Rifna Khrisna Indrawan Eka Putra Khusnul Aidil Santosa Komang Anggada Sugiarta Krisna Andryan Syahputra Effendi Lailatul Fitriah Lailil Muflikhah M. Ali Fauzi Made Bela Pramesthi Putri Marji Marji Maya Febrianita Meilinda Dwi Puspaningrum Meutya Choirunnisa Miga Palma Putri Mochamad Rafli Andriansyah Moh. Zulfiqar Naufal Maulana Mohammad Zahrul Muttaqin Muh Hamim Fajar Muh. Thanthowi Lathif Muhamad Danis Firmansyah Muhamad Fahrur Rozi Muhammad Alfian Nuris Shobah Muhammad Alimuddien Rasyid Muhammad Aminul Akbar Muhammad Ardhian Megatama Muhammad Atabik Usman Muhammad Aulia Rahman Muhammad Dimyathi Muhammad Fachry Noorchoolish Arif Muhammad Fauzan Ziqroh Muhammad Fuad Efendi Muhammad Miftah Dhiaulhaq Muhammad Shafaat Muhammad Tanzil Furqon Mukhlis Anshori Witanto Nendiana Putri Ninda Silvia Tri Cahyani Nonny Windarti Novanto Yudistira Novi Fadilla Ulfa Nurudin Santoso Nurul Hidaya Nurul Hidayat Paul Manason Sahala Simanjuntak Putra Aditya Primanda Ratih Kartika Dewi Regina Anky Chandra Renaldy Senna Hutama Reyhan Dzickrillah Laksmana Reynaldi Ricky Putra Utama Guinta Rezza Hary Dwi Satriya Rezza Pratama Rhayhana Putri Justitia Richard Emmanuel Johanes Riesma Rahman Nia Rio Cahyo Anggono Rizky Maulana Iqbal Rizky Ramadhan Rizqi Addin Arfiansyah Roma Akbar Iswara Salam Maulana Sari Narulita Hantari Satrio Hadi Wijoyo Sema Nabillah Dewi Shibron Arby Azizy Stefanus Bayu Waskito Supraptoa Supraptoa Surya Dermawan Sutrisno Sutrisno Syailendra Orthega Tara Dewanti Sukma Tibyani Tibyani Tjahjanulin Domai Tony Faqih Prayogi Tri Afirianto Tuahta Ramadhani Tubagus Agung Nugroho Vogue Nevarika Wa Ode May Zhara Averina Wahyu Dwiky Rahmadan Wayan Firdaus Mahmudy William Muris Parsaoran Nainggolan Wunsel Arto Negoro Yogi Pinanda Yudha Eka Permana Yuita Arum Sari Yulianus Wayan Yudistira Rudja Yunita Dwi Lestari Yuwilda Wilantikasari