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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI)
Tibyani Tibyani
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Minyak Goreng Berdasarkan Frekuensi Penggorengan Menggunakan Metode K-Nearest Neighbor Berbasis Raspberry Pi Linda Silvya Putri; Fitri Utaminingrum; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cooking oil is often used by the people as stapel for frying food ingredients. There are several types of oil, one of which is vegetable oil. Vegetable oil contains essential fatty acid which has function to prevent constriction of blood vessel that will effect accumulation of cholesterol. The cooking oil used repetitively can cause various diseases. The cooking oil used repetitively will make the double bonds of oxidized oil, and form peroxide groups and cyclic monomers, and will contain trans fatty acid. From these problems, it is necessary to have a system that can classify frequency of the use of cooking oil. In this study, the parameters studied in cooking oil are from color and turbidity. To determine classification of the frying frequency in cooking oil, for color detection of R (Red), G (Green), B (Blue) is obtained from the results of raspberry pi camera readings, and for turbidity is obtained from LDR (Light Emitting Diode) readings by Raspberry Pi 3 by using the KNN (K-Nearest Neighbor) method. From the results of study, it is known that the percentage of accuracy from R (Red), G (Green), B (Blue) readings on a raspberry pi camera with TCS3200 censor is R = 98.102%, G = 98.072%, B = 96.732%. In study of system using the KNN (K-Nearest Neighbor) method with 72 training data and 30 test data, is obtained an accuracy K=1, K=3, K=5 73.33% with an average time computing system of 3.9 ms.
Rancang Bangun Sistem Pemilah Tomat Berdasarkan Tingkat Kematangan Lb Novendita Ariadana; Dahnial Syauqy; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In human life is heavily dependent on agriculture. To meet the needs of everyday human life then takes the process of planting, harvesting and land sports. For a short time as well as the limitations of power is a challenge that must be faced by the farmers. So did the problems facing tomato farmers who must sort out the tomato based on a different level of maturity - different. Tomato growers should be picking tomatoes first and then sort it based on the level of ripeness. This is done because each level of maturity tomatoes have different uses. Of the matter, the author makes a tomato based parser system level of maturity. Level of maturity is detected using the color tomato. To detect the color of the tomatoes then it needs three sensors on the left side, top, and right system. Tomato fruit is placed in the middle of the system on the box then motor stepper will push it so it just below the sensor. Then the color of tomatoes will be read by a third color sensor. After that the Bayes method will look for opportunities and will classify the tomatoes into three categories. After that the system will drain the tomatoes into the container according to the degree of ripeness by opening and closing the line using a servo motor. This research has as many as 45 data training data and each level has 15 kematangn data. The result of the test there is a 10 x 9 x 1 x and correct errors. From these tests can noted that 90% of system accuracy.
Sistem Pemilah Telur Ayam Kampung dan Ayam Negeri Menggunakan Metode Naive Bayes Hazal Kurniawan Putra; Dahnial Syauqy; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The value demand of chicken eggs in Indonesia is high, in the sector of trading, chicken eggs in Indonesia has dominating the market wich value of 65%, the rest is duck eggs,bird egg and quails eggs. There are two types of eggs, eggs produced by free-range chickens and eggs produced by domestic chickens. The difference between this egg, domestic chicken eggs is heavier than free-range chickens eggs. Because of these parameters, that's will be difficult differentiate between free-range and domestic chicken eggs, and this will take long time and lot of energy. Based of the problem, it is necessary to create a system that can be used to differentiate between free-range chicken eggs and domestic chicken eggs. Using TCS-3200 to measure the level of egg color based on red, green and blue values, and loadcell sensor to measuring egg weight, then it will be classified using the Naive Bayes Method, and status will be printed on LCD, all systems are processed on Arduino. Testing method focused on functionality, accuracy, and system performance. From the functional testing, this system has 100% value, so it can be concluded successful functional testing. For Accuracy testing, the system tested with 40 of training data and test data of 20 data and have accuracy 100%. Testing for performance, the system has an average processing time speed of 754,95 ms.
Implementasi Metode Template Matching untuk Mengenali Nilai Angka pada Citra Uang Kertas yang Dipindai Muria Naharul Hudan Najihul Ulum; Tibyani Tibyani; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Money is a valuable tools that are needed by all of the people for payment. Moreover, when people knowing about the money, the computer have limited ability to read the image of money. Computer is an electronic tool that used to receive and store the data, processing that and produce the output that already saved in the memory. The case of computer or robot that cannot notes the value of money because of the limited access in introducing the data, made the researcher provide a solutions from that problem to support the application of money which called template matching. A matching template is an input image that matches the linkeness of the test image. Based on that template matching method is designed for the data training and introduction of the data. A series of test was used in diagnostic to calculate the accuracy. So the average result will be 91% from all of the calculation of diagnostic test. Therefore, the error will state in front of money.
Implementasi Metode Klasifikasi Support Vector Machine (SVM) Terhadap Pemakaian Minyak Goreng Muhammad Yusuf Ramadan; Dahnial Syauqy; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The use of cooking oil repeatedly and beyond the normal limits (waste cooking oil) can cause variety of dangerous diseases to human health such as heart failure, stroke, coronary heart disease, and others. However, currently the use of recurrent cooking oil is still high. This is shown from the results of research in Semarang City, showing that 75% of respondents people use the same cooking oil for frying as much as 61.2 percent use it twice, 19.6 percent use it three times, and 5.4 percent use it as four time. Based on problems, it is necessary to have an automation system for classifying the frequency of the using cooking oil, so it can be used for the frequency classification of the use of cooking oil that has been used several times (waste cooking oil) accurately. In this study, the parameters used were the color and turbidity level of cooking oil. Determination of cooking oil classification is based on color and turbidity level of cooking oil was obtained from TCS3200 color sensor readings ADC and the resistance of the photodiode sensor by the Arduino uno microcontroller using the Support Vector Machine methods, because this method is one of the classification methods that are still rarely used, easy to understand, more accurate and has high computational speed. From the results of the tests performed, it is known the percentage error reading TCS3200 color sensor is 3.31% and the photodiode sensor can work well. So, if the cooking oil is more turbid, the value of the photodiode sensor is bigger. Furthermore, in testing the system using the Support Vector Machine method with the amount of training data as many as 60 data and test data as many as 13 data, obtained an accuracy of 92.3% with the average computing time for 4384.53 ms.
Implementasi Metode Klasifikasi Bayes Untuk Penentuan Keaslian Madu Lebah Berbasis Embedded System Ardiansyah Ardiansyah; Dahnial Syauqy; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Honey is a natural substance of the bees that carry a result plant secretions become flower's nectar. Bees are conserved with special care, will produce honey in a good quality. The benefits of honey are for health, beauty and food. We need a lot of time and cost to get honey in a good quality. Moreover, there are many honey's producer have mixed another ingredients like glucose, fluctose in pure honey to get a lot of profit income. The forgery of natural honey often did by seller. Therefore, technology needed to help society for testing authenticity of honey directly and quickly. To minimize these problems, this research has been designed a tool that can check the degree of authenticity of honey bees. In this research using some components that is Bayes methods or commonly called Bayessian Classification. Bayes method is one of method that can be used for processing inconsistent data and bias character. The function of color sensor TCS3200 is for checking the color of honey has been detected. Photodiode is an electronic device of semiconductor material that can be convert the light intensity in electric current, and pH sensors is a sensor that can measure the level of acidity accurately . Based on the results of testing accuracy, the level accuracy of clarification bayes method for honey's authenticity are 88,89%. While, the estimatin speed of time for processing system bayes methode to authenticity of honey has a speed average of 96,388ms.
Sistem Deteksi Lama Waktu Penyimpanan Daging Ayam Berdasarkan Warna Dan Kadar Amonia Berbasis Sensor TCS3200 dan MQ135 Dengan Metode Jaringan Syaraf Tiruan M. Adib Fauzi Rahmana; Dahnial Syauqy; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The length of time for storing chicken meat is the important factor that is related to the freshness and quality of chicken meat whether or not the meat is suitable for consumption. It is very important in determining the feasibility of chicken meat for consumption. In this research, it is designed a system that can be used fastly, accurately, and non-destructive. This system is implemented into an Arduino microcontroller by using gas sensors and color sensors as a measurement tool for determining chicken meat based on length of time storage. The process of inputting data is gained by data acquisition with two sensors, there are MQ135 gas sensor and TCS3200 color sensor which is able to read parameters in the form of ammonia levels and RGB colors. For the classification process, supervised learning algorithms are used from artificial neural networks that are able to recognize and group data based on predetermined targets at the beginning. There are 3 types of chicken meat based on the length of time storage. First, meat of chicken that are only slaughtered up to 12 hours long storage time. Second, it is stored longer than 12 hours up to 24 hours.The last, it has been stored for more than 24 hours. This research gave accuracy system of 86.7% in deciding time of period chicken meat time storage, by average computational time needed for 3.2 seconds.
Sistem Pendeteksi Kecelakaan Pada Sepeda Motor Berdasarkan Kemiringan Menggunakan Sensor Gyroscope Berbasis Arduino Aries Suprayogi; Hurriyatul Fitriyah; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Motorbikes are transportation that are generally in great demand by citizens of developed countries, especially Indonesia. With the increasing population and enthusiasts of motorbikes, the number of accidents in traffic will increase every year. The lack of handling of motorcycle accident sufferers at the time of the incident resulted in a high mortality rate. By knowing the slope of the motorcycle can be stated as an accident. Namely the slope of 10 ° - 50 ° for the left and the slope of 130 ° - 170 ° for the right. Therefore an accident detection system was built on a motorcycle based on the slope using a sensor gyroscope which was used to read the slope of the motorcycle, then sent a notification in the form of an SMS to the victim's family's cellphone via the GSM SIM900A Module. The MPU6050 sensor which is the reader of the slope value on the system installed on the motorbike will be processed on the Arduino Uno microcontroller. If the slope reading is stated as an accident, the GSM SIM900A Module will send a notification in the form of a help message to the relatives or families of the victims with the number that already exists on the GSM SIM900A module. By doing the slope alternately between left and right is selected with the roll value in the MPU6050 Sensor ranging ± -80.00- ± 50.00 expressed with an angle of 10 ° -50 ° and the slope value ± -20.00- ± 74.00 then expressed at an angle of 130 ° ¬ -170 ° the angles are expressed as the angle of the accident on the system and the boundary conditions are 60 ° -120 ° where the roll value is ± -21.00 - ± 1.00 which is declared as a normal system or does not send messages. The system will read the slope if it does not meet the boundary conditions of the roll angle, the system will immediately send a notification in the form of a message of assistance to relatives or victims' families with 80% accuracy if not constrained by the network / signal on the GSM SIM900A Module.
Implementasi Raspberry Pi Untuk Mendiagnosis Penyakit Diabetes Melitus Melalui Warna Lidah Menggunakan Metode Otsu's Tresholding Tri Putra Anggara; Rizal Maulana; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Misdiagnosis is the cause of treatment and maintenance of the disease to be inappropriate, perhaps even cause of death. Some technological applications are able to overcome misdiagnosis. In general, diagnosis uses technology used images as data to be processed. One disease that can be diagnosed is diabetes mellitus. In this research tongue images used to diagnose diabetes mellitus. The color of the tongue image is a parameter used to diagnose diabetes mellitus. Tongue image obtained from webcam by Raspberry Pi with the Otsu's Thresholding method. The tongue image before processing uses Otsu's Thresholding, image must be converted into grayscale, then Improves the histogram using the Histogram Equalization method. Based on the test results, the company can acquire images, become Grayscale imagery, generalize histograms by histogram equalization method and be able to diagnose diabetes mellitus through tongue color. The result of testing the acquisition image result was obtained on 100 %, testing the system the diagnosis of diseases diabetes mellitus against patients diabetes mellitus obtained accuracy 80 % and testing the system the diagnosis of diseases diabetes mellitus against patients non diabetics mellitus obtained much as 90 % accuracy. The average of the past computing time towards the tongue diabetics mellitus 0.3 seconds and computing the average of the past time towards the tongue non diabetics mellitus 0.4 seconds.
Optimasi Travelling Salesman Problem Pada Angkutan Sekolah Dengan Menggunakan Algoritme Hybrid Discrete Particle Swarm Optimization (Studi Kasus: MI Salafiyah Kasim Blitar) Ana Holifatun Nisa; Imam Cholissodin; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The policy of using school buses as a means of transportation to take students from school to home is very helpful for their role as parents. Moreover the distance between home and school is quite far and the age of students is still young. The constraints of the system between school transport can not be separated from the name of the efficiency of the time needed, but also the comfort of the students and the trust of the parents. With the optimization of the problems of the delivery route from this school bus, it is expected to minimize problems that can occur, including: traffic accidents due to the use of private vehicles; reduce fears of parents; so that it can increase student satisfaction with the optimization of delivery time. The algorithm used to optimize the Traveling Salesman Problem (TSP) problem is Hybrid Discrete Particle Swarm Optimization (HDPSO). In this study using data from students of Blitar's Salafiyah MI MI, which in the process of going to the house were divided into 2 groups, namely: the first group of 20 people and the second group of 24 people. From the results of testing the system compared to the actual data, the biggest difference was obtained on the second day of 2,69 Km (10,7%) in the first cluster and 22,8 (41%) Km in the second cluster.
Co-Authors Abi Dwijo Sukma Adinugroho, Sigit Aditya Dwi Wicaksono Adlan Husein Malahella Adnan Mahfuzhon Agung Bachtiar Sukmaarta Agung Cahya Kurniawan Ahmad Afif Supianto Akhmad Rohim Ana Holifatun Nisa Andrew Adi Nugraha Angga Dwi Apria Rifandi Anindya Agustina Damayanti Anisa Dwi Novita Rika Ardiansyah Ardiansyah Aries Suprayogi Ayang Setiyo Putri Bagus Cakra Jati Kesuma Barlian Henryranu Prasetio Belqis Putri Himmatul Karimah Bilal Benefit Buce Trias Hanggara Budi Darma Setiawan Dahnial Syauqy Davriwan Dzaky Muttaqien Diah Priharsari Edwin Yosef Setiawan Sihombing Edy Santoso Fadhlillah Ikhsan Faizatul Amalia Fitriyah, Hurriyatul Galih Ariwanda Gembong Edhi Setyawan Hazal Kurniawan Putra Ians Adji Adhitama Imam Cholisoddin Imam Cholissodin Imam Ghozali Indah Riska Aulia Irvan Windy Prastyo Irwan Kurniawan Issa Arwani Ivarianti Sihaloho Kamal Irsyadillah Kevin Aditya Firmansyah Putra Kholif Beryl Gibran Kresna Wiska Kafila Lailil Muflikhah Lb Novendita Ariadana Linda Silvya Putri Luthfi Anshori M. Adib Fauzi Rahmana M. Ali Fauzi M. Rizzo Irfan Mochammad Hannats Hanafi Ichsan Mochammad Izzuddin Moh. Ibnu Assayyis Muchammad Cholilulloh Muhammad Resna Muhammad Rizki Augusta Muhammad Sanzabi Libianto Muhammad Yusuf Ramadan Muria Naharul Hudan Najihul Ulum Nabila Divanadia Luckyana Nurul Hidayat Paul Manason Sahala Simanjuntak Pitoyo Peter Hartono Priscillia Pravina Putri Sugihartono Putra Pandu Adikara Ramadhan Anindya Guna Aniwara Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rich Juniadi Domitri Simamora Rivan Haposan Rizal Maulana Ryan Bayu Permadi Sarah Aditya Darmawan Siti Nafiah Sutrisno Sutrisno Tegar Assyidiqi Nugroho Tobing Setyawan Tri Putra Anggara Utaminingrum, Fitri Valensiyah Rozika Widhy Hayuhardhika Nugraha Putra Yanuar Enfika Rafani Yogi Suwandy Yuita Arum Sari