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INDONESIA
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Published by Universitas Brawijaya
ISSN : -     EISSN : -     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering
Jurnal Pengembangan Teknlogi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya merupakan jurnal keilmuan dibidang komputer yang memuat tulisan ilmiah hasil dari penelitian mahasiswa-mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Jurnal ini diharapkan dapat mengembangkan penelitian dan memberikan kontribusi yang berarti untuk meningkatkan sumber daya penelitian dalam Teknologi Informasi dan Ilmu Komputer.
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Articles 10 Documents
 1 
Search results for , issue "Vol 1 No 5 (2017): Mei 2017" : 10 Documents clear
Pemodelan Sistem Pakar Diagnosis Penyakit Tanaman Apel Manalagi Dengan Metode Backward Chaining Menggunakan Certainty Factor Muhammad Burhannudin; Suprapto Suprapto; Nurul Hidayat
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

Kota Batu is one Agropolitan city located in East Java province with huge potential for development in agriculture. Apple is a fruit plant that can live well in the highlands. This plant in Indonesia since 1934. As other fruit crops, apples are also susceptible to the disease. Maintaining plants from disease is also an attempt to preserve the environment. One form of such vandalism is negligence of farmers in preserving plants from disease. Making this system an attempt to perform human roles. This system is expected to help farmers, in particular, to be able to identify precisely the apple crop diseases and appropriate. So can meminimalisi impact. This application is developed using PHP programming language and MySQL database. Both are a combination of the most popular in the manufacture of web-based applications. While the inference method used is Backward chaining which is based on the tracking of data or facts then led to the conclusion in the form of conclusions pests or diseases that attack the apple crop. Tests performed by comparing the suitability of the output with the diagnosis expert system. And of the 30 test cases the data obtained accuracy rate modeling expert system testing using methods Certainty Factor on apple crop disease diagnosis system amounted to 93.3%. With the accuracy of the results indicate that the system is able to replace the role of experts.
Sistem Pendeteksi Pencemaran Udara Ambien Di Kawasan Lumpur Lapindo Dengan Menggunakan Logika Fuzzy Reza Hastuti; Edita Rosana Widasari; Barlian Henryranu Prasetio
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

Lapindo hot mud in disaster area affected the quality of ambient air. Monitoring ambient air pollution in affected area of Lapindo hot mud performed by classifying the level of ambient air pollution. The classification also describes the impact that can occur from each category based on the level of ambient air pollution. Based on the result of testing system with samples from three affected areas of Lapindo hot mud, fuzzy output has the accuracy 84% in Siring Barat village, 93% in Mindi Village, and 95% in Jatirejo village by using methane gas, dust particle (PM10), and CO gas as parameters. Furthermore, Jatirejo village has an average index value of air quality is about 54.43 with an average methane concentration is about 4.60 ppm. Therefore, Mindi village has an average index of air quality is about 41.95 with an average methane concentration is about 2.40 ppm and Siring Barat village has an average index of air quality is about 37.00 with an average methane concentration is about 15.18 ppm. The analysis result shows the concentration of methane exceeds the threshold level even the air quality index in a safe range, It shows that the level of ambient air pollution in those three affected areas of Lapindo hot mud is in Hazardous level.
Klasifikasi Tweets Pada Twitter Dengan Menggunakan Metode Fuzzy K-Nearest Neighbour (Fuzzy K-NN) dan Query Expansion Berbasis Apriori Joda Pahlawan Romadhona Tanjung; Mochammad Ali Fauzi; Indriati Indriati
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

Twitter is a unique conversation tool that allows us to send and receive short messages called tweets in the Twitter community. Tweets are short messages that have a length of 140 characters. Tweets that appear on the homepage are all jumbled into one, posted variety ranging from the economy, sports, technology, automotive, healthcare and others. When users search for a news or information desired, the problem that arises is Twitter user difficult to find tweets. The classification process can be performed to categorize a tweets using an algorithm Fuzzy K-Nearest Neighbour. However, the process of classifying a tweets it is difficult to do because the tweets in the form of short-text. Therefore, before doing the classification process a tweets done preprocessing and word expansion beforehand with Query Expansion algorithms in order to provide maximum results in the classification. In the study conducted to produce the best accuracy by 82%. Best accuracy is obtained when using the Fuzzy KNN method with Query Expansion without preprocessing and threshold for the support value> = 0.15 and the value of confidence> = 1.
Identifikasi Penyakit Tanaman Jarak Pagar Menggunakan Metode Fuzzy K-Nearest Neighbor (FK-NN) Eva Agustina Ompusunggu; Dian Eka Ratnawati; Lailil Muflikhah
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

Jatropha (Jatropha curcas L., Euphorbiaceae) is a plant that has many uses that as a raw material medicines and vegetable oil (biodiesel). Jatropha is used to cure various diseases. Some people also make Jatropha as a main ingredient of their livelihoods. However, the quality of Jatropha decreased due to various diseases. Lack of knowledge about the disease of jatropha and do not know how to overcome it became one of the causes. As well as the unavailability of media for the public to know the diseases that attack. To know and make it easier to diagnose diseases that attack jatropha, a system needs to be made. To support this diagnosis used k-nearest neighbor and fuzzy method. The first step of this method is entering training data that contains symptoms. Then classification using the k-nearest neighbor and fuzzy. Then we get the result of this system which is the diagnosis of Jatropha's diseases from nine diseases that there are. Results of tests performed on this study, obtained the highest accuracy by 80%
Perancangan Pengendali Rumah menggunakan Smartphone Android dengan Konektivitas Bluetooth Angger Dimas Bayu Sadewo; Edita Rosana Widasari; Adharul Muttaqin
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

Home is a place to hide and gather with family. The house also has become the basic needs of every person who is married, then have a dream home is everyone's desire. The dream house is a comfortable home to live in. In today's technological developments are very rapidly making the home function in building a dream home to increase the comfort and safety of the inhabitants of the house. In this research will be designed home controller using android smartphone with bluetooth connectivity that can control the home appliance lamp, fan and celenoid door lock with monitoring function and timer padadevice built. In this study can be done in the same way. The result of the functional testing of wireless communications can still be done in the existing space of the wall barrier and the distance of 20 meters in open space. Functional timer goes well according to the added value and how to handle it by the sensor according to the desired result.
Penerapan Metode K-Nearest Neighbor (KNN) dan Metode Weighted Product (WP) Dalam Penerimaan Calon Guru Dan Karyawan Tata Usaha Baru Berwawasan Teknologi (Studi Kasus : Sekolah Menengah Kejuruan Muhammadiyah 2 Kediri) Nihru Nafi' Dzikrulloh; Indriati Indriati; Budi Darma Setiawan
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

World of particular employment agencies Vocational High School, many a teacher or school employee who less clever in technology of the current technological developments. Actually, it is in need of teachers and school administration employees who have qualified human resources high in the knowledge of science and technology. The school is in need it is because it affects how do learning on students in school. To meet the desired standards of quality teachers, during The Vocational High School Muhammadiyah 2 Kediri is selection and recruitment of teachers by means of manual employees. The selection has been done manually through the test phase 4 aspects of your application letter and attachments GPA averages, academic test, test general knowledge of science and technology (IPTEK), and interview. The data collection process for the selection still use manual. Therefore, we need a web-based system so that the selection acceptance of new teacher candidates can run more effectively and efficiently. On this website using K-Nearest Neighbor (KNN) and the method of Weighted Product (WP). K-Nearest Neighbor used to determine the weight of each criterion to classify the good or bad. After classifying the KNN method, the selection of prospective teachers will be recruited by the school Vocational High School Muhammadiyah 2 Kediri using Weight Product (WP). Weight Product used to determine the results of the classification by KNN method to perform a ranking in order to take the best results. Tests conducted consisting of, testing the accuracy of the value of K means and accuracy testing of the WP value criteria weighting method. The accuracy of the test results obtained suitability accuracy value by 94%, precision 80%, and recall 80%.
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%.
Implementasi Sistem Kontrol dan Monitoring pH pada Tanaman Kentang Aeroponik secara Wireless Andrika Wahyu Wicaksono; Edita Rosana Widasari; Fitri Utaminingrum
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

The needs of potato each year has increased, but not offset by increased production and land area for commodity crops of potatoes. To boost production in an increasingly limited land, aeroponics techniques into one solution for farmers who have no land availability. Aeroponics potato production techniques have yields more good than conventional techniques and with the land. PH is one of the elements that greatly affect the growth of aeroponic plant. The ideal pH range for an aeroponics system ranges between 5.5-6.5. Then the system control and monitoring is required in an aeroponics techniques. In this research for controlling and monitoring the State of a pH using wireless transmission. There are six nodes that is two nodes, one node sensor Coordinator, and three nodes of the actuators. From the test results obtained by the sensor data reading of pH value of 1% error within an error reading of 0.08 degree pH. Sensor data transmission using wireless data on delivery without hitch has the accuracy of data delivery of 99.98% with one node of the sensors and 96.13% with two sensor nodes. On delivery with the hitch has the level of accuracy of the data delivery of 99.93% with one sensor nodes and of 92.99% with two sensor nodes
Sistem Pendeteksi Dehidrasi Berdasarkan Warna dan Kadar Amonia pada Urin Berbasis Sensor TCS3200 Dan MQ135 dengan Metode Naive Bayes Rint Zata Amani; Rizal Maulana; Dahnial Syauqy
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

Dehydration is a condition when human body tissue's loss of fluid abnormally and this condition often underestimated by common people, so in case on serious level illness of dehydration will causes death. However nowadays to detect dehydration still according to analysis from health team by some clinical sign that cause dehydration. From this problem, it is needed a research about automatic system to detect dehydration level that can use by common people, so can decrease amount of dehydration's patient that untreated since begining. On this research, the parameters were used to compare dehydration's level are color and level of ammonia in human urine. The reason of using urine as research object is because urine condition reflect fluid condition in human body. Process to determine dehydration's level from color and level of ammonia in human urine is perform with read data color sensor TCS3200 and gas sensor MQ135 by Arduino Uno Microcontroler with Naive Bayes method. Naive Bayes method is selected as a technique to make a decision of dehydrations level because this method was one of classification method that good, which the classification classes of dehdydration level were already known since begining. From some testing result, it has known that the error percentage of color sensor TCS3200 on read the color object was 2,70% and the corelation value of gas sensor MQ135 reading with out voltage of sensor was 99,81%. And then on system testing by Naive Bayes method with amount of training data was 46 data and testing data as many as 23 data, the accuration reached 95,65% with average computation time was 0,69 second.
Penentuan Siswa Berprestasi Menggunakan Metode K-Nearest Neighbor dan Weighted Product (Studi Kasus : SMP Negeri 3 Mejayan) Jodi Irjaya Kartika; Edy Santoso; Sutrisno Sutrisno
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

Education has an important role to develop this country. The school as an educational institution must develop a variety of guidance systems that are motivating and developing potential of the student. One of them with the selection of student achievement.However, the general election student achievement is more focused in academic achievement. As in JHS 3 Mejayan, has no balance in election of student achievement because in the process of selecting student achievement weight voting greater than the value of the non-academic. So there a rises of a problem in determining the best weighting of each criterion both of them and it really takes time to selection of student achievement. To make it come true, needs to be made for a system that able to work fast and objectively in decision making so that the result were correct and could be called as student achievement. In manufacturing of a system is necessary to suppor the methods used. The methods used are K-Nearest Neighbor as a classifier and Weighted Product as to sorting. Based on the comparison between data expert with manually calculation from the school and output data system for K-Nearest Neighbor's method has an accuracy continuesly 56.67 % and 76.67%. Then, ranked comparison between data expert with manually calculation from the school and output data system for Weighted Product's method has an accuracy continuesly 11,1 % and 100%.

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