cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota malang,
Jawa timur
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.
Arjuna Subject : -
Articles 6,850 Documents
 46   47   48   49   50 
Pengenalan Entitas Bernama untuk Identifikasi Transaksi Akuntansi Menggunakan Hidden Markov Model Rika Raudhotul Rizqiyah; Lailil Muflikhah; Mochammad Ali Fauzi
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 (906.78 KB)

Abstract

Accounting is a task which has an important role in supporting economic continuity, due to the recording of any business process that occurred was done in accounting. However, the recording of financial transactions in accounting for identification into journal is still done manually, so that required classification and extraction of information contained in the accounting transaction text to make it easier. Named Entity Recognition (NER) is the first step needed to perform information extraction. To solve this problem, named entity recognition done for identification of accounting transaction. In this research used method of Hidden Markov Model (HMM), because HMM can resolve labeling task and and known robustly in performing named entity recognition. The main process in this named entity recognition is divided into modeling process using Hidden Markov Model and decoding process using Viterbi Algorithm. In this research will be recognize 12 entities namely DATE, TITLE, PER, TRANS, EXP_MON, TYP_COMP, FIRST_ORG, SECOND_ORG, EXP_DATE, NO_DATE, MONTH and YEAR. Overall entity recognition with addition Laplace Smoothing and Regular Expression techniques produce a value of average precision, recall and f-measure consecutive 81.75%, 87.88%, and 82.39%.
Evaluasi Manajemen Risiko Teknologi Informasi Menggunakan Kerangka Kerja COBIT 5 (Studi Kasus Pada Perum Jasa Tirta I Malang) M. Habibullah Arief; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (773.408 KB)

Abstract

The amount of contribution from telemetry system to support the main job of Perum Jasa Tirta I Malang on handling the flood prevention, making telemetry system as a vital system that must be spared from the risks. That risk might obstruct and effect the result of flood monitoring which potencially harmfull to society. Perum Jasa Tirta I Malang was established a policies about risk management, include managing the risk profile. An evaluation on the implementation of information technology risk management in Perum Jasa Tirta I Malang was done to measure the capability level accomplishment. Cobit 5 framework, especially in process domain EDM03 (Ensure Risk Optimisation) and APO12 (Manage Risk), was used as the basis of the evaluations, it turned out that capability level for both of process domain EDM03 and APO12 were on level 2. Target of capability level that want to be achieved by Perum Jasa Tirta I Malang for both of process domain EDM03 and APO12 are on level 3. In other words, the interval of deviation (gap) from the two domain process was 1. And then, risk identification was needed to figure out wether the current control was appropriated. Besides that, risk assessment was also needed to reduce impact and probability of the the risks. From the evaluation result, recomendation and mitigation strategy ware made to support the improvement for the implementation of risk management information and technology at Perum Jasa Tirta I Malang.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1244.744 KB)

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.
Prediksi Jumlah Pengangguran Terbuka di Indonesia menggunakan Metode Genetic-Based Backpropagation Dyva Pandhu Adwandha; Dian Eka Ratnawati; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 4 (2017): April 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1389.588 KB)

Abstract

The number of open unemployment in Indonesia has increased and decreased every year. The factors that can make unemployment happens is the number of the labor force is not balanced to the available jobs. In addition, the weakening of labor absorption in some industrial sectors has also the cause of the increasing number of open unemployment in Indonesia. Predict the number of open unemployment, expected can help the government and related parties to take the appropriate policy to reduce the number of open unemployment in Indonesia. Genetic-based backpropagation is one of the methods that can be implemented to perform predictions. This method performs weight and biases optimization process as parameters in backpropagation training. In this research the result value of Average Forecast Error Rate (AFER) of backpropagation method is 4.715198444% and genetic-based backpropagation method is 3.877514478%. Based on the result value of AFER, genetic-based backpropagation method can be used to predict the number of open unemployment in Indonesia with a better accuracy.
Penerapan Parallel Genetic Algorithm untuk Optimasi Penyusunan Bahan Makanan Keluarga Penderita Hiperkolesterolemia Anandita Azharunisa Sasmito; Imam Cholissodin; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1058.971 KB)

Abstract

Cholesterol is a fatty substance that is essential for the sustainability of body functions. However, if cholesterol is above normal levels, the body can not eliminate it and will accumulate in the arteries that can cause heart attacks or strokes. A person with hypercholesterolaemia should maintain a diet and nutritional intake. The composition of food consumed should be in accordance with the needs. Unfortunately, few Indonesians realize the importance to pay attention to the diet and nutritional content of the food consumed each day. The algorithm to be used in this research is parallel genetic algorithm (PGA) where the algorithm is the result of modification of the genetic algorithm. In the PGA population will be divided into several sub-populations that run in parallel. In this study PGA still uses the concept of multi-population and migration but will only run on a single processor. In the application of parallel genetic algorithm for this research resulted the highest fitness solution using method parameter with popsize number of 65, sub population of 5, using generation 60, crossover rate with value 0,4 and mutation rate equal to 0,6, Permutation with value 145.
Klasifikasi Berita Online dengan menggunakan Pembobotan TF-IDF dan Cosine Similarity Bening Herwijayanti; Dian Eka Ratnawati; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1034.548 KB)

Abstract

In discussing the online news by using the weighting of tf-idf and cosine of this similarity the previous research reference on online news information using single pass clustering algorithm, where the data to be used comes from the online news website that is kompas.com. Because of the many news that is on the website, so sometimes the news is posted not in accordance with the category. Human error will be the problem of wrong news posting. In addition to posting errors online news groupings are also important for the convenience of users to search for news according to their category. Implementing online news stories using tf-idf and cosine similarities, preprocessing processes ie tokenizing, stopword and stemming can reduce the term process of speeding the weighting of terms using tf-idf and accelerating the cosine process of similarity. The goal is to facilitate human error as well as reduce caution categorization. The value is able to classify news with accreditation rate of 91.25%.
Implementasi Algoritma Particle Swarm Optimization (PSO) untuk Optimasi Pemenuhan Kebutuhan Gizi Balita Leni Istikomah; Imam Cholissodin; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1207.22 KB)

Abstract

Toddlers are children with 1-5 years age range. According to Riskesdas, in the year 2007, 2010, and 2013 the percentage of cases of malnutrition tends to increase, especially in toddlers. In the fulfillment of nutrients, one type of food alone is not enough so it requires a variety of food ingredients that contain all the elements of nutrients. Efforts to improve child nutrition have been done by the government through Posyandu to monitor and provide more servants to toddlers. Nutrition needs of Indonesian people has been set in the guidelines of Pedoman Gizi Seimbang by the Ministry of Health Republic Indonesia, including nutritional guidelines to meet the nutritional needs of infants. However, the nutritional guidelines only provide the value of the nutrient content of each foodstuff, making it difficult for Posyandu staff to provide menu variations to fit the needs of children according to their health condition. In this research give recommendation of variation of foodstuff automatically by using optimization process of Particle Swarm Optimization algorithm so that it can facilitate Posyandu and parents of toddlers in providing daily food according to the nutritional needs of toddlers. Based on the test results, the most optimal parameter is the number of particles = 30, Wmin = 0.4, Wmax = 0.7, C1 = 2, C2 = 1.5, Number of iterations = 40 and Upper Limit Permutation number of 75 resulting in average energy, protein, fat and carbohydrate difference of 16.04%, -8.08%, 2.85% and 25.98% which can save parents toddlers by 28.56%.
Implementasi Low Power Multi Sensor Node pada Wireless Sensor Network Muhammad Fatikh Hidayat; Barlian Henryranu Prasetio; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1331.482 KB)

Abstract

The power source is one of the important things that have to be noticed at the application of WSN on wide area scope, data transmission and monitoring scope of sensor module that used by sensor node cause high amounts of sensor node required. Especially if the node only use to monitor a type of environmental condition, while the monitoring needs are required to be able to monitor many type of condition, on those case more amounts and also power sources needed according to the area and the type of environmental condition to be monitored by sensor nodes. To be able to solve the problem, the authors implement a sensor node equipped with multi sensors and including a low power mechanism that is useful to determine when the sensor node will activating sleep mode or not. The sensor node is designed using ATmega328P as microcontroller with NRF24L01 as wireless communication module, equipped RTC module as time data source which use as time stamp of running system. With the low power mechanism inside the sensor nodes reduces current consumption up to 65,3%, so as to extend the active life of the sensor node compared with the absences of the low power mechanism.
Analisis Performansi HTTP Networking Library pada Android (Studi Kasus: Portal Berita) Mochammad Syaifullah Ferryansyah; Mahardeka Tri Ananta; Lutfi Fanani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (598.6 KB)

Abstract

The development of technology that more sophisticated, making the news spread faster. Initially news is presented in conventional forms such as newspapers. Slowly the news is presented in the form of mobile apps. In its implementation, application developers use various libraries to create a news portal. The frequently used libraries include HttpURLConnection, Asynchronous Http Client, Retrofit, and OkHttp. But the performance of each library is unknown. Therefore, needs a research to provide performance information from each library. In this research, metrics are response time, memory usage, and network usage as a comparison between libraries. Testing consists of a comparison between text data and text data along with images. The results of this study showed that the fastest response time in OkHttp library with an average of 148,675 ms. The smallest usage memory in the HttpURLConnection library with an average of 13906.1 KB. While the smallest network usage on Asynchronous Http Client library with an average of 67196.5 B. The test results in this study also showed an increase in response time of each library when the accessed data is text and image data. And there is an increase in memory usage and network usage memory when the accessed data is text and image data.
Clustering Data Kejadian Tsunami Yang Disebabkan Oleh Gempa Bumi Dengan Menggunakan Algoritma K-Medoids Daniel Alex Saroha Simamora; Muhammad Tanzil Furqon; Bayu Priyambadha
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 8 (2017): Agustus 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (983.063 KB)

Abstract

Tsunami is a natural events caused by sudden alteration in sea surface vertically, causing displacement of a large volume of water. Underwater volcano eruption, earthquake that is centered under the sea, and submarine landslide are some of the causes of sudden sea level change. Tsunami have occurred many times and causing many damages and fatalities. Tsunami often occurred so suddenly and cannot be predicted is the main reason for so many damages and fatalities, and the lack of knowledge and awareness are also worsen the effect of tsunami. K-Medoids is one of many clustering method which is applied to the dataset which have outlier. Subject in this research is a clustering application using K-Medoids to cluster the tsunami event which caused by earthquake dataset. Dataset used in this research come from the tsunami events database from the official site of National Oceanic and Atmospheric Administration (NOAA). The outcome from this research is a system that able to do clustering process on the tsunami events dataset using K-Medoids method. From the test, it is showed that the best number of clusters for tsunami events dataset is 2 clusters.

Page 48 of 685 | Total Record : 6850

 46   47   48   49   50 

Filter by Year

2017 2026


Reset
Filter By Issues
All Issue Vol 10 No 13 (2026): Publikasi Khusus Tahun 2026 Vol 10 No 01 (2026): Januari 2026 Vol 10 No 2 (2026): Februari 2026 Vol 9 No 13 (2025): Publikasi Khusus Tahun 2025 Vol 9 No 12 (2025): Desember 2025 Vol 9 No 11 (2025): November 2025 Vol 9 No 10 (2025): Oktober 2025 Vol 9 No 9 (2025): September 2025 Vol 9 No 8 (2025): Agustus 2025 Vol 9 No 7 (2025): Juli 2025 Vol 9 No 6 (2025): Juni 2025 Vol 9 No 5 (2025): Mei 2025 Vol 9 No 4 (2025): April 2025 Vol 9 No 3 (2025): Maret 2025 Vol 9 No 2 (2025): Februari 2025 Vol 9 No 1 (2025): Januari 2025 Vol 8 No 13 (2024): Publikasi Khusus Tahun 2024 Vol 8 No 10 (2024): Oktober 2024 Vol 8 No 9 (2024): September 2024 Vol 8 No 8 (2024): Agustus 2024 Vol 8 No 7 (2024): Juli 2024 Vol 8 No 6 (2024): Juni 2024 Vol 8 No 5 (2024): Mei 2024 Vol 8 No 4 (2024): April 2024 Vol 8 No 3 (2024): Maret 2024 Vol 8 No 2 (2024): Februari 2024 Vol 8 No 1 (2024): Januari 2024 Vol 7 No 13 (2023): Publikasi Khusus Tahun 2023 Vol 7 No 9 (2023): September 2023 Vol 7 No 8 (2023): Agustus 2023 Vol 7 No 7 (2023): Juli 2023 Vol 7 No 6 (2023): Juni 2023 Vol 7 No 5 (2023): Mei 2023 Vol 7 No 4 (2023): April 2023 Vol 7 No 3 (2023): Maret 2023 Vol 7 No 2 (2023): Februari 2023 Vol 7 No 1 (2023): Januari 2023 Vol 7 No 14 (2023): Antrian Publikasi Vol 6 No 13 (2022): Publikasi Khusus Tahun 2022 Vol 6 No 12 (2022): Desember 2022 Vol 6 No 11 (2022): November 2022 Vol 6 No 10 (2022): Oktober 2022 Vol 6 No 9 (2022): September 2022 Vol 6 No 8 (2022): Agustus 2022 Vol 6 No 7 (2022): Juli 2022 Vol 6 No 6 (2022): Juni 2022 Vol 6 No 5 (2022): Mei 2022 Vol 6 No 4 (2022): April 2022 Vol 6 No 3 (2022): Mei 2022 Vol 6 No 2 (2022): Februari 2022 Vol 6 No 1 (2022): Januari 2022 Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021 Vol 5 No 12 (2021): Desember 2021 Vol 5 No 11 (2021): November 2021 Vol 5 No 10 (2021): Oktober 2021 Vol 5 No 9 (2021): September 2021 Vol 5 No 8 (2021): Agustus 2021 Vol 5 No 7 (2021): Juli 2021 Vol 5 No 6 (2021): Juni 2021 Vol 5 No 5 (2021): Mei 2021 Vol 5 No 4 (2021): April 2021 Vol 5 No 3 (2021): Maret 2021 Vol 5 No 2 (2021): Februari 2021 Vol 5 No 1 (2021): Januari 2021 Vol 5 No 13 (2021) Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020 Vol 4 No 12 (2020): Desember 2020 Vol 4 No 11 (2020): November 2020 Vol 4 No 10 (2020): Oktober 2020 Vol 4 No 9 (2020): September 2020 Vol 4 No 8 (2020): Agustus 2020 Vol 4 No 7 (2020): Juli 2020 Vol 4 No 6 (2020): Juni 2020 Vol 4 No 5 (2020): Mei 2020 Vol 4 No 4 (2020): April 2020 Vol 4 No 3 (2020): Maret 2020 Vol 4 No 2 (2020): Februari 2020 Vol 4 No 1 (2020): Januari 2020 Vol 3 No 12 (2019): Desember 2019 Vol 3 No 11 (2019): November 2019 Vol 3 No 10 (2019): Oktober 2019 Vol 3 No 9 (2019): September 2019 Vol 3 No 8 (2019): Agustus 2019 Vol 3 No 7 (2019): Juli 2019 Vol 3 No 6 (2019): Juni 2019 Vol 3 No 5 (2019): Mei 2019 Vol 3 No 4 (2019): April 2019 Vol 3 No 3 (2019): Maret 2019 Vol 3 No 2 (2019): Februari 2019 Vol 3 No 1 (2019): Januari 2019 Vol 2 No 12 (2018): Desember 2018 Vol 2 No 11 (2018): November 2018 Vol 2 No 10 (2018): Oktober 2018 Vol 2 No 9 (2018): September 2018 Vol 2 No 8 (2018): Agustus 2018 Vol 2 No 7 (2018): Juli 2018 Vol 2 No 6 (2018): Juni 2018 Vol 2 No 5 (2018): Mei 2018 Vol 2 No 4 (2018): April 2018 Vol 2 No 3 (2018): Maret 2018 Vol 2 No 2 (2018): Februari 2018 Vol 2 No 1 (2018): Januari 2018 Vol 2 No 8 (2018) Vol 2 No 6 (2018) Vol 1 No 12 (2017): Desember 2017 Vol 1 No 11 (2017): November 2017 Vol 1 No 10 (2017): Oktober 2017 Vol 1 No 9 (2017): September 2017 Vol 1 No 8 (2017): Agustus 2017 Vol 1 No 7 (2017): Juli 2017 Vol 1 No 6 (2017): Juni 2017 Vol 1 No 5 (2017): Mei 2017 Vol 1 No 4 (2017): April 2017 Vol 1 No 3 (2017): Maret 2017 Vol 1 No 2 (2017): Februari 2017 Vol 1 No 1 (2017): Januari 2017 More Issue