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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.
Arjuna Subject : -
Articles 6,923 Documents
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Pengembangan Sistem Informasi Autopsi Verbal (Studi Kasus : Dinas Kesehatan Kabupaten Malang) Muhammad Ridho; Ismiarta Aknuranda; Lutfi Fanani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Malang District's health service offices own a pilot project whose objective is to record in the form of causes of death in the region Gondanglegi and Kepanjen. One of the ways to record such data is through verbal autopsy which is done by interviewing family members of the deceased on visible signs or symptoms of a certain individual before death. The ongoing process of the verbal autopsy is still recorded manually using paper, which when gathered is vulnerable to being lost or damaged. Otherwise, there was no system to record the data that has been gathered. Based on the above-mentioned problem, an information system is needed to ease the recording, storing, and processing of data that contains verbal autopsy. The development of the information system uses a prototyping method which presents a picture of the system in general toward the client in order to gain feedback in the form of advice or critique. Development is started with the modeling of the business process and requirements of the analysis, prototype designing, prototype evaluation, continued designing, which is finished with implementation and testing. The implementation results in a web-based verbal autopsy information system. The system is utilized to record, verify, manage, and manage verbal autopsy data and to present general information. The next step is to test the implementation results with validation testing which shows valid test results which are in accord with the identified requirements, tests towards the compatibility of the browser show that the error issues were at 9% and the system was run on a variety of browsers without any problems whatsoever.
Klasifikasi Penerimaan Program Keluarga Harapan (PKH) Menggunakan Metode Learning Vector Quantization (Studi Kasus Desa Kedungjati) Vidya Capristyan Pamungkas; Lailil Muflikhah; Rendi Cahya Wihandika
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

Poverty is a condition of someone inability to fulfill basic needs for a decent life. The poverty rate is increases, especially in Jombang Regency from year to year until 2017 reaching 131.16 people, various ways have been carried out by the government to reduce poverty, one of which is Program Keluarga Harapan or PKH, Kedungjati Village officer doing survey head of family with manual method by visiting each head of family and recording one by one the criteria. Classification system of Program Keluarga Harapan using Learning vector quantization (LVQ). LVQ is a classification method that has a pattern where the output of each unit is a representation of a class or category. The weight vector of each unit's output is a vector representation to a class. Weight vector have rules during training. As a classification method, LVQ does a lot of training repeatedly process until get maximum results, so LVQ can minimize errors that occur in the process. LVQ method do training and testing process to obtain the classification results. In this case using 5 test parameters with the best results, that is learning rate 0.7, DecAlpha 0.3, Epoch 2, and MinAlpha 0.01, using 2 weight vector to represent class 0 and class 1, get the results of an accuracy of 100%.
Sistem Pendukung Keputusan Pemilihan Produk Promo Dengan Menggunakan Metode Analytical Hierarchy Process - Simple Additive Weighting (AHP - SAW) (Studi Kasus : Geprek Kak Rose) Royan Krisnanda Tiony; Niken Hendrakusma Wardani; Tri Afirianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Decision making on a product must be taken appropriately and in line with company's objectives so that a business will have a long product life cycle and win the market competition. One form of decision making undertaken by a company is through the process of Decision Support System (DSS). The DSS implementation in the culinary business Geprek Kak Rose will help the company in decision making process related to products promotion recommendation to be more accurate and faster to make the company reach target and stay competitive. In determining the product promotion, the company uses a number of criteria that are used as references such as Price, Sales, Durability, and Inventory. These criteria will be the main guideline in DSS using the AHP (Analytical Hierarchy Process) - SAW (Simple Additive Weighting) method. AHP method is used for the criteria weighting process, then proceed with the SAW method for the best performance ranking process based on all available alternatives. To see the suitability of DSS made with a manual decision from the user, this study uses a Spearman correlation test that produces a value of 0.737 which means it has a very strong relationship.
Penerapan Term Frequency - Modified Inverse Document Frequency pada Analisis Sentimen Ulasan Barang menggunakan Metode Learning Vector Quantization Moch. Yugas Ardiansyah; Mochammad Ali Fauzi; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In online stores there are reviews of items that contain comments about feedback from previous buyers that are useful for subsequent buyers as well as sellers at online stores. Reviews Usually consist of negative comments or positive comments. The number of reviews is very much. In overcoming this problem, sentiment analysis is needed. This study uses the Learning Quantization Vector and Term Frequency-Modified Inverse Document Frequency methods. The LVQ method was chosen because it has the advantage of being able to summarize the dataset into a codebook vector. The data used consisted of 250 positive comments and 250 negative comments. The data will be preprocessing, weighting the word using TF-mIDF and consequently using the LVQ method. The results of testing the LVQ parameters obtained an accuracy value of 75.11%, recall of 75.11% precision of 77,80%, f-measure of 76.43% with parameter values ​​of learning rate 10-3, dec α 10-6, and values maximum epoch 19. Based on the final test results, obtained the value of the Learning Vector Quantization method with TF-mIDF resulted in an average accuracy of 72.47%, recall of 72.47%, precision of 76.39%, and f-measure of 74.33 % and using the Learning Vector Quantization method with TF-IDF resulted in an average accuracy of 54.80%, recall of 54.80%, precision of 54.30%, and f-measure of 52.61%.
Analisis dan Perbaikan Proses Bisnis dengan menggunakan Metode Business Process Improvement (BPI) pada PT. Andynni Chitta Sejahtera Prakoso Adi Bagaskara; Nanang Yudi Setiawan; Andi Reza Perdanakusuma
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PT. Andynni Chitta Sejahtera is a company engaged in the field of marine maintenance, especially in sandblasting and painting activities. In carrying out the business process of PT. Andynni Chitta Sejahtera is still experiencing problems and problems in some of its business process activities which are still done manually, which results in activities being worked on for a long time and causing a very high risk of human error. But not all activities that are done manually are problematic, so it is necessary to do an analysis and evaluation of the ongoing business processes. Evaluation and analysis of problems in the Main Business Process was carried out by using Value Added Assessment (VAA) and Root Cause Analysis (RCA) with fishbone diagram techniques. From the results of analysis and evaluation found 2 No Value Added (NVA) activities that can be considered to be eliminated in the recommendation process and there are 9 problematic activities that need to be improved with tools streamlining from the Business Process Improvement (BPI) method. In the last stage, a simulation was carried out by using Bizagi Modeler to find out how much time was lost between business processes (as-is) and the recommended business process (to-be). On the Recommendation of Business Process Service Order Receipts decreased in time by 541.6 minutes, and resulted in a time efficiency of 15.72%. This shows that implementing a business process design recommendation can accelerate the Business Process of Accepting Service Orders.
Analisis Sentimen Pada Ulasan Aplikasi Mobile Banking Menggunakan Metode Support Vector Machine dan Lexicon Based Features Katherine Ivana Ruslim; Putra Pandu Adikara; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sentiment analysis is a very popular field of research in text mining. The basic idea of ​​sentiment analysis is finding the polarity of the document and classifying it into positive or negative. The text documents used in the research are reviews on the Google Play Store regarding the mobile banking application. Support Vector Machine is a method used and added Lexicon Based Features as additional feature besides using the Bag of Words. The research data is 500 data by dividing 90% training data and 10% test data. The system evaluation results obtained with a combination of Bag of Words and Lexicon Based Features are higher than the results of system evaluations that only use the Bag of Words and systems that only use Lexicon Based Features. The evaluation results obtained by the combination of the two features with testing using 10 fold cross validation are accuracy = 0,846, recall = 0,846, precision = 0,864, and f-measure = 0,855 with the Support Vector Machine parameter value used is the best parameter value of sigma kernel RBF = 3, lambda = 0,1, gamma = 0,001, complexity = 0,1, epsilon = 0,001, and iteration = 50.
Penerapan Multi Travelling Salesman Problem Pada Optimasi Pendistribusian Bantuan Sosial Beras Sejahtera Studi Kasus: Perum Bulog Subdivre Malang Muhammad Nadzir; Imam Cholissodin; Bayu Rahayudi
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

Distribution is an economic activity that bridges the production and consumption processes. The distribution process is distributing goods from producers to consumers. Bantuan Sosial Beras Sejahtera (Bansos Rastra) Program has a goal to improving the quality of service for the poor through fulfilling food needs. The distribution system of Bansos Rastra sending goods to each Distribution Point by Perum Bulog in accordance with the data distribution request. In the process of distributing goods, it is necessary to calculate the route distance in order to minimize travel time with the problems used in processing document data is Multi Traveling Salesman Problem (m-TSP) with Genetic Algorithm. From the evaluation results, the distribution routes for each warehouse are recommended by meeting the limits made. Based on the research carried out, the optimal parameters obtained were the size of the optimal number of generations of 300 generations, the optimal size of the population is 90 populations. The crossover probability value is 0.1 and the probability of mutation is 0.9 so that it gets the best average fitness value of 2.583. The final evaluation results produce the best chromosomes with a difference in the predicted distance that is more efficient than the actual distance so that the distribution process of Bansos Rastra can be more optimal.
Implementasi Intrusion Prevention System (IPS) berbasis Athena untuk Mencegah Serangan DDoS pada Arsitektur Software-Defined Network (SDN) Muhammad Farradhika Muntaha; Primantara Hari Trisnawan; Rakhmadhany Primananda
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Distributed Denial of Service (DDoS) are common and popular attacks on the SDN layer, namely the data plane. In this study, Athena-based Intrusion Prevention System (IPS) is applied to prevent and reduce the impact of DDoS attacks, especially TCP SYN flood and UDP flood. Two test scenarios were carried out to determine the IPS performance. The first scenario, comparing the impact of DDoS attacks without and with applied IPS to throughput and CPU usage on the controller. The second scenario, comparing the speed of the prevention function based on features in the detection model. The first test results show that IPS is able to prevent DDoS attacks as proven by the decrease in the throughput. The throughput when normal and IPS is applied against TCP SYN flood and UDP flood attacks for transmit parameters of 3956 pps, 4045 pps and 3919 pps while for receive parameters it is 4720 pps, 4793 pps and 4692 pps. IPS is also able to reduce the CPU load on the controller when those attacks are carried out each at 4.95% and 7.9%. The second test result concludes that the more appropriate and correct features are used for training, the faster IPS in recognizing the characteristics of dangerous hosts. This is proven by the average speed of prevention for each attack using 10 features each at 5.78 seconds and 5.99 seconds while the 5 features each at 12.42 seconds and 11.42 seconds. Moreover, IPS can be applied to hardware with specifications as in this study.
Evaluasi Usability Aplikasi Mobile Karir.com Menggunakan Metode Heuristic Evaluation Denis Mafira Ramdhan; Satrio Hadi Wijoyo; Niken Hendrakusma Wardani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Karir.com is the first career portal in Indonesia and a platform for recruitment of employee through online. Karir.com can be access through website and mobile application. However, in the Karir.com mobile application there is a usability problems when the users use the application. Examples, there is no confirmation when applying a job and there is no cancellation feature after applying a job. In order to have information on other problems which are more complex and specific, heuristic evaluation can be done as it involves usability expert as an evaluator. Heuristic evaluation used can be divided into 10 Nielsen's heuristics principle. The 10 Nielsen's heuristics principle are visibility of system status, match between systems and real world, user control and freedom, consistency and standards, error prevention, rather than recall recognition, flexibility and efficiency of use, aesthetic and minimal design, help users recognize, diagnose, and recover from errors and help and documentation. The evaluators involve in the evaluation process consist of 4 people evaluators. In the first analysis, the evaluators discovered 25 usability problems. From the total of 25 usability problems, it includes all 10 aspects from Nielsen's usabiliity problems. The highest frequency of the problem is at the consistency and standards (H-4) with the percentage of 22.5%. furthermore, the highest average of severity rating is at the help and documentation (H-10) of heuristic principle with the value of 3. After the implementation of recommendation improvement results, there is no problem found on the usability in the early evaluation, and only 1 new usability problem found in further evaluation with the severity rating value of 1. The improvements made are very effective with the decreasing of total problems found.
Sistem Pakar Deteksi Kenakalan Remaja di Sekolah Menggunakan Modified K-Nearest Neighbor (MKNN) Asrul Syawal; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Juvenile delinquency is one of the problems faced by parents in guiding children. Juvenile delinquency has often happened in the world of primary education in schools, this is a concern for parents, besides parents, teachers as mentors in schools actively participate in guiding students in schools to avoid juvenile delinquency and to behave positively and positively in the school environment and outside the school environment . To avoid delinquency in school prevention is done by detecting delinquency that might occur in children based on factors or behavioral symptoms that are often carried out by children. In this study a system was created to detect juvenile delinquency especially in schools to prevent delinquency that might occur using the Modified K-Nearest Neighbor (MKNN) method. MKNN method is a developmental method of the KNN method, which distinguishes the value of validity in training data to produce better values. The results of this test used as much as 60 training data, and the accuracy of the variation in training data obtained the lowest level of accuracy when the value of training data variation was 30% the accuracy was 76.78% and the highest level of accuracy when the training data variation value was 90% the accuracy was 100%. In this test the average system accuracy was obtained at a maximum of 86.7%.

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