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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 50 Documents
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Search results for , issue "Vol 2 No 1 (2018): Januari 2018" : 50 Documents clear
Evaluasi Kualitas Layanan Website E-Commerce Salestock Indonesia Dengan Menggunakan Metode Webqual 4.0 dan Importance Performance Analysis Rizky Nanda Istichomah; Suprapto Suprapto; Admaja Dwi Herlambang
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The quality of the web service Salestockindonesia.com needs to be evaluated because it has a ranking of 1591 according to alexa.com, ranked 422 according to similiarweb.com and ranked 72 according to statshow.com which can be stated far below similar websites. Evaluation is done by using Webqual variable that is usability, information quality, and service interaction quality. Usability there are six indicators, information quality there are four indicators, and service interaction quality there are three indicators. Data quality of service obtained from questionnaire which then the result is analyzed by using method of Importance Performance Analysis (IPA). Data obtained from the number of samples of 100 respondents by using questionnaires. From the evaluation results can be stated that the quality of service on the variable usability of two indicators of good quality that is on the indicators of ease of us and navigation and learnability. Four indicators of poor quality that is on the indicator of appearance, the imaged conveyed to the user, errors, and satisfaction. In variable information quality two indicators of good quality that is on indicator of relevance and accessibility. Two quality variables are less good that is on indicators of representational and accuracy. In service interaction quality variable two good quality indicator that is at indicator of trust and responsiveness and one indicator of quality is not good that is at empathy indicator. From the results of these tests the authors provide recommendation improvement for the poor quality that is referenced from the relevant journal or scientific articles.
Analisis Faktor-Faktor yang Memengaruhi Penggunaan KMSPico Untuk Aktivasi Produk Microsoft Pada Mahasiswa Universitas XYZ Muhammad Faizal Ismail; Ari Kusyanti; Admaja Dwi Herlambang
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The use of computer in modern days is almost a necessity for everyone. Based on data from BSA Global Survey in 2015, use of pirated software in Indonesia reaches 84 percent. KMSPico is an application that can be used as an activator for Microsoft products like Microsoft Windows and Microsoft Office for free. However university of XYZ has a cooperation program with Microsoft by name of DreamSpark. DreamSpark is a program from Microsoft that supports technical education by providing access to various Microsoft products for free. In this study, the researchers conducted a non parametric analyzed with Kendall Tau to determine the factors of what makes students of university of XYZ use KMSPico. By combining several models of User Acceptance of Information Technology (UTAUT), Protection Motivation Theory (PMT), and Security Belief Model. Sample collection of data by using a questionnaire and analyzed by Kendall Tau. The number of samples used in this study is 206 datas. Results of this study showed that University of XYZ students using KMSPico because KMSPico is effortless, performance, social influence, facilitating condition, perceived vulnerability, perceived severity of using KMSPico, self-efficacy, response efficacy, interest with KMSPico's information, and perceived benefits
Analisis Sentimen Dengan Query Expansion Pada Review Aplikasi M-Banking Menggunakan Metode Fuzzy K-Nearest Neighbor (Fuzzy k-NN) Nanda Cahyo Wirawan; Indriati Indriati; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In this digital era, bussiness grow significantly by using digital application. Banking is one field of business that utilizes the current technological advances very well. Mobile banking is one of the most popular digital banking products, because it is not as complicated as SMS banking or internet banking. In order to face the strict banking business, every company applying feedback from their customers. Now customers can use the review feature that provided by apps store. There's a lot of reviews that received every day, and it takes some time to knowing what kind of review is that. Systems with machine learning are expected to save time to sort out textual data that containing polarity. The system's machine learning in this study was made using fuzzy k-nearest neighbor (fuzzy k-NN) method. The fuzzy k-NN method is a combined method between fuzzy logic and the k-Nearest Neighbor algorithm. The weighting method for processing textual data into numerical data that can be computed is using TF-IDF method with Cosine similarity to calculate the distance between data. The output of this system is the classified data review. Based on the results of the tests, this system produces the best F-Measure is 0.9273 and the worst is 0.8349.
Prediksi Suku Bunga Acuan (BI Rate) Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS) Nur Adli Ari Darmawand; Dian Eka Ratnawati; Rizal Setya Perdana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

BI Rate is the interest rate policy that reflects the monetary stance policy which set by Bank of Indonesia and announced to the public. BI Rate is used as the parameter of economic activity of a country. BI Rate will affect the turnover of bank financial flows, inflation, and currency movement. The ups and downs of BI Rate are highly important for investors and market participants to increase or decrease the amount of production and to increase or decrease existing investment. That's what makes the BI Rate prediction important. The predicted BI Rate is expected to help investors and market participants to determine long-term economic decisions. In this study used Adaptive Neuro Fuzzy Inference System method which is a combination of steepest descent and least square estimator (LSE) algorithm for training. Based on the test results, it produces the best RMSE value 0.0019165.The final result obtained is the predicted value of bi rate.
Sistem Rekomendasi Psikotes untuk Penjurusan Siswa SMA menggunakan Metode Modified K-Nearest Neighbor Muchlas Mughniy; Randy Cahya Wihandika; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Major selection for high school student intended to facilitate students to focusing on specific field for higher education. However, assigning academic potential for each student through school counselor needs plenty of time. A recommendation system can generate a recommendation for major selection based on cognitive ability by Intelligenz Struktur Test (IST). Modified k-Nearest Neighbor is applied to system which classifying academic potential based on neighborhood by training data. Training data consist of nine cognitive intelligences and two majors. So, system will provide a recommendation for major. From the testing process that has been done, has obtain highest averaged accuracy on 90% dataset is 67,95%, averaged accuracy on 4-fold Cross Validation is 63,58%, averaged Sensitivity and Specificity is 23,64% and 92,34%, accuracy comparison between MKNN and KNN is 63,58% and 57,11%, and then highest accuracy for feature reduction using PCA is 55,26% which is reduced to 6 features. According to test result indicate that Modified k-Nearest Neighbor recommendation system not optimal yet to generate a recommendation for major selection.
Penerapan Bayesian Network Pada Sistem Pakar Ekspresi Wajah dan Bahasa Tubuh Melalui Pengamatan Indra Penglihatan Pada Foto Muhammad Adiputra; Rekyan Regasari Mardi Putri; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Facial expression and body language is a non-verbal language that can describe the real emotion in a person. Movement on facial expressions and body language shown by humans not only contains. Other than that, for some cases it needs a combination of facial expressions with body language to know the hidden meaning in it. The expert system of facial expression and body language is the application of probabilistic theory and graph theory on the bayesian network method. The purpose of making this expert system is to identify the meaning of emotion that a person shows through facial expression and body language. There are 7 expressions of feelings and emotions that becomes the system output, that are: lie, honest, angry, sad, fear, happy, and suprised. Based on testing of variation data training, it was found that the amount of data training and variation of it also affected the accuracy of the system result. In addition, it is also known that more data training used and more varied, it will increase the level of accuracy. While based on the results of the test using the f-measure method conducted on 5 cases containing 28 images, where each picture shows facial expression and body language of 5 different people, obtained the average of 80.47% precision, 86.34% recall, and an accuracy level for f-measure is 80.31%.
Implementasi Kura Framework pada Purwarupa Rumah Cerdas Muhammad Iqbal; Sabriansyah Rizqika Akbar; Bayu Priyambadha
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the challenges when implementing a smart home system is the interoperability with the diversity of devices and technologies that are potentially used in an intelligent home system (Lakomiak, 2017). These challenges can be overcome by applying IoT gateways to a smart home system. IoT gateway is responsible for bridging between endpoint devices such as sensors and actuators with brokers so that these devices can send information to the broker and can be controlled by the client remotely. From that problem, Eclipse developed an IoT framework called Kura. The purpose of this study is to implement Kura on the prototype of a smart home systems and test the performance provided. To know the performance of the prototype of a smart home system built is done testing the validity of the system and calculation of the response time system. From the results of the tests conducted, it was found that in the automation cycle of publishing data from the client device to the smart device until the data returned displayed on the client device within 1 second, the system successfully perform the task and display the return to the client in accordance with the data published by the client. With the average response time in one cycle is 990.8 ms which is still less than 1 second, the performance of the intelligent home system prototype using the Kura framework can be categorized well and still accepted by the client (Neil, 2009).
Penentuan Kelayakan Lokasi Usaha Franchise Menggunakan Metode AHP dan VIKOR Vienticentia Imanuwelita; Rekyan Regasari Mardi Putri; Faizatul Amalia
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Franchise is a type of businesses that offers various benefits such as the good reputation and the stability of operating procedures. Nevertheless, the franchise business could be closed to bankruptcy, one aspect which influences that fact is the location factor. Site selection that does not meet certain criteria has a direct impact on the failure of the franchise business. The determination of the business location feasibility for the object under study has a computational pattern that is not clear, not directional and not concrete. Therefore, it is important to establish the appropriate business location feasibility supported by proper calculation patterns. This research proposes AHP and VIKOR methods to build system that can answer Multi Criteria Decision Making (MCDM) problem for feasibility of franchise business location. The AHP method is used to derive the weighting value of all criterias, while VIKOR focuses on the ranking of alternative business locations and proposes compromise solution. Based on the testing performance, the highest accuracy obtained is 85% with threshold value of 0,56. The sensitivity of VIKOR value while value is changed derived four alternatives that are sensitive to that change. The final result obtained is the eligibility status of each proposed business location.
Pengembangan Sistem Informasi KIM (Kelompok Informasi Masyarakat) KOMINFO Jatim Berbasis Web Mohammad Mirza Zanuar; Mochamad Chandra Saputra; Fajar Pradana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of programs that being held by KOMINFO JATIM is ‘Kelompok Informasi Masyarakat' that have a purpose to increase the public participation to contribute for sharing an information on their region. Based on observation and interview , KIM program has not been able to run well becasuse of some problems. The absence of control mechanism in the KIM program, such as controlling the incoming article and controlling the registered kim members. The previous alternative controls are done manually which creates new problems that are poor data management. Base on these problem, KIM information system are being developed to serve as a medium for the implementation of the KIM program. Development method used is waterfall method. The Naive Bayes method is used to classify unexpected articles (spam). Then used the feature of laravel that is middleware to manage role available in KIM information system. In testing, basic path tests, validation testing, compatibility tests, and user acceptance tests were performed. For classificatoin feature, test is done by using coincidence matrix table to get the value from precision,recall, and accuracy.
Deteksi Jumlah Penghuni Pada Ruangan Berpintu Untuk Smart Home Berbasis Arduino dan Sensor PIR Lintang Cahyaning Ratri; Hurriyatul Fitriyah; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Counting people coming in and out of the desired region automatically is very important in business, management and security. This research introduces Detection system of people in the room that has doors for smart home based arduino and PIR sensors. The benefits of the system are for management and security. In this research, the purpose is focused on counting the number of people in the room that has the doors automatically, so, the owner can see the number of people in each room in his house periodically. The use of PIR sensors aims for detects human presence without disturbing the privacy of the householders. So the sensor is very suitable for home / office automation. This system uses arduino nano type and NRF24L01 type microcontroller as a wireless device. The result shows that the system has 100% accuracy in calculating people automatically by 6 times entering-exiting of the room testing. This system can overcome if the object that goes into the room is a non-human object (cat). This system can count 2 people as 2 people that can be detected from the distance between people about 3,5 meters. In data transmission test, system can send data at a distance of about 35 meters in open space (without wall barrier) and about 4 meters in room with wall barrier

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