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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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Pembangunan Sistem Reservasi Kamar Hotel berbasis Web dengan memanfaatkan Teknologi Payment Gateway (Studi Kasus: Hotel Asri) Muhammad Syahputra; Bayu Rahayudi; Welly Purnomo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 1 (2023): Januari 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Asri Hotel is located in Banyuwangi regency, East Java. The process of renting a room or reservation at this hotel is still written in the ledger. Customers must come in person or call-in advance to make a reservation, so there are often mistakes that harm customers and Asri Hotel. Currently, Hotel Asri also experiences problems in booking rooms due to a shortage of employees, so employees who have duties on the front end or reception are not always there. So, the step that can be taken to facilitate room reservations at Hotel Asri is to build a hotel room reservation system. The system to be built is web-based that is integrated with Midtrans's payment gateway so that guests can make room reservations and hotels in confirming room reservations. The research methodology used is the waterfall, starting from the analysis of needs in obtaining functional needs and non-functional needs of the system. Designing applications using Unified Modelling Language (UML). Functional testing of the system is performed by BlackBox testing the acquisition of 100% valid values. Non-functional testing was carried out using compatibility testing and the results of the system running in various browsers without any problems. System Usability Scale (SUS) testing was carried out on seven respondents and an average final score of 86% was obtained which based on the SUS score, the system built was accepted with the Acceptability Ranges assessment the system got an "ACCEPTABLE" score, in the Grade Scale assessment the system got a B grade and the system Adjective Ratings score got an "EXCELLENT" score.
Evaluasi Tata Kelola dan Manajemen Risiko Teknologi Informasi pada PT. MyECO Teknologi Nusantara menggunakan Framework COBIT 2019 Proses EDM03 dan APO12 Ayunda Della Ariesta; Suprapto Suprapto; Andi Reza Perdanakusuma
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PT. MyECO Teknologi Nusantara is a startup company that focuses on electricity-saving smarthome technology solutions. It has a product, namely an IoT-based automatic electricity-saving device. In supporting the quality of the company's products, MyECO has a smarthome application, namely the "myECO" application which functions to control electrical devices in the house from anywhere and at any time. The "myECO" application is expected to support the company's business processes. However, IT implementation is not always in accordance with the expected conditions because it can create risks. Regarding IT risk management, PT. MyECO Teknologi Nusantara has not implemented a specific mechanism to deal with IT risks that will arise when these risks have not been managed properly, it is necessary to conduct an assessment of IT risk management at PT. MyECO Teknologi Nusantara uses the COBIT 2019 framework. The framework used focuses on the EDM03 and APO12 processes. The research aims to assess the level of capability, gaps, and provide recommendations for the company. Data collection was obtained through interviews, questionnaire assessment sheets and observation. Respondents in this study were CEOs and CTOs who were determined using the RACI Chart. The results of the assessment show the capability level achieved by PT. MyECO Teknologi Nusantara is level 1 for EDM03 and APO12 processes. The recommendations focus on preparing documents that contain risk profiles, risk appetite, risk tolerance, corrective steps, risk grouping and the implementation of regular IT risk management evaluation activities in the company.
Analisis Sentimen Wisata Alun-Alun Kota Batu menggunakan Algoritma Support Vector Machine Ghani Fikri Baihaqi; Dian Eka Ratnawati; Buce Trias Hanggara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Batu town square is one of the tourist destinations in Batu city which is located in the center of Batu city and is an icon of the city. Batu City is also the number one tourist destination center in East Java with more than three million tourists every year. Batu City Square is a cheap tourist attraction which is the main destination for tourists visiting Batu City before heading to other tourist objects in this city. The tourism manager of Batu City Square, namely the Tourism Goverment, needs to know the perspective of visitors as evaluation material in building better infrastructure and services. Acquisition of visitor review data for the Batu City Square tour was obtained from the Tripadvisor website with data collection techniques using web scraping. Reviews from Tripadvisor will be categorized into two classes, positive and negative. Before classifying, text preprocessing is carried out to process the data into more structured data for research needs and to weight words using the Term Frequency - Inverse Document method. Classification is done using the Support Vector Machine algorithm. Classification uses data of 240 positive and negative data for classification in each Kernel. The best results in testing using the Support Vector Machine algorithm are testing on the rbf Kernel and a C value of 50. The Cross Validation used in this test is as many as 8 folds and produces an average value on the parameters and the number of folds, namely accuracy of 89.58%, precision of 90.73%, recall of 89.48%, f-measure of 89.45%, and specificity of 91.27%.
Klasifikasi Kesiapan Panen Tanaman Hidroponik Bayam Hijau menggunakan Metode Pengolahan Citra dan K-Nearest Neighbours berbasis Raspberry Pi Bilawal Haesri; Hurriyatul Fitriyah; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Green spinach is one of the vegetables that is favored by the Indonesian people for consumption, this can be seen from the increasing production of green spinach from 2020 to 2021 with an increase of 9%. Generally, the cultivation of green spinach is done conventionally using soil as the plant medium, but this cultivation technique requires a large area of land. One alternative way to cultivate green spinach is through hydroponic techniques that utilize nutrient-rich water as the plant growth medium. The readiness of hydroponic plants for harvest can be determined by their age, but it must first be seen from the shape and size of the hydroponic plants to be harvested. The problem found in hydroponic farming is that hydroponic farmers need to do regular monitoring to determine whether the hydroponic plants are ready to harvest or not on each plant that takes a long time, which reduces the effectiveness of plant production, because it will inhibit the hydroponic production cycle. In this study, we will build a system that can classify the readiness for harvest of hydroponic green spinach using digital image processing and K-Nearest Neighbors classification. The system uses a webcam to take images, Raspberry Pi as an image processing and classification device, and a 20x4 LCD to display the harvest readiness classification results. The system was tested using 12 images of green spinach with a classification accuracy using K-NN of 100% at K=3 and an overall computation time of the system with an average value of 1.4 seconds.
Implementasi Algoritme SPONGENT sebagai Algoritme Hashing untuk Integritas pada Modul Komunikasi LoRa I Putu Agrahita Wiguna; Ari Kusyanti; Fariz Andri Bakhtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 13 (2023): Publikasi Khusus Tahun 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Dipublikasikan di JTIIK (Jurnal Teknologi Informasi dan Ilmu Komputer)
Sistem Klasifikasi Kualitas Air untuk Budidaya Ikan Nila Hitam (Oreochromis Niloticus) menggunakan Metode Support Vector Machine Dwiki Ilham Bagaskara; Dahnial Syauqy; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Black Tilapia or which has the scientific name Oreochromis Niloticus is a type of freshwater fish that is widely consumed throughout the world, especially in Indonesia. Tilapia production continues to increase along with the increasing demands to meet food needs both domestically and abroad. One of the efforts made to achieve this target is cultivating tilapia seeds to improve the quality and production of tilapia. In cultivating tilapia in order to obtain quality fish yields, one of the most important factors influencing this is the quality of the water in the pond where the tilapia is cultivated. In Indonesia there are still many tilapia cultivators who measure and control pond water quality manually or even don't do this at all. For this reason, a water quality classification system will be designed for black tilapia cultivation using the support vector machine method which can carry out classifications to determine water quality in ponds automatically. The system is implemented using 3 sensors, namely the temperature sensor DS18B20, the pH sensor PH-4502c, and the turbidity sensor SEN0189. In the test, 3 features were used in the system to make training and testing data, namely temperature features, pH features, and turbidity features to determine the class of pond water being tested. 60 total training data consisting of 30 pieces of data for the "good" class and 30 pieces of data for the "bad" class were used to conduct training data for the classification system. The support vector machine classification method that is programmed in the system will carry out the classification process by reading the values ​​from the sensors and storing them as features to be processed and compared with the results of the training data. The system will look for the y value as the reference value for class classification results where if the y value ≤ 1 then the water will be declared "good" and if y> 1 then the water is said to be "bad". The test results are obtained by reading the output results on the system LCD for 15 seconds. From the test results, 15 reading were obtained where 12 of the test results were correct readings and 3 were incorrect readings. From the test results it can be concluded that this system can work according to its function and purpose.
Sistem Identifikasi Label Ruangan menggunakan MobileNet SSD dan OCR berbasis Raspberry Pi 3B+ dan Intel Neural Compute Stick 2 Zhuliand Rachman; Fitri Utaminingrum; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

A blind person generally has limitations in visual sensing and uses aids such as a cane to assist their mobility but still has obstacles, especially when they are in a building and want to find the room they are aiming for. Room labels that are usually printed and cannot be recognized by a blind person can be identified with the help of a portable device that performs computing in the field of computer vision. By relying on the MobileNet SSD algorithm, which can detect the presence of room labels with a fast computation, and Optical Character Recognition (OCR) which can recognize the name of the room label, users can hear the name of the room spoken through the speakers. In short, the system converts visual information into audio information that a blind person can receive. Even though the primary processor is an edge device such as the Raspberry Pi 3B+, an additional Intel Neural Compute Stick 2 accelerator device can help the detection process go faster because the detection algorithm involves a computationally intensive deep neural network. Based on the tests carried out in this study, the room label detection test using MobileNet SSD resulted in an accuracy rate of 80% with an average computation time of 68.44 ms. While for recognition using OCR, it produced an accuracy value of 93.65% with an average computation time of 263.05 ms. In addition, the integration results based on digital image input with sound output obtained an accuracy rate of 50% because the sound is only pronounced if the recognition results match the name of the existing room label.
Perancangan User Experience Aplikasi Web Pelaporan Tempat Pembuangan Sampah Reduce, Reuse, Recycle Dinas Lingkungan Hidup Kota Batu menggunakan Metode Human Centered Design Hendrikus Dimas Samara; Hanifah Muslimah Az-Zahra; Komang Candra Brata
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The reduce,reuce,recycle (TPS3R) landfill is an important element in terms of waste management in Batu City which is managed by the Batu City Environment Service (DLH). it aims to help with TPS3R reporting problems by designing a TPS3R waste reporting system so that it can ease the workload of DLH staff in Batu City. System design is carried out using the Human Centered Design method which prioritizes user needs in designing the system. from this research in the form of wireframes, mockups, and prototypes that describe the original function of the system. efficiency, as well as user satisfaction in trying the system prototype. The prototype that has been made is tested to measure whether the system design made is acceptable to users. Testing was carried out using usability testing to 5 respondents, the aspects tested were effectiveness, efficiency, and user satisfaction in trying the system prototype. The results obtained in the test are an effectiveness value of 91.42%, an efficiency value of 0.1271 goals/second, and a user satisfaction value of 80 points which gets a B value and is categorized as Good.
Pengelompokan Film Berdasarkan Alur Cerita menggunakan Metode Self Organizing Maps dan Silhouette Coefficient Wilis Biro Syamhuri; Muhammad Tanzil Furqon; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Movie is one of the most popular entertainment media around the world by presenting interesting audio and visuals. Now movies can be easily accessed via streaming service provider sites or applications, even with mobile devices. The site or application that provides movie streaming service has one simple but very useful feature namely movie grouping, which are generally based on genre, year, rating, country of origin, and others. Each movie has its own unique plot or storyline, but there are several movies that have similar plots in some parts. Regardless of the same genre, sometimes there are movies that have different plots. Vice versa, there are movies with different genres but have similarities in plots. On the basis of these problems, this research grouped movies based on similarities in plots. Grouping is done using the Self Organizing Maps clustering method. After that, the results of the clustered movies were evaluated using the Silhouette Coefficient method. A total of 800 movies were successfully grouped into 25 clusters with the highest evaluation result of 0.175. One out of twenty-five clusters has the highest local evaluation score of 0.714. The results of this evaluation indicate that grouping movies based on plots is still not fully effective because only one out of twenty-five clusters produces an evaluation value in the "strong structure" category.
Pengembangan Sistem Manajemen Sampah TPS3R Dinas Lingkungan Hidup Kota Batu berbasis Web Responsive menggunakan Tailwind dan ReactJS Ignatius Daniel Y.T.A. Ginting; Herman Tolle; Komang Candra Brata
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The Reduce, Reuse, Recycle Waste Management Site (TPS3R) is a system that functions to manage waste from households and industries to reduce environmental pollution. In TPS3R waste management, it is necessary to collect data on the amount of incoming and processed waste in order to determine the efficiency of waste management at TPS3R sites. In this case, the Batu City Environmental Service obtained the data through calculations carried out by TPS officers who were on the TPS3R site around Batu City villages and sub-districts. However, the process of recording waste data is still done manually so that the analysis of the efficiency of waste management in TPS3R is still not optimal. To overcome this problem, a web-based waste management application was developed with adding and viewing waste data features to facilitate data processing carried out by the Environmental Service at TPS3R in Batu City. This study uses the waterfall method to develop the TPS3R waste management system. Based on the tests that have been carried out, namely validation testing which produces a value of 100% for each test case and Compability testing is carried out using the sortsite test tool which results in the system running well on the 7 browser versions that have been tested. Meanwhile, the usability test conducted on 5 respondents using the System Usability Scale (SUS) yielded a value of 78, thus proving that the usability of the system can be said to be good.

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