JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Paper topics that can be included in JuTISI are as follows, but are not limited to: • Artificial Intelligence • Business Intelligence • Cloud & Grid Computing • Computer Networking & Security • Data Analytics • Datawarehouse & Datamining • Decision Support System • E-Systems (E-Gov, E-Health, E-Commerce, etc.) • Enterprise System (SCM, ERP, CRM) • Human-Computer Interaction • Image Processing • Information Retrieval • Information System • Information System Audit • Enterprise Architecture • Knowledge Management • Machine Learning • Mobile Computing & Application • Multimedia System • Open Source System & Technology • Semantic Web & Web 2.0
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<![CDATA[Perancangan dan Implementasi Sistem Informasi Kesehatan P - IRT berbasis Web dan Android ]]>
<![CDATA[Yan Rigid Wijaya]]>;
<![CDATA[Radius Tanone]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2457
<![CDATA[The Salatiga City Government through the Health Office organizes a system of services and socialization to the community in a preventive manner. The intended community includes P-IRT (Food and Home Industry) which constitutes the food and beverage industry sector which is included in the small industry. In carrying out the delivery of information, employees must carry out a program of training activities as well as by conducting socialization to the community directly, where it is more time consuming, costly, and energy. This also makes the service and delivery of information less efficient. Therefore a web-based and mobile-based information system design is needed to complement these shortcomings. By using the Laravel Framework and Android Programming as well as a collaborative filter algorithm, a web-based application and an Android phone are generated to address the problem. Sharing information and discussions between the public and related agencies is easier to use this system.]]>
<![CDATA[Kombinasi Damerau Levenshtein dan Jaro-Winkler Distance Untuk Koreksi Kata Bahasa Inggris ]]>
<![CDATA[Bonifacius Vicky Indriyono]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2493
<![CDATA[Writing is one of the efforts made by the writer to express ideas and ideas to others. But sometimes when writing, there are many errors in typing spelling, especially English spelling, resulting in errors in capturing the meaning and meaning of the writing. To overcome this problem, we need a system that can detect word spelling errors. Damerau Levenshtein and Jaro Winkler Distance Algorithms are algorithms that can be used as a solution to detect English typing errors. From the test results, it can be concluded that the Damerau Levenshtein and Jaro-Winkler Distance are able to optimally detect word mismatches and look for similarities of words compared. The Damerau Levenshtein Distance works by finding the smallest distance value, while the Jaro-Winkler Distance works by finding the greatest proximity value of the string being compared. Using this algorithm, errors in writing the spelling of words can be minimized. Keywords— Algorithm; Damerau Levenshtein; Jaro Winkler; Spelling Cheker; String Matching.]]>
<![CDATA[Perancangan Data Warehouse Perguruan Tinggi untuk Kinerja Penelitian dan Pengabdian kepada Masyarakat ]]>
<![CDATA[Agata Filiana]]>;
<![CDATA[Andhika Galuh Prabawati]]>;
<![CDATA[Maria Nila Anggia Rini]]>;
<![CDATA[Gloria Virginia]]>;
<![CDATA[Budi Susanto]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2557
<![CDATA[Accreditation is an evaluation to ensure the quality of a study program at higher education by completing two main documents for qualitative data and self-evaluation, namely Study Program Performance Report (LKPS) and Self Evaluation Report (LED) respectively. Data used for this process must be consistent and accurate, therefore a central repository is proposed. A data warehouse for the domain of Research and Community Service is built using the snowflake schema and a five-step approach methodology proposed for the educational data warehouse. The schema consisted of one fact table, ten dimension tables, and four bridge tables. Using a business intelligence tool, data from the data warehouse is queried and provided in a dashboard. The data warehouse successfully returned the qualitative data needed for LKPS. As for the evaluation data for LED, the data warehouse is able to fulfill seven out of ten requirements. The data for the remaining three are provided with a slightly different orientation to the requirement, this was due to the data source.]]>
<![CDATA[Faktor Kesuksesan Sistem E-Office Rumah Sakit dalam Upaya Meningkatkan Kepuasan Pengguna ]]>
<![CDATA[Ari Cahaya Puspitaningrum]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2559
<![CDATA[Nowadays, hospital industries are aware of the importance of technological innovation that needs to be managed properly to drive business continuity and success in the future. The development of technological innovation in hospital industries has increased over time. This happens because of the desire to compete with each other continuously by utilizing technological innovation. This study has observed the existing information systems in the hospital, where the business process of the information system focuses on the hospital's internal correspondence process. This information system is called an e-office which is intended for the National Center General Hospital (RSUPN) Dr. Cipto Mangunkusumo. This study aims to determine what factors influence the successful implementation of the e-office system as seen from the evaluation of user satisfaction. Besides that, this study observed what efforts were made by the PT. Vidya Sentra Utama (Sevima) to create a successful and usable e-office system, where e-office is a large and complex system that includes more than 77 divisions with different business processes. Data collection methods used were interviews, observation, and document analysis. This study contributes to Sevima's knowledge of what factors of success need to be measured to determine user satisfaction and what needs to be done by Sevima's agile team to developing information systems and provide references for further research to evaluate an information system.]]>
<![CDATA[Rancang Bangun Sistem Identifikasi Arus Lalu Lintas pada Simpang Tiga Menggunakan Database NoSQL ]]>
<![CDATA[Muhammad Alkaff]]>;
<![CDATA[Iphan Fitrian Radam]]>;
<![CDATA[Sugiantoro Sugiantoro]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2567
<![CDATA[T-junction is one of the types of intersections that often results in congestion, and long queues. Therefore, it is necessary to identify the traffic flow to determine vehicles per hour, Passenger Car Unit (PCU) per hour, traffic fluctuations, vehicle composition, trip composition and traffic flow at peak hours at T-junction. The process of identifying traffic flow is complex and involves many variables. The process is currently still using Microsoft Excel which requires a lot of time and energy and allows for human error. Therefore, the purpose of this research is to design and build a traffic flow identification system at T-junction using NoSQL database. NoSQL is useful for complex data because NoSQL eliminates repetitive data. The results of this research are the traffic flow identification system at T-junction using NoSQL database which consists of vehicles per hour, PCU per hour, traffic fluctuations, vehicle composition, trip composition, and traffic flow during peak hours.]]>
<![CDATA[Pengembangan Sistem Pengelolaan dan Pemantauan Proyek dengan Metode Agile Pola Scrum ]]>
<![CDATA[Adhe Rama Febrianto]]>;
<![CDATA[Anita Wulansari]]>;
<![CDATA[Latipah Latipah]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2592
<![CDATA[Vsualproject is a business unit of Visi Prima Group which is located in Gresik, a business engaged in software development. In working on the project, the Vsualproject is required to complete the task on time as well as under the customers' requirement. Current management processes were still done manually which consist of recording in the Whatsapp application chat group. In a software development project, it is also necessary to develop the desired interests to find out whether it is under the organization' demands and needs. Keeping notes in the WhatsApp chat group makes notes frequently disappeared and the search process was more complicated about who requests the development process. The purpose of this research is to develop a system that can help Vsualproject to manage projects and provide services to their customers with the project monitoring feature. The system was developed using the Scrum pattern Agile development method which was carried out during the four-cycle sprints. The results of the development of the system were tested by the Black Box Testing method to ensure that the system meets the user's requirements. The result of this study produced a project management system that can be used by internal users of Vsualproject management projects includes managing the stages, payment, and project’s works. The system can also be used by customers to monitor projects through a web profile without asking for special access rights.]]>
<![CDATA[Rancang Bangun Sistem Informasi Geografis Rekomendasi Cagar Budaya Menggunakan Metode Analytic Hierarchy Process ]]>
<![CDATA[Nicolas Evander Suhandi]]>;
<![CDATA[Kristoko Dwi Hartomo]]>;
<![CDATA[Penidas Fiodinggo Tanaem]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2593
<![CDATA[Salatiga City is a town located in the province of Central Java. In this town, there can be found many cultural heritage buildings that were built in the mid-18th century to 1940. Potential visitors would increase easier if a geographic information system is built. Tourists who visit can access the website to select or search for cultural heritage that they want to visit, therefore the availability of a geographic information system that provides information and data on the location of cultural heritage in digital maps is needed. The system must also consider aspects of the cultural heritage rating, the price of admission, and the condition of the cultural heritage to provide recommendations on which cultural heritage to be visited. Therefore the geographic information system of cultural heritage recommendations uses the analytical hierarchy process (AHP) method which can calculate multi- criteria, multi alternatives, and provides cultural heritage recommendations. This system combines geographic information system as a provider of cultural heritage information and AHP decision support system to assist tourists in choosing cultural heritage.]]>
<![CDATA[Optimasi Fuzzy Artificial Neural Network dengan Algoritma Genetika untuk Prediksi Harga Crude Palm Oil ]]>
<![CDATA[Anwar Rifa'i]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2617
<![CDATA[Crude Palm Oil (CPO) is one of Indonesia's best export commodities. CPO production competition causes price fluctuations so that it can trigger losses. The solution that can be taken to avoid losses is to predict the price of CPO. Time series data in the previous months, starting from January 2009 until January 2020, are used as a reference to predict the next CPO price. In this research, CPO price prediction is carried out with a combination of artificial intelligence concepts, namely Radial Basis Function Neural Network (RBFNN), and fuzzy logic. The combination of these methods, namely Fuzzy Radial Basis Function Neural Network (FRBFNN), is then optimized using genetic algorithms. The prediction results show that the error based on the MAPE value for FRBFNN prediction on training data is 11.7% and the MAPE value for testing data is 9.4%. In the FRBFNN prediction that was optimized using a genetic algorithm, the MAPE value was 10.2% for training data and 8.3% for testing data.]]>
<![CDATA[K-Nearest Neighbor Berbasis Particle Swarm Optimization untuk Analisis Sentimen Terhadap Tokopedia ]]>
<![CDATA[Dicki Pajri]]>;
<![CDATA[Yuyun Umaidah]]>;
<![CDATA[Tesa Nur Padilah]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2658
<![CDATA[Tokopedia is a popular marketplace used by e-commerce in Indonesia. Customers’ perception of Twitter towards Tokopedia can be used as an important source of information and can be processed into useful insights. Sentiment analysis is a solution that can be used to process the customers’ perception using K-Nearest Neighbor based on Particle Swarm Optimization. The purpose of this study is to classify customers’ perception based on positive, neutral, and negative classes. The test is carried out with four different scenarios and k values which are evaluated using a confusion matrix. Evaluation results showed the distribution of the dataset is 90:10 and the value of k = 1 is the best evaluation result, which is 88.11%. The feature selection was used for results by using Particle Swarm Optimization. The Particle Swarm Optimization used 20 iterations and 10 particles. It produced 97.9% the best evaluation accuracy, 96.17% precision, 96.62% recall, and 96.39% f-measure.]]>
<![CDATA[Prediksi Risiko Perjalanan Transportasi Online Dari Data Telematik Menggunakan Algoritma Support Vector Machine ]]>
<![CDATA[Christ Memory Sitorus]]>;
<![CDATA[Adhi Rizal]]>;
<![CDATA[Mohamad Jajuli]]>
<![CDATA[ Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI ]]>
Publisher : <![CDATA[Maranatha University Press ]]>
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DOI: 10.28932/jutisi.v6i2.2672
<![CDATA[The ride-hailing service is now booming because it has been helped by internet technology, therefore many call this service online transportation. The magnitude of the potential for growth in online transportation service users also increases the risk of user satisfaction which could have declined therefore the company is increasing in its service. Both in terms of application and services provided by partners/drivers of the company. During each trip, the online transportation application will record device movement data and send it to the server. This data set is usually called telematic data. This telematics data if processed can have enormous benefits. In this study, an analysis will be conducted to predict the risk of online transportation trips using the Support Vector Machine (SVM) algorithm based on the obtained telematic data. The data obtained is telematic data so it must be processed first using feature engineering to obtain 51 features, then trained using the SVM algorithm with RBF kernel and modified C values. Every C value that is changed will be used K-Fold cross-validation first to separate the testing data and training data. The specified k value is 5. The results for each trial obtained accuracy, Receiver Operating Characteristic (ROC) and Area Under the Curves (AUC), for the best that is at C = 100 while the worst at C = 0.001.]]>
