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Scientific Journal of Informatics
Published by Universitas Negeri Semarang
ISSN : 24077658     EISSN : 24600040     DOI : -
Core Subject : Science,
Computer Science & IT
Scientific Journal of Informatics published by the Department of Computer Science, Semarang State University, a scientific journal of Information Systems and Information Technology which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : -
Articles 19 Documents
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Search results for , issue "Vol 8, No 2 (2021): November 2021" : 19 Documents clear
Model for Identification and Prediction of Leaf Patterns: Preliminary Study for Improvement Muzakir, Ari; Ependi, Usman
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.30024

Abstract

Purpose: Many studies have conducted studies related to automation for image-based plant species identification recently. Types of plants, in general, can be identified by looking at the shape of the leaves, colors, stems, flowers, and others. Not everyone can immediately recognize the types of plants scattered around the environment. In Indonesia, herbal plants thrive and are abundantly found and used as a concoction of traditional medicine known for its medicinal properties from generation to generation. In the current Z-generation era, children lack an understanding of the types of plants that benefit life. This study identifies and predicts the pattern of the leaf shape of herbal plants. Methods: The dataset used in this study used 15 types of herbal plants with 30 leaf data for each plant to obtain 450 data used. The extraction process uses the GLCM algorithm, and classification uses the K-NN algorithm. Result: The results carried out through the testing process in this study showed that the accuracy rate of the leaf pattern prediction process was 74% of the total 15 types of plants used. Value: Process of identifying and predicting leaf patterns of herbal plants can be applied using the K-NN classification algorithm combined with GLCM with the level of accuracy obtained.
Increasing Message Capacity in Images Using Advanced Least Significant Bit and Image Scaling Fadlil, Affan; Prasetiyo, Budi; Alamsyah, Alamsyah
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.28138

Abstract

Purpose: Steganography is the science of writing hidden or hiding messages so that apart from the sender and the recipient, no one can know or realize that a message is hidden. This paper aims to analyze the method of advanced LSB to increase message capacity. Methods/Study design/approach: The steganography technique advanced LSB algorithm develops pre-existing steganographic algorithms such as LSB by utilizing a range of media pixel values cover (images that are used as media to hide messages) with different insertion rules from LSB. Image scaling in digital image processing is known as resampling. Resampling is a mathematical technique used to produce a new image from the previous image with different pixel size, often called interpolation. Increasing the pixel size of the previous image is called upsampling and in this study we will only use twice the image magnification. Result/Findings: The results of each test method using advanced LSB without image scaling and advanced LSB using image scaling were compared to obtain detailed comparison results of each method. Novelty/Originality/Value: Advanced LSB and image scaling in this study can increase the message capacity three times compared to only using the advanced LSB method without image scaling. It depends on the image pixels used.
Tide Prediction in Prigi Beach using Support Vector Regression (SVR) Method Utami, Tri Mar'ati Nur; Novitasari, Dian Candra Rini; Setiawan, Fajar; Ulinnuha, Nurissaidah; Farida, Yuniar; Sari, Ghaluh Indah Permata
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.28906

Abstract

Purpose: Prigi Beach has the largest fishing port in East Java, but the topography of this beach is quite gentle, so it is prone to disasters such as tidal flooding. The tides of seawater strongly influence the occurrence of this natural event. Therefore, information on tidal level data is essential. This study aims to provide information about tidal predictions. Methods: In this case using the SVE method. Input data and time were examined using PACF autocorrelation plots to form input data patterns. The working principle of SVR is to find the best hyperplane in the form of a function that produces the slightest error. Result: The best SVR model built from the linear kernel, the MAPE value is 0.5510%, the epsilon is 0.0614, and the bias is 0.6015. The results of the tidal prediction on Prigi Beach in September 2020 showed that the highest tide occurred on September 19, 2020, at 10.00 PM, and the lowest tide occurred on September 3, 2020, at 04.00 AM. Value: After conducting experiments on three types of kernels on SVR, it is said that linear kernels can predict improvements better than polynomial and gaussian kernels.
ADALINE Neural Network For Early Detection Of Cervical Cancer Based On Behavior Determinant Midyanti, Dwi Marisa; Bahri, Syamsul; Midyanti, Hafizhah Insani
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.31064

Abstract

Purpose: Cervical cancer is one of the most common types of cancer that kills women worldwide. One way for early detection of cervical cancer risk is by looking at human behavior determinants. Detection of cervical cancer based on behavior determinants has been researched before using Naïve Bayes and Logistic Regression but has never using ADALINE Neural Network. Methods: In this paper, ADALINE proposes to detect early cervical cancer based on the behavior on the UCI dataset. The data used are 72 data, consisting of 21 cervical cancer patients and 51 non-cervical cancer patients. The dataset is divided 70% for training data and 30% for testing data. The learning parameters used are maximum epoch, learning rate, and MSE. Result: MSE generated from ADALINE training process is 0.02 using a learning rate of 0.006 with a maximum epoch of 19. Twenty-two test data obtained an accuracy of 95.5%, and overall data got an accuracy value of 97.2%. Novelty: One alternative method for early detection of cervical cancer based on behavior is ADALINE Neural Network. 
Implementation of Support Vector Machine Algorithm with Correlation-Based Feature Selection and Term Frequency Inverse Document Frequency for Sentiment Analysis Review Hotel Ririanti, Novia Puji; Purwinarko, Aji
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.29992

Abstract

Purpose: The study aims to reduce the number of irrelevant features in sentiment analysis with large features. Methods/Study design/approach: The Support Vector Machine (SVM) algorithm is used to classify hotel review sentiment analysis because it has advantages in processing large datasets. Term Frequency-Inverse Document Frequency (TF-IDF) is used to give weight values to features in the dataset. Result/Findings: This study's results indicate that the accuracy of the SVM method with TF-IDF produces an accuracy of 93.14%, and the SVM method in the classification of hotel reviews by implementing TFIDF and CFS has increased by 1.18% from 93.14% to 94.32%. Novelty/Originality/Value: Use of Correlation-Based Feature Section (CFS) for the feature selection process, which reduces the number of irrelevant features by ranking the feature subset based on the strong correlation value in each feature
Geographical Information System of Bus and Travel Counter in Padang City Using BFS Method Based on Mobile Web Sularno, Sularno; Astri, Renita; Anggraini, Putri; Prima Mulya, Dio; Mulya, Dwiki
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.33117

Abstract

Purpose: One of the main objectives of the research is the BFS (Breadth-First Search) algorithm method in the search for nearby bus and travel counters using GPS found on each device used in the search process. Each smartphone produces a different coordinate point with an average distance difference of 30.2 meters to the hardware coordinate point. Each GPS embedded in the smartphone will process the data according to the location conditions of the user's point of existence. The methodology for system development is a standard process for a team of developers to connect all the steps needed in analyzing, designing, implementing, and maintaining information systems. Methods: The methodology becomes a guideline in system development activities in SDLC. The SDLC model used in this study is the WaterFall Model. Result: The results of this study are expected to facilitate the public in booking tickets and to find the nearest location from the bus and travel counters. Novelty: The novelty of this research is the development of GIS as a search for the location of bus and travel counters using the breadth-first search algorithm. This research can help the community find the location of the nearest bus and tourist counter in the city of Padang.
Halal Food Restaurant Classification Based on Restaurant Review in Indonesian Language Using Machine Learning Hidayat, Nurul; Hakim, M. Faris Al; Jumanto, Jumanto
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.33395

Abstract

Purpose: Halal tourism or muslim friendly tourism has big potential for the tourism industry in Indonesia. According to Cresent Rating, the world’s leading authority on halal-friendly travel, one of the indicators for halal tourism is the availability of choices for halal foods. To support halal tourism, unfortunately, not all restaurants around the tourism object or in the city where the tourism object is located have labels or information that makes people know about halal food in the restaurant easily.Methods/Study design/approach: The data in this research was obtained from online media such as Google Maps, TripAdvisor, and Zoomato. The data consists of 870 data with the classification of halal food restaurants and 590 data with the reverse classification. Machine learning methods were chosen as classifiers. Some of them were Naive Bayes, Support Vector Machine, and K-Nearest Neighbor. Result/Findings: The result from this research shows that the proposed method achieved an accuracy of 95,9% for Support Vector Machine, 93,8% for Multinomial Naive Bayes, and 91% for K-Nearest Neighbor. In the future, our result will be to support the halal tourism environment in terms of technology. Novelty/Originality/Value: In this study, we utilize restaurant reviews done by visitors to get information about the classification of halal food restaurants.
Real-Time Monitoring: Development of Low Power Fire Detection System for Dense Residential Housing Based on Internet of Things (IoT) and Cloud Messenger Muhendra, Rifki; Amin, Aisyah
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.30811

Abstract

Purpose: This paper reports on the development of a low-power fire potential monitoring system for densely populated housing based on IoT Study design: This system consists of sensors integrated with a microcontroller and a Wi-Fi module that can provide data in real-time and can be accessed remotely. In addition, this system has also been simulated to analyze environmental conditions as notification data sent using cloud messenger. The grouping of potential fire hazards based on the legibility of physical parameter values is also displayed. Findings: In performance measurement, the data loss of this system is less than 1% of the total data every day. Value: It shows that this system is feasible and applied more broadly to anticipate fires in densely populated areas.
Digital Management of Micro, Small and Medium Enterprises (MSME) Activities Based on the Unified Approach Astri, Renita; Faradika, Faradika; A, M. Razi; Kamal, Ahmad
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.29339

Abstract

Purpose: Micro, Small, and Medium Enterprises (MSME) is an important part of today's Indonesian economy. The times have allowed many people to do their own business. Along with the many existing businesses, many business actors are marketing for the sustainability of their business. A web-based information system that can accommodate information about Micro, Small, and Medium Enterprises management is one of the main needs for MSME actors themselves. Methods/Study design/approach: In addition, the public can use this web-based information system to obtain detailed information on MSME and MSME products through the web. Making the web using the PHP programming language where the approach taken in the design is the Unified Approach used as a method in object-based system development. Result/Findings: From the final results of this study, it can be concluded that the web-based MSME Activity Management Information System can help mass marketing of MSME players and help related agencies to find out the development of existing MSME. Novelty/Originality/Value: The website was built can help and accelerate the marketing process for existing MSMEs and can be used as a medium of communication between MSMEs and visitors.
The Analysis and Optimization of Business Processes for Students in Higher Education Based on Togaf 9.2 Anam, M. Khairul; Nasution, Torkis; Erlinda, Susi; Efrizoni, Lusiana; Susanti, Susanti
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.29952

Abstract

Purpose: The IT Blueprint is used as a guideline in achieving organizational goals, such as the built and development of information technology (IT) infrastructure. STMIK Amik Riau is one of the universities vision to become an excellent university in Sumatra by 2030. To achieve this vision, it is necessary to develop various units, one of which is the built and development of IT in student services. To build IT for student services, an enterprise architecture is needed so that the development is more focused. Study design: In this study, TOGAF became the framework used to design, plan, implement, and manage the company's organizational architecture. TOGAF has 8 phases, but this research takes 6 phases: Architecture Vision, Business Architecture, Information System Architectures, Technology Architecture, Opportunities and Solutions, and Migration Planning. Result: The results obtained in this study are the creation of IT blueprints for student business processes. There are several updates in each process, especially in the information system architecture, then in business processes and technology. There are also updates that need to be done. This study also provides several reasons for updating the Opportunity and Solutions. Other than that, this research guides to apply the updates based on priorities that must be applied to migration planning. Novelty: In the information system architecture, 18 applications become service systems for students. After analyzing it into 31 applications, they will later be used to support good services for students.

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