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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 564 Documents
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Identifying The Common Type of Spelling Error by Leveraging Levenshtein Distance and N-gram Hardiyanti, Margareta
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.29273

Abstract

Purpose: This study aims to identify the common type of spelling error and it uses the list of common misspelling words submitted by Wikipedia contributors. Methods: Levenshtein and N-gram distance are utilized to predict the correct word of misspelling from English dictionary. Then, the result of both algorithms is observed and evaluated using recall metrics to determine which technique works more effectively. Result: The result of this study shows that Levenshtein works well to correct substitution single letter and transposition two sequenced letters, while N-gram operates effectively to fix the word with letter omission. The overall result is then evaluated by recall measurement to see which technique that works well on correcting the misspellings. Since the recall of Levenshtein is higher than N-gram, it is concluded that the frequency of misspelling words that are correctly fixed by Levenshtein occurs more often. Novelty: This is the first study that compares two spelling correction algorithms on identifying the common type of spelling error.
Genetic Algorithm for Relational Database Optimization in Reducing Query Execution Time Hidayat, Kukuh Triyuliarno; Arifudin, Riza; Alamsyah, Alamsyah
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.12720

Abstract

The relational database is defined as the database by connecting between tables. Each table has a collection of information. The information is processed in the database by using queries, such as data retrieval, data storage, and data conversion. If the information in the table or data has a large size, then the query process to process the database becomes slow. In this paper, Genetic Algorithm is used to process queries in order to optimize and reduce query execution time. The results obtained are query execution with genetic algorithm optimization to show the best execution time. The genetic algorithm processes the query by changing the structure of the relation and rearranging it. The fitness value generated from the genetic algorithm becomes the best solution. The fitness used is the highest fitness of each experiment results. In this experiment, the database used is  MySQL sample database which is named as employees. The database has a total of over 3,000,000 rows in 6 tables. Queries are designed by using 5 relations in the form of a left deep tree. The execution time of the query is 8.14247 seconds and the execution time after the optimization of the genetic algorithm is 6.08535 seconds with the fitness value of 0.90509. The time generated after optimization of the genetic algorithm is reduced by 25.3%. It shows that genetic algorithm can reduce query execution time by optimizing query in the part of relation. Therefore, query optimization with genetic algorithm can be an alternative solution and can be used to maximize query performance.
Information and Analysis System Stages of Family Welfare in District Balong Ayu, Eka Arynda; Widaningrum, Ida
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.7217

Abstract

Badan Kependudukan dan Keluarga Berencana Nasional (BKKBN) is a family that formed due to legal marriage, is able to meet the needs of the spiritual and the material that is decent, devoted to God Almighty, have a relationship that is harmonious and balanced between members and between families with the community and the environment. Every year the government to collect data on the status of a prosperous family stage where the purpose of the data collection is in the framework of development and poverty alleviation programs. Data collection process in the District Balong is still done manually so that the risk of error in determining the status of a family stage could happen. Information and analysis system of status stages of family welfare is designed to make web-based officers in the input data and determine the status of a prosperous family stages based on selected indicators of the sheet R/1/KS. Sample of data from Bulukidul village and sub-district village of Balong Ngraket 2014. Results of the system in the form of data reports the results of process steps and the results can be viewed in graphical form. Comparison chart to show the status of the highest percentage of poor welfare families stages. Instead lowest percentage shows the stages of a prosperous family able or rich. 
Sentiment Analysis Provider By.U on Google Play Store Reviews with TF-IDF and Support Vector Machine (SVM) Method Fransiska, Susanti; Rianto, Rianto; Gufroni, Acep Irham
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25596

Abstract

Provider By.U is a relatively new and attractive telecommunications service with claims to be the first digital provider in Indonesia. All services are done digitally with the By.U application that offers convenience. Even so not all users are satisfied with the service, there are criticisms and suggestions, one of which is delivered through the By.U app review feature on the Google Play Store. Sentiment analysis is performed to extract information related to provider by.U. The steps taken are scrapping review data, positive and negative labeling, preprocessing data including data cleaning, data normalization, stopword removal and negation handling, sentiment classification using Support Vector Machine (SVM) and TF-IDF as feature extraction. TF-IDF+SVM with 5-Fold Validation produces pretty good accuracy with an average accuracy of 84.7%, precision of 84.9%, recall of 84.7%, and f-measure of 84.8%. The highest accuracy results in fold 2, 86.1%. The effect of TF-IDF on the measurement of model performance is not so great, but it is better.
Sistem Pengolahan Data Kegiatan Penelitian dan Pengabdian Kepada Masyarakat di Universitas Respati Yogyakarta Hamzah, Hamzah
Scientific Journal of Informatics Vol 3, No 1 (2016): May 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i1.5473

Abstract

Unit Penelitian dan Pengabdian pada Masyarakat merupakan salah satu unit di Universitas Respati Yogyakarta yang bertugas untuk mengelola kegiatan penelitian dan pengabdian kepada masyarakat yang dilakukan oleh dosen. Dalam proses pengolahan data kegiatan kegiatan penelitian dan pengabdian kepada masyarakat masih mengalami beberapa permasalahan yaitu belum adanya basis data yang digunakan untuk pengumpulan data rekam jejak kegiatan penelitian dan pengabdian kepada masyarakat oleh dosen dan sistem pengarsipan dokumen masih berbentuk kertas yang berdampak pada kerusakan dokumen, hilangnya dokumen, efisiensi ruang dan pencarian data. Penelitian yang dilakukan bertujuan menghasilkan luaran sistem informasi yang dapat melakukan proses pengolahan data penelitian dan kegiatan pengabdian kepada masyarakat yang dikelola oleh Unit Penelitian dan Pengabdian pada Masyarakat di Universitas Respati Yogyakarta. Pengolahan data mengacu pada komponen beban kerja dosen dibidang penelitian dan pengabdian kepada masyarakat. Metode pengembangan dilakukan dengan tahapan analisa sistem, perancangan sistem, coding dan implementasi sistem. Hasil pengembangan sistem informasi penelitian dan pengabdian masyarakat yaitu sebuah sistem yang dapat membantu Unit Penelitian dan Pengabdian pada Masyarakat dalam proses pengolahan data rekam jejak kegiatan penelitian dan kegiatan pengabdian kepada masyarakat yang dilakukan dosen.
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.
INTESTINE DISEASE DIAGNOSIS SYSTEM USING CERTAINTY FACTOR METHOD Kirana, Chandra -; Pradana, Harrizki Arie; Sulaiman, Rahmat -
Scientific Journal of Informatics Vol 6, No 1 (2019): May 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.17908

Abstract

Inside the human body there are many important organs, one of which is the intestine. Intestinal disease / digestive disease is a disease that most often attacks the digestive tract in humans. There are several intestinal diseases that are dangerous and there are also harmless intestinal diseases. In this research, researchers created an android-based expert system application that can provide information to the users about diseases that are being suffered through the symptoms experienced by the user. The process of making expert system applications using the certainty factor algorithm. The certainty factor algorithm is used to accommodate the uncertainty of an expert's. The mechanism that be used in the certainty factor algorithm on each symptom uses a measure of increased belief (MB) and measure of increased disbelief (MD). Expert system applications that have been built to detect intestinal diseases based on Android have been successfully implemented with a presentation of accuracy of 99.7265625%. by that percentage, it show us that the diagnosis of symptoms of the selected disease is in suitable by the experienced of user, and has the accuracy determined by the system
Logaritmic Fuzzy Preference Programming Approach for Evaluating University Ranking Optimization Wahyuningrum, Tenia; Pandiya, Ridwan
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.6738

Abstract

Assesing quality university’s website trough webometrics is becoming one of many measures in World Class University. To get good grades, so that it can compete with other universities in the world, it needs to be pursued strategies based on the achievement of the perspective of cost (expenses) and the condition of the availability and readiness of human resource (HR owned) by the institution. Webometrics ranking optimization tailored to the institutional capacity is absolutely necessary, in order to achieve the expected goals effectively and fuel-efficient. Therefore, this paper discussed the application of the Analytical Hierarchy Process with Logarithmic Fuzzy Preference Programming combination proved to covered of the methods FPP on the university web ranking optimization. From the results of sub-criteria weighting based on the perspective of cost and human resources, earned the highest ranking among other factors recommended monitoring the ranking of sites ahrefs (C332) and majesticseo (C331) as well as increasing the number of links from other websites (C321). 
Multi-hop Communication between LoRa End Devices Triwidyastuti, Yosefine; Musayyanah, Musayyanah; Ernawati, Fifin; Affandi, Charisma Dimas
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.21855

Abstract

Gateway elimination in a LoRa network could highly reduce the network installation cost. However, LoRa end devices could not overcome many obstacles with only a point-to-point communication. Thus, this research implemented a multi-hop communication in a LoRa network. One or more LoRa end devices are placed between the source node and the destination node to act as relay nodes. A simple routing based on the packet length is configured to determine the packet transmission path. As the results, the designed multi-hop communication could improve packet success rate until 2,47 times in indoor environment. Whereas, the optimum delay time for multi-hop communication is 100 ms for each hop to produce high PRR and lowest RTT.
Implementasi Vector Space Model dalam Pembangkitan Frequently Asked Questions Otomatis dan Solusi yang Relevan untuk Keluhan Pelanggan Aziz, Abdul; Saptono, Ristu; Suryajaya, Kartika Permatasari
Scientific Journal of Informatics Vol 2, No 2 (2015): November 2015
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v2i2.5076

Abstract

Salah satu keunggulan dari sebuah lembaga/unit pelayanan adalah seberapa cepat dan akurat dalam menangani keluhan pelanggan. Keluhan yang disampaikan pelanggan umumnya memiliki kesamaan dengan keluhan-keluhan sebelumnya, sehingga solusi dari keluhan baru dapat didasarkan pada solusi yang diberikan pada keluhan lama. Vector Space Model (VSM) merupakan salah satu model yang digunakan untuk mengetahui kemiripan dokumen, yang digunakan dalam membangkitkan FAQ otomatis. Pembobotan term dilakukan dengan teknik Term Frequency-Inverse Document Frequency (TF-IDF). Kombinasi notasi TF-IDF yang dibandingkan adalah TF-IDF itu sendiri, modifikasi logaritmik TF dan modifikasi logaritmik IDF. Similarity measure yang digunakan adalah cosine similarity. Hasil dari penelitian ini adalah algoritma VSM dengan pembobotan TF-IDF dapat digunakan untuk membangkitkan FAQ otomatis dan solusi yang relevan. Berdasarkan hasil perhitungan accuracy pada masing- masing percobaan dapat disimpulkan bahwa pada threshold 0.5, kombinasi notasi TF-IDF yang memiliki nilai rata-rata accuracy dan precision tertinggi adalah modifikasi pertama, yaitu masing-masing sebesar 62.09% dan 55.15%. Sedangkan untuk threshold 0.65 yang memiliki nilai rata-rata accuracy dan precision tertinggi adalah TF-IDF, yaitu masing-masing sebesar 83.18% dan 68.35%. Selain itu percobaan dengan menggunakan 171 data, TF-IDF dan threshold 0.65 dapat membangkitkan 27 FAQ, yaitu dengan persentase 70.37% relevan. 

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