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Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : -     EISSN : 25973584     DOI : -
Core Subject : Science,
Computer Science & IT
Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK) merupakan ajang pertemuan ilmiah, sarana diskusi dan publikasi hasil penelitian maupun penerapan teknologi terkini dari para praktisi, peneliti, akademisi dan umum di bidang sistem informasi dan teknologi dalam artian luas.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 472 Documents
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Pemilihan Guru Terbaik Berbasiskan Web menggunakan Metode Simple Additive Weighting Sumardiono; Zahra Qotrun Nida
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The complete information system is technology that is based on the thoughts of people who have interests; the aim is to assist in the activities of these people, especially in an organization such as a school, one of which is selecting the best teachers. We still consider the selection of the best teacher in a school to be subjective, as it involves the appointment of a leader or principal, either without or with the support of objective data. The research is a case study at one of the vocational schools in Bekasi City. This research was carried out using a quantitative approach by developing a web-based system using the Simple Additive Weighting (SAW) method. This SAW method explains values from normalization to preference and ranking, making it easier to determine and select the object in question, namely the best teacher. The results of this research were measured by a usability value of 89%, a reliability value of 88%, an efficiency value of 91%, and a functionality value of 91%. By looking at several system testing factors above, it can be concluded that web-based best teacher selection is ready to be used at the vocational school.
Implementasi Metode Trend Projection pada Sistem Prediksi Penggunaan Consumable Berbasis Web Dwi Ismiyana Putri; Putri Nikmaturidha; Yogi Kristiyanto; Solikin; Muhamad Baydhowi; Sumardiono
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Recording the use of consumables in the quality department has not been done consistently and is still done by recording on a piece of paper collection form, then transferring to an excel form, causing errors such as lack of consumable stock before the time the purchase should be made. This causes excess funds and the use of other funds to buy the shortage of consumables needed. This research uses the Extreme Programming (XP) system development model with the Trend Projection method, aiming to overcome existing problems by predicting consumable forecasts based on trends from previous item data. The output of the Trend Projection Method forecasting can help, simplify, and speed up the admin in determining what items are worth buying for use in the next month with a more detailed amount.
Peringkas Teks Otomatis Berita Online Komisi Pemilihan Umum Menggunakan Algoritma K-Means Clustering Ezra Matthew Warouw Runturamby; Vivi Peggie Rantung; Kristofel Santa
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This research aims to develop an automatic text summarization system capable of summarizing online news about the General Election Commission (KPU) using the K-Means Clustering algorithm. In the current digital era, online news has become a primary source of information for the public, but the overwhelming amount of available information often makes it difficult for readers to filter and comprehend news efficiently. The low reading interest of the public further exacerbates this issue. Therefore, the automatic text summarization system is expected to provide a solution by helping readers quickly and effectively grasp the essence of the news. The K-Means Clustering algorithm will group sentences in the news into several clusters, which will then be used to create a representative summary. This research also identifies challenges such as the accuracy of the summary and the diversity of language in the news. The implementation of this system is expected to improve readers' time efficiency, provide better access to information, and support increased public participation in the democratic process.
Implementasi Augmented Reality untuk Pembelajaran Gerakan Pencak Silat Menggunakan Unity dan Vuforia Fahmi; Alders Paliling; Ery Muchyar Hasiri; LM. Fajar Israwan
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Pencak Silat is a traditional martial art that originated in Indonesia, now pencak silat is a sport that has many enthusiasts in various countries. At the State Junior High School 4 Wangi - Wangi, pencak silat still uses a learning method with direct practice in the field which is only done 1 time a week. This research aims to design and build a learning application for the Pencak Silat movement by applying Augmented Reality technology. In making this application, there are several stages, namely, character design and animation using avatars sdk and blender which then markers are stored in the Vuforia database and built using unity. This research produces the application of Augmented Reality in Learning Pencak Silat movements as a learning medium that can be used as a learning medium for students, where students can learn Pencak Silat movements by looking at the movements of characters in the application in 3 dimensions so that it will make students enthusiastic in learning Pencak Silat.
Implementasi Projection Profile dan Connected Component untuk Segmentasi Citra Manuskrip Beraksara Jawa Cetak Gerardus Kristha Bayu Indraputra; Anastasia Rita Widiarti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Javanese script is one of Indonesia's cultural heritages. Many ancient manuscripts in Javanese script are still neatly stored in museums and libraries in Indonesia, but only a few people can utilize the important information contained therein. The difficulty of the transliteration process is one of the challenges in obtaining this important information. With the development of document image analysis science, this research was developed to help shorten the process of transliterating Javanese manuscript images. Segmentation is an essential stage in transliterating the manuscript image, namely, automatically taking each script image in a document. This research developed the segmentation process by combining the projection profile and connected component methods. Using one image from a scanned manuscript in the book "Hamong Tani" written using printed Javanese script on page 5, the results of line segmentation with 100% accuracy and the results of Javanese script segmentation with 95.952% accuracy were obtained after preprocessing. From the large segmentation accuracy value, it can be concluded that the projection profile and connected component methods can be used well in segmenting printed Javanese manuscript images.
Aplikasi Pembelajaran Bahasa Daerah Tontemboan Menggunakan Metode Extreme Programming Berbasis Android Glendy Koleangan; Vivi Peggie Rantung
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Regional languages play an important role in maintaining the cultural identity of a community, but their use is decreasing due to globalization and technological developments. This study aims to preserve the Tontemboan language, a language used by the Tontemboan tribe in Minahasa, through the development of an Android-based learning application using the Extreme Programming (XP) method. The research method used is application development with data collection methods such as interviews and observations, analysis and qualitative data. The results of the study indicate that this application is effective in improving the understanding and use of the Tontemboan language among users. The conclusion of this study is that technology-based learning applications can be an effective tool in preserving regional languages and cultural heritage.
Implementasi Data Mining Dalam Pengelompokan Data Penyakit Pasien Menggunakan Metode K-Means Clustering Gusna Mayang Sari; Irfan AP
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study aims to identify the pattern and distribution of diseases at the Mambi Health Center using the K-Means Clustering method. Patient data includes age, gender, address, and type of disease suffered. This method was chosen because of its ability to group data based on similar characteristics, making it easier to identify dominant diseases. The results reveal the age groups susceptible to certain diseases, the geographical distribution of diseases with high prevalence, and the types of diseases often encountered at the Puskesmas. These insights are expected to help Puskesmas in allocating resources effectively, designing more appropriate prevention programs, and improving the quality of health services. This study also provides recommendations for disease management strategies based on the identified groups, so as to support efforts to improve public health.
Prediksi Pendapatan Penjualan Menggunakan Metode Double Exponential Smoothing Pada Toko Retail XYZ I Gede Sudiantara; I Made Oka Widyantara; I Gede Iwan Sudipa; I Gusti Agus Adek Putra Ardiwinata
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Revenue is a key indicator in determining a company's financial success, both for identifying potential profits and losses. This predictive model is designed to assist management in developing strategies to increase product sales. Accurate forecasting can provide early warnings regarding the actions store management needs to take. This study employs the Double Exponential Smoothing Brown method with a smoothing parameter alpha (?) of 0.5. The analysis results indicate that the Mean Absolute Percentage Error (MAPE) values range from 0.26% to 4.29%, demonstrating a high level of accuracy. Based on these MAPE results, the predictive model is then implemented into a web-based system. This system allows management to access information anytime and anywhere. Therefore, this prediction system is expected to assist the store in making strategic decisions, particularly in managing and increasing future revenues
Mapping Review Penerapan Artificial Intelligence pada Cyber Security untuk Meningkatkan Security Awareness I Putu Agus Eka Pratama; I Made Oka Widyantara; Linawati; Nyoman Gunantara
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The rapid development of information technology (IT), on the one hand, has the potential to increase the number of cyber attacks, so cyber security needs to be handled properly. As the weakest element, efforts are needed to increase cyber security awareness on the user side. Artificial intelligence (AI), which is increasingly developing and widely applied in various fields of life, has the potential to be used to increase security awareness in users. To study this further, a literature study, review, and mapping analysis were conducted from a number of references in order to obtain an overview of the potential and future research plans related to the use of AI in cyber security for security awareness along with providing recommendations. This study conducted a study and analysis using the mapping review method on 37 selected papers indexed by Google Scholar, referring to the NIST (National Institute of Standards and Technology) framework. The results of the mapping review show that the mapping of publications related to the application of AI to cyber security to increase security awareness is the most in 2024, with the most trends being education/training, and the most widely used AI method is deep learning. This study recommends education and deep learning as areas that can be taken for future research related to the application of AI to cyber security.
Klasifikasi Daun Kelor Kering Berbasis Vision Artificial Intelegence I Wayan Sudiarsa; Gede Agus Santiago
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The drying process of moringa leaves (Moringa oleifera) is necessary to reduce the moisture content so that the leaves become dry and can be utilized for the next processes. Drying moringa leaves to change the moisture content from 80% to 9.2% requires an ideal heating condition, as the heating rate must not damage the nutritional content present in the leaves. The utilization of ANN models can recognize seasonal time series data patterns. The introduction is categorized into several classifications. By using IoT, it is hoped that the drying conditions can be monitored. The system is also connected to a recommendation system using Recurrent Neural Networks (RNN), which will provide recommendations for the best conditions for moringa flour production. The Google Cloud Vision AI system suite combines artificial intelligence with other technologies to understand and analyze videos and easily integrate vision detection features into applications. These tools are available through APIs and can still be customized for specific needs. The Google Cloud Vision AI system suite combines artificial intelligence with other technologies to understand and analyze videos, as well as to easily integrate vision detection features into applications. These features include image labelling, face and structure detection, optical character recognition (OCR), and tagging of vulgar content. The test results found that the Vision AI system used has been tested to detect and classify moringa leaves, both in wet and dry conditions. The testing was conducted using a mobile-based Vision AI application and the Google Cloud Vision API. The results indicate that the system detects moringa leaves more as a plant.

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