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Analisis Kinerja Dan Kualitas Hasil Kompresi Pada Citra Medis Sinar-X Menggunakan Algoritma Huffman, Lempel Ziv Welch Dan Run Length Encoding Anandita, Ida Bagus Gede; Gunadi, I Gede Aris; Indrawan, Gede
SINTECH (Science and Information Technology) Journal Vol 1 No 1 (2018): SINTECH Journal Edisi April 2018
Publisher : LPPM STMIK STIKOM Indonesia

Technological progress in the medical area made medical images like X-rays stored in digital files. The medical image file is relatively large so that the image needs to be compressed. The lossless compression technique is an image compression where the decompression results are the same as the original or no information lost in the compression process. The existing algorithms on lossless compression techniques are Run Length Encoding (RLE), Huffman, and Lempel Ziv Welch (LZW). This study compared the performance of the three algorithms in compressing medical images. The result of image decompression will be compared to its performance in the objective assessment such as ratio, compression time, MSE (Mean Square Error) and PNSR (Peak Signal to Noise Ratio). MSE and PSNR are used for quantitative image quality measurement for subjective assessment assisted by three experts who will compare the original image with the decompression image. Based on the results obtained from the objective assessment of compression performance of RLE algorithm showed the best performance by yielding ratio, time, MSE and PSNR respectively 86,92%, 3,11ms, 0 and 0db. For Huffman, the results can be 12.26%, 96.94ms, 0, and 0db respectively. While LZW results can be in sequence -63.79%, 160ms, 0.3 and 58.955db. For the results of the subjective assessment, the experts argued that all images can be analyzed well.

RANCANG BANGUN APLIKASI MOBILE SISKA BERBASIS ANDROID Ceryna Dewi, Ni Kadek; Anandita, Ida Bagus Gede; Atmaja, Ketut Jaya; Aditama, Putu Wirayudi
SINTECH (Science and Information Technology) Journal Vol 1 No 2 (2018): SINTECH Journal Edition Oktober 2018
Publisher : LPPM STMIK STIKOM Indonesia

SISKA is an Academic Information System at Ganesha University of Education (UNDIKSHA) used for TESIS process. Starting from proposal submission, proposal seminar, pre thesis exam and thesis exam. So far the running application is still in web form. With so rapid development of Android-based applications, it will be made SISKA Android-based applications that will certainly make it easier for students and lecturers to access this application via Smartphone. In the development of this application will be used Eclipse commonly used for software development. Web-based SISKA application development into Android-based SISKA application provides a new look that is more user friendly, easy to use, and easy to access using smartphone  

Analisis Kinerja Dan Kualitas Hasil Kompresi Pada Citra Medis Sinar-X Menggunakan Algoritma Huffman, Lempel Ziv Welch Dan Run Length Encoding Ida Bagus Gede Anandita; I Gede Aris Gunadi; Gede Indrawan
SINTECH (Science and Information Technology) Journal Vol. 1 No. 1 (2018): SINTECH Journal Edition April 2018
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v1i1.179

Technological progress in the medical area made medical images like X-rays stored in digital files. The medical image file is relatively large so that the image needs to be compressed. The lossless compression technique is an image compression where the decompression results are the same as the original or no information lost in the compression process. The existing algorithms on lossless compression techniques are Run Length Encoding (RLE), Huffman, and Lempel Ziv Welch (LZW). This study compared the performance of the three algorithms in compressing medical images. The result of image decompression will be compared to its performance in the objective assessment such as ratio, compression time, MSE (Mean Square Error) and PNSR (Peak Signal to Noise Ratio). MSE and PSNR are used for quantitative image quality measurement for subjective assessment assisted by three experts who will compare the original image with the decompression image. Based on the results obtained from the objective assessment of compression performance of RLE algorithm showed the best performance by yielding ratio, time, MSE and PSNR respectively 86,92%, 3,11ms, 0 and 0db. For Huffman, the results can be 12.26%, 96.94ms, 0, and 0db respectively. While LZW results can be in sequence -63.79%, 160ms, 0.3 and 58.955db. For the results of the subjective assessment, the experts argued that all images can be analyzed well.

RANCANG BANGUN APLIKASI MOBILE SISKA BERBASIS ANDROID Ni Kadek Ceryna Dewi; Ida Bagus Gede Anandita; Ketut Jaya Atmaja; Putu Wirayudi Aditama
SINTECH (Science and Information Technology) Journal Vol. 1 No. 2 (2018): SINTECH Journal Edition Okctober 2018
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v1i2.291

SISKA is an Academic Information System at Ganesha University of Education (UNDIKSHA) used for TESIS process. Starting from proposal submission, proposal seminar, pre thesis exam and thesis exam. So far the running application is still in web form. With so rapid development of Android-based applications, it will be made SISKA Android-based applications that will certainly make it easier for students and lecturers to access this application via Smartphone. In the development of this application will be used Eclipse commonly used for software development. Web-based SISKA application development into Android-based SISKA application provides a new look that is more user friendly, easy to use, and easy to access using smartphone

IMPLEMENTASI ALGORITMA GENETIKA BERBASIS WEB PADA SISTEM PENJADWALAN MENGAJAR DI SMK DWIJENDRA DENPASAR Ni Luh Wiwik Sri Rahayu Ginantra; Ida Bagus Gede Anandita
Jurnal Teknologi Informasi dan Komputer Vol 5, No 1 (2019): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (721.327 KB)

ABSTRACTIntelligence from a computer that can mimic the human work system is commonly referred to as artificial intelligence which can solve problems (problem solving) that are complicated and sometimes humans themselves cannot solve them, as in the process of scheduling subjects. The preparation of scheduling school subjects is prepared by considering several components including; Teachers, time, majors, levels, and subjects themselves. Based on these problems the researchers conducted a study of scheduling school subjects with the method of Genetic Algorithm and took a case study at one of the private vocational high schools in Denpasar, namely SMK Dwijendra Denpasar. Based on the results of the design and discussion that have been conducted, scheduling teaching with Genetic Algorithms with case studies at Dwijendra Vocational School can be done by using subject data and teachers from the Vocational School and producing teaching schedules for teachers at the school so that there is no schedule clash. The results of testing carried out in this study are by testing measurements of population size and size of generations. The test was carried out by using a population size and generation of 150 with a crossover rate (cr) of 50%. The test results show that in a small population and generation produce a variety of fitness values. Good fitness values are generated in populations and generations above 50.Keywords: Genetic Algorithms, Scheduling, Lesson Type.ABSTRAKKecerdasan dari komputer yang dapat meniru system kerja manusia biasa disebut dengan istilah kecerdasan buatan (artificial intelegence) yang dapat memecahkan masalah (problem solving) yang rumit dan kadang manusia sendiri tidak dapat menyelesaikannya, seperti dalam proses penjadwalan mata pelajaran. Penyusunan penjadwalan mata pelajaran sekolah disusun dengan mempertimbangkan beberapa komponen diantaranya ; Guru, waktu, jurusan, jenjang, dan mata pelajaran itu sendiri. Berdasarkan permasalahan tersebut peneliti melakukan penelitian tentang penjadwalan mata pelajaran sekolah dengan metode Algoritma Genetika dan mengambil studi kasus pada salah satu sekolah menengah kejuruan (SMK) swasta di Denpasar yaitu SMK Dwijendra Denpasar. Berdasarkan hasil perancangan dan pembahasan yang telah dilakukan, penjadwalan mengajar dengan algoritma Genetika dengan studi kasus di SMK Dwijendra dapat dilakukan dengan menggunakan data mata pelajaran dan guru dari SMK tersebut dan menghasilkan jadwal mengajar bagi guru di sekolah tersebut sehingga tidak terjadinya bentrokan jadwal. Hasil pengujian yang dilakukan pada penelitian ini yaitu dengan pengujian pengukuran ukuran populasi dan ukuran ukuran generasi. Pada pengujian tersebut dilakukan dengan menggunakan ukurun populasi dan generasi sebanyak 150 dengan crossover rate (cr) 50%. Hasil pengujian menunjukan bahwa pada populasi dan generasi sedikit menghasilkan nilai fitness yang beragam. Nilai fitness yang baik dihasilkan pada populasi dan generasi diatas 50.Kata Kunci : Algoritma Genetika, Penjadwalan, Mata Pelajaran

Sales Forecasting System Using Single Exponential Smoothing Ketut Jaya Atmaja; Ida Bagus Gede Anandita
Jurnal Mantik Vol. 4 No. 4 (2021): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2021.1207.pp2552-2557

In a trading business, meeting customer demand is very important to do. Fulfilling customer demand can be done with good stock inventory management. Accuracy in carrying out stock management is important to maintain the level of satisfaction of consumers because of the needs being met. In addition, accuracy in carrying out stock management can affect the financial cash flow of a trading business. Over-stocking, over time it will become dead-stock because the goods being sold become obsolete, changes in market tastes, not to mention merchandise that has an expiration date. Meanwhile, too little stock can cause lost of sales because the level of demand from consumers is greater than the amount of existing stock. Forecasting systems can help maximize stock inventory management in meeting customer demand needs. Forecasting is an activity in predicting and predicting something that will happen in the future. Forecasting is done through calculation analysis techniques based on past data references. This data can be in the form of qualitative data and quantitative data. The exponential smoothing method is a forecasting method based on qualitative data from a time series of previous sales trends to predict the future. This method is best used to analyze fluctuating sales trends. To determine the accuracy of forecasting, the results of the forecasting are then analyzed using the MSE and MAPE methods.

Comparative Analysis of Naïve Bayes and K-Nearest Neighbor (KNN) Algorithms in Stroke Classification Iswara, Ida Bagus Ary Indra; Anandita, Ida Bagus Gede; Dahul, Maria
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4395

Stroke, also known as cerebrovascular, is a type of Non-Communicable Disease (NCD). The symptoms of this disease arise due to a blockage (ischemic) or rupture (hemorrhagic) of a blood vessel that disrupts blood flow to the brain. This condition causes a lack of oxygen and nutrients to brain cells, resulting in damage and potentially death. This research aims to compare the use of Naive Bayes and K-Nearest Neighbor (K-NN) algorithms in classifying stroke diseases. The research process involves data collection, data validation, data preprocessing, data reading, data transformation, data splitting, model implementation, classification evaluation, application of Naive Bayes and K-Nearest Neighbor (K-NN) algorithms, and comparative analysis of results. The variables used in this study include: gender, age, hypertension, heart disease, ever married, work type, residence type, avg glucose level, bmi, smoking status, stroke. Sugar, BMI, Smoking Status, Stroke. Based on the experiments conducted, it was found that the Naive Bayes algorithm achieved an average accuracy rate of 91.67%, while the K-Nearest Neighbor (K-NN) algorithm achieved an average accuracy rate of 95.59%. Therefore, it can be concluded that the K-Nearest Neighbor (K-NN) algorithm has a higher average accuracy rate than the Naive Bayes algorithm, with a percentage difference in accuracy of 3.92%.

Penerapan Metode Single Exponential Smoothing Dalam Peramalan Penjualan Barang Ginantra, Ni Luh Wiwik Sri Rahayu; Anandita, Ida Bagus Gede
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

The technology of buying and selling goods in managing goods in and out will provide convenience for the management in managing stock data, financial control and profit calculation that will be immediately known by stakeholders. Forecasting method is a method that is able to analyze several factors that are known to influence the occurrence of an event with a long grace period between the need for knowledge of an event to occur in the future and the time the event has occurred in the past. In a retail company, if this forecasting method is applied in the planning of goods management, the company will be assisted in the process of planning the sale of goods which is currently still being done by predicting the amount of sales of goods that will come without any calculation, causing excessive purchases of goods that can affect the stock of goods. Single exponential smoothing method is a development of the single moving averages method where the forecasting method is done by repeating calculations continuously using the latest data and each data is weighted. The single exponential smoothing method considers the weight of the previous data by giving weight to each data period to distinguish the priority of data. The single exponential smoothing method is a method used in short-term forecasting that is usually only 1 month ahead which assumes that the data fluctuates around a fixed mean value without consistent trends or growth patterns. The accuracy of the application of the single exponential method in forecasting sales of goods in this study with an alpha value of 0.1 on the MAPE calculation average is 2%.

Penerapan Metode Single Exponential Smoothing Dalam Peramalan Penjualan Barang Ginantra, Ni Luh Wiwik Sri Rahayu; Anandita, Ida Bagus Gede
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i2.162

The technology of buying and selling goods in managing goods in and out will provide convenience for the management in managing stock data, financial control and profit calculation that will be immediately known by stakeholders. Forecasting method is a method that is able to analyze several factors that are known to influence the occurrence of an event with a long grace period between the need for knowledge of an event to occur in the future and the time the event has occurred in the past. In a retail company, if this forecasting method is applied in the planning of goods management, the company will be assisted in the process of planning the sale of goods which is currently still being done by predicting the amount of sales of goods that will come without any calculation, causing excessive purchases of goods that can affect the stock of goods. Single exponential smoothing method is a development of the single moving averages method where the forecasting method is done by repeating calculations continuously using the latest data and each data is weighted. The single exponential smoothing method considers the weight of the previous data by giving weight to each data period to distinguish the priority of data. The single exponential smoothing method is a method used in short-term forecasting that is usually only 1 month ahead which assumes that the data fluctuates around a fixed mean value without consistent trends or growth patterns. The accuracy of the application of the single exponential method in forecasting sales of goods in this study with an alpha value of 0.1 on the MAPE calculation average is 2%.

Visual Analysis of Marketplace Sales Data for Strategic Decision Making Using Tableau Dewi, Ni Luh Putu Trisna Kantina; Nilawati, Ni Ketut Utami; Anandita, Ida Bagus Gede
TECHNOVATE: Journal of Information Technology and Strategic Innovation Management Vol. 1 No. 3 (2024): July 2024
Publisher : PT.KARYA GEMAH RIPAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52432/technovate.1.3.2024.156-169

PT Akselerasi Sumber Berkah is a local company engaged in the production and distribution of beauty and health products, under the brand name Beaudelab. This company was established in 2019. PT Akselerasi Sumber Berkah is located in West Denpasar, Bali. In processing sales data, the company uses Microsoft Excel. The weakness of the data or information generated is still in the form of tables that do not display more informative information in the form of graphs, making it difficult for companies to see sales developments and other information in a short time. Therefore, in this study, a sales data visualization using tableau was built to assist companies in processing table data into information in the form of graphs so that it does not take a long time to see the company's sales development. The research method used in this research is the nine steps kimball method. In this research through the stages of analyzing company data, designing a data warehouse, extract transform load process, implementing data visualization, and testing the system. This system was tested using the user acceptance test method and has obtained results with a percentage of 93% or strongly agree so that this sales data visualization is in accordance with the needs of the company. The results of this study are in the form of 3 pages that display company information in the form of graphs to assist in decision making.

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