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SINTECH (Science and Information Technology) Journal
Published by STMIK STIKOM Indonesia
ISSN : 25987305     EISSN : 25989642     DOI : -
Core Subject : Science,
Computer Science & IT
SINTECH (Science and Information Technology) Journal merupakan jurnal yang dikelola dan diterbitkan oleh Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK STIKOM Indonesia, dengan e-ISSN 2598-9642 dan p-ISSN: 2598-7305. SINTECH Journal diterbitkan pertama kali pada bulan April 2018 dan memiliki periode penerbitan sebanyak dua kali dalam setahun, yaitu pada bulan April dan Oktober. Bidang keilmuan dari SINTECH Journal mencakup bidang ilmu : Data analysis, Natural Language Processing, Artificial Intelligence, Neural Networks, Pattern Recognition, Image Processing, Genetic Algorithm, Bioinformatics/Biomedical Applications, Biometrical Application, Content-Based Multimedia Retrievals, Augmented Reality, Virtual Reality, Information System, Game Mobile, dan IT Bussiness Incubation.
Arjuna Subject : -
Articles 166 Documents
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Implementasi Metode Convolutional Neural Network Pada Pengenalan Aksara Bali Berbasis Game Edukasi I Gusti Ngurah Anom Cahyadi Putra I Gusti Ngurah; I Kadek Agus Andika Putra; Ida Bagus Gede Dwidasmara; Made Widiartha; Ngurah Agus Sanjaya ER; I Putu Gede Hendra Suputra
SINTECH (Science and Information Technology) Journal Vol. 6 No. 1 (2023): SINTECH Journal Edition April 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i1.1298

Abstract

Balinese script or also known as hanacaraka, is the writing used by Balinese people to write their language. In general, this script is used to write everyday language and literary language. Balinese script in the past was not only used for writing literature or sacred texts but also for writing everyday language. Balinese script plays an important role in literary writing. The sacred text of the Vedas uses Balinese script in the Sanskrit language. In preserving the Balinese script, itself, Balinese script lessons are mandatory for students from elementary school to high school. In addition to studying at school, interesting learning is certainly needed to attract students' interest. One way is by way of game applications or educational games. This Balinese script recognition application receives input in the form of Balinese script writing characters from the user, then it will be processed by preprocessing and continued with the classification training process using the Convolutional Neural Network (CNN) and Backpropagation methods. The result is a web-based application that can recognize Balinese script writing with the CNN classification method with an accuracy rate of 81.3% and gets a positive response from respondents who have tested the application.
Analisa Prediksi Harga Emas Dengan Kemungkinan Terjadinya Resesi Menggunakan Metode SVR Fevrierdo Nathaniel Shanahan Pradana; Frederik Samuel Papilaya
SINTECH (Science and Information Technology) Journal Vol. 6 No. 1 (2023): SINTECH Journal Edition April 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i1.1329

Abstract

Gold is a resource that has a high value and has the advantage of a stable selling price. This can be proven by the choice of gold which is often used as a long-term investment tool. It can be seen that the impact of Covid-19 and the Russia-Ukraine war is considered to be the causes of recession that will affect the economy and end with the changes of gold selling price. This research was conducted on the basis of the large number of people who are now starting to be interested in investing in gold. However, this is quite a question for gold investors because of economic changes from the impact of Covid-19 and the Russia-Ukraine war. People are certainly worried, especially for those who have investments in the form of gold. The purpose of this research is to provide an analysis in the form of predictions of gold prices in 2023, an advice on managing gold in the future. The method used is the Support Vector Regression method using a polynomial kernel and supported by the Mean Absolute Percentage Error measurement. From the past research that has been done, the prediction results for gold prices in 2023 with an error value of 4.8% where this value is in the very good category. From this research, several suggestions are also given in managing gold during a recession
Support Vector Machine For Hoax Detection Ni Wayan Sumartini Saraswati; I Putu Krisna Suarendra Putra; I Dewa Made Krishna Muku; Gede Dana Pramitha
SINTECH (Science and Information Technology) Journal Vol. 6 No. 2 (2023): SINTECH Journal Edition Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i2.1366

Abstract

Along with the development of information technology, news media has also developed by presenting information online Along with the rapid development of online news, the spread of fake news information (hoaxes) is also increasing rapidly and widely. Hoax news is often spread intentionally for various purposes. Generally, hoax news aims to direct the reader's perception to believe in a bad perception of an event, character or even a company. The motivation is to invite readers to believe something that is not true with the aim of benefiting the news disseminator is something dangerous. This research aims to detect English-language hoaxes by applying the Support vector machine (SVM) algorithm. In this study, the data used are two data sources, namely English news datasets from Kaggle and English news taken from BBC. The results of this study show that the application of the SVM algorithm turns out to get good performance because the model is able to classify hoax news with an accuracy of 99.4% on Kaggle data while on the BBC news dataset the model gets an accuracy of 98.9%. This research also shows that the SVM method is proven to have good generalization properties. Where it is able to identify test data that is completely different from the training data.
Analisis Sentimen Program Mbkm Pada Media Sosial Twitter Menggunakan KNN Dan SMOTE Komang Pramayasa; I Md Dendi Maysanjaya; I Gusti Ayu Agung Diatri Indradewi
SINTECH (Science and Information Technology) Journal Vol. 6 No. 2 (2023): SINTECH Journal Edition Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i2.1372

Abstract

The Merdeka Belajar-Kampus Merdeka (MBKM) program is a relatively new program implemented in Indonesia since February 2020. Like a new program, the implementation of the MBKM program is also followed by various pro and con attitudes. Therefore, a sentiment analysis technique is needed to determine the public opinion towards the MBKM program. The purpose of this study is to determine the performance of the KNN method in performing sentiment classification optimized by the SMOTE method in overcoming the problem of unbalanced data and to determine the tendency of public sentiment towards the implementation of the MBKM program. Based on the research results, the KNN method optimized with the SMOTE method is proven to improve classification performance. From initially producing an accuracy value of 76.13%, precision of 76.03%, recall of 76.13% and f1-score of 76.01% there was an increase in accuracy value to 76.13%, precision to 76.03%, recall to 76.13%, and f1-score to 76.01%. In this study, it was found that community responses tended to be neutral towards the MBKM program. The community feels that the MBKM program is a program that can increase student experience. However, there are still program systems that are considered complicated and need to be evaluated.
Klasifikasi Penyakit Antraknosa Pada Cabai Merah Teropong ”Inko Hot” Dengan Metode Convolutional Neural Network Donny Avianto; Ilmy Eka Handayani
SINTECH (Science and Information Technology) Journal Vol. 6 No. 2 (2023): SINTECH Journal Edition Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i2.1377

Abstract

The red chili variety "inko hot" is a type of red chili that has a high economic value. Unfortunately, these red chili plants are often infected with anthracnose disease, which results in significant losses for farmers. Anthracnose is one of the major diseases infecting chili plants, potentially resulting in crop failure and losses of up to 80%. The purpose of this study is to develop a classification system to identify anthracnose disease in red chili fruit, using Convolutional Neural Network (CNN) method. In this experiment, 1500 data were used, of which 80% were used as training data and 20% as validation data. The best results of this experiment produced a model with an accuracy of 97% and a loss rate of 6.45%, by applying the Nadam optimization algorithm and going through 50 iterations (epochs). The model showed good performance with a prediction accuracy rate of 83.33%. The development of this classification system has significant potential in providing efficient solutions to recognize diseases in chili plants. Through continuous development, this system can be a valuable tool for farmers to increase crop productivity and reduce the negative impact of disease attacks on red chili peppers and other crops.
Deep Learning Berbasis CNN Untuk Pengenalan Pola Partial Discharge Isolasi Silicone Rubber Ferlian Seftianto; Sukemi Sukemi; Zainuddin Nawawi
SINTECH (Science and Information Technology) Journal Vol. 6 No. 2 (2023): SINTECH Journal Edition Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i2.1390

Abstract

Partial discharge (PD) activity measurements have been carried out by selecting noise signals (de-noising) using Support Vector Machine (SVM)and then recognized using Convolutional Neural Network (CNN). CNN testing was carried out using various models such as activation methods: Sigmoid, Softmax, Relu, Tanh, Swish. Number of layers used is 1, 2, 3, 4 with filter sizes of 32, 64, 128, 256  and kernel sizes 3x3, 2x2, 1x1, 1x2,  1x3 in the MaxPooling and AveragePooling pooling methods. The results obtained, On sigmoid method the MaxPooling and AveragePooling with  1 layers  having a low accuracy around 14.40% but the other layers configurations gets a high accuracy around 98.99% both has been done with or without de-noising. In Softmax activation method, MaxPooling pooling method has an accuracy around 84.94% and has de-noising 90.66%. The AveragePooling pooling method has an accuracy 65.25% and around 75.29% with de-noised. The result shows that SVM de-noising increases the accuracy around 11.12% in the Softmax activation method. In the Tanh, Relu, and Swish activation methods, a low level of accuracy is obtained with an average of 14.40%, and SVM de-noising doesn’t increase the accuracy, so CNN-based deep learning with SVM de-noising is more suitable using the Sigmoid and Softmax.
Pengembangan Sistem Business Intelligence Dalam Monitoring Performa Perusahaan Multi Company I Dewa Gde Deva Baskara Muku; I Putu Agung Bayupati; Anak Agung Ngurah Hary Susila
SINTECH (Science and Information Technology) Journal Vol. 6 No. 2 (2023): SINTECH Journal Edition Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i2.1394

Abstract

Multi-company companies have challenges in managing subsidiary data into performance information of all subsidiaries in one window. This is due to the variation of data dimensions according to the business processes of each subsidiary. CV. XYZ is a holding company engaged in the food & beverage business. CV. XYZ currently manages three companies consisting of restaurants, catering, and tent and decoration rental. The problem faced by the company owner is the limited access to company performance in one information window. Each company has working papers in Excel format to record expenditure and income transactions. This article proposes the development of a website-based business intelligence system to overcome the problems of CV. XYZ. The purpose of developing a business intelligence system in this article is to provide access to the performance of each subsidiary in one website media. The business intelligence system is developed through the stages of data collection and analysis, data warehouse design, ETL process, and data visualization with Microsoft Power BI. The data warehouse design uses Kimball's nine-step method which produces a data warehouse with a star scheme. The developed Business Intelligence system was tested using the UAT method. The UAT test results show that the system development is following the company's needs as indicated by the UAT score of 92%
Implementation Of A* Algorithm In A Great Elephant Game With Unity 2D Ahmad Zuhdi; Imam Ahmad; Ade Dwi Putra
SINTECH (Science and Information Technology) Journal Vol. 6 No. 2 (2023): SINTECH Journal Edition Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i2.1396

Abstract

Video game is a game play which related to interesting User Interface through a picture which processed and transmitted into a video, as it alive and moving. At early 2014, smartphone users were increased, affected to decreasing of computer users.Pathfinding is a route search method. Google maps is one example of an application which using pathfinding method. A* Algorithm through pathfinding method is the development of dijkstra algorithm using heuristic to produce best and optimum solution. So it is possible to discover fastest path without checking in every path. Therefore, the objective of this study is implementing A* algorithm in Great Elephant game. This algorithm can be implemented to the character for discovering nearest route and increase the score easily. Because of the route is in maze form, it will be time wasting to looking for any food. This algorithm help the character to not wasting time in looking for the food. The result study is a game using A* algorithm in the player game which can access in android smartphone. The test result is using ISO 25010 in functionality suitablity aspect and produced 100% success.
Implementasi K-Medoids Clustering Dalam Pengelompokkan Harga 8 Jenis Minyak Goreng Nasari, Fina; Am, Andri Nofiar
SINTECH (Science and Information Technology) Journal Vol. 6 No. 3 (2023): SINTECH Journal Edition December 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i3.1419

Abstract

In everyday life, cooking oil has become a necessity with international sales prices varying depending on the quality and type. The types of cooking oil sold in the international market are very diverse, including coconut, olive, palm kernel oil, palm oil, peanuts, rapeseed, soybeans and sunflower. Therefore, it is necessary to group data on selling prices of cooking oil on the international market to get the best grouping of cooking oil. The data used in this research is historical price data of 8 edible oils kaggle August 1992 to July 2022. Data grouping in this research uses the k-medoids algorithm. The k-medoids algorithm produces a more balanced group, better performance and accuracy than other algorithms. The aim of this research is that the k-medoids algorithm is able to group cooking oil price data into 4 group models, namely group models 2, 3, 4 and 5 and obtain the best group model based on the dbi value. The research results showed that the cooking oil price data was successfully grouped into group 2, 3, 4 and 5 models with the best group based on the lowest dbi performance value being the group 2 model with a dbi value of 0,000 and olive oil being the cooking oil with the highest price in the world while 7 types other cooking oils have more or less the same price (in the same price group).
Penerapan Metode Clustering Dalam Segmentasi Pelanggan Perusahaan Logistik Kishendrian, Hanan; Hanum, Nisa; Prianto, Cahyo; Rahayu, Woro Isti
SINTECH (Science and Information Technology) Journal Vol. 6 No. 3 (2023): SINTECH Journal Edition December 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i3.1432

Abstract

Marketing is important in business to compete and maintain market share. The development of technology brings major changes in the industry. In addition to product development as well as required services, and customer segmentation becomes a factor to consider in marketing strategies. Clustering, such as the K-Means method, is used in customer segmentation to divide data into groups based on similarities. This technique helps in useful pattern recognition and customer segmentation. By applying Clustering techniques in Data mining, companies can understand customer behavior, recognize similar customer groups, and plan marketing strategies accordingly. The results showed that the best cluster was generated with a k value of 4, and the data was normalized using the Min-Max Normalization method. Grouping customers in the form of clusters can enable the identification of consumer profiles to guide companies in decision making.

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