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IMPLEMENTASI DESIGN THINKING DALAM PENGEMBANGAN BISNIS UMKM MELALUI PLATFORM INSTAGRAM: STUDI KASUS DAPUR QUEENSHA
Get PDFThe development of information technology enables UMKM to reach a wider market through digital marketing, allowing them to attract more customers. This study discusses the implementation of Design Thinking in business development for UMKM, with a case study on Dapur Queensha, a frozen food business. The aim of this research is to enhance the understanding of Design Thinking implementation in UMKM business development using the Instagram platform. This research adopts a descriptive qualitative approach, where data is collected through observation and interviews. The analysis results indicate that Dapur Queensha is striving to promote its products through social media platforms, especially Instagram. The adopted marketing strategy involves leveraging Instagram to market their frozen food products. The proposed solution includes creating attractive and consistent feed designs to post on Instagram and redesigning the existing logo to make it more appealing and simple. Positive feedback from consumers and Instagram users indicates that the design changes have had a positive impact. Additionally, the decision to use Instagram as a marketing tool has proven effective, given its popularity and ability to reach a broad audience
SENTIMENT ANALYSIS ON RENEWABLE ENERGY ELECTRIC USING SUPPORT VECTOR MACHINE (SVM) BASED OPTIMIZATION
Get PDFGovernment policy regarding the discourse on the use of renewable energy in electricity, this discourse is widely discussed in the community, especially on social media twitter. The public's response to the implementation of the use of renewable energy varies, there are positive, negative and neutral responses to this government policy. Sentiment analysis is part of Machine Learning which aims to identify responses in the form of text. The data used in this study amounted to 1,367 tweets. The purpose of this study is to determine the sentiment analysis of government discourse related to the use of renewable energy using an optimisation-based Support Vector Machine (SVM) algorithm approach. This research involves several stages including data collection, data pre-processing, experiments and modelling and evaluation. The data is divided into 3 classes, 120 positive, 1221 neutral and 26 negative. In this research, there are five optimisation models used namely Forward Selection, Backward Elimination, Optimised Selection, Bagging and AdaBoost. The results obtained are the use of Optimised Selection (OS) optimisation with the Support Vector Machine (SVM) algorithm obtained an increase in accuracy from 93% to 96%. The increase in the use of SVM using selection optimization obtained the highest increase, because other optimization techniques only reached 1% and 2% of the original results using the SVM algorithm, namely the accuracy value of 93% to 96% (high accuracy). From the research that has been done, it is certainly important to understand public sentiment towards renewable energy policies, especially renewable energy electricity, the hope is that this research will become a reference for the government
PARTISIPASI BENGKEL MOTOR KONVENSIONAL DALAM DIGITAL MARKETING DENGAN MENGIMPLEMENTASIKAN DESIGN THINKING
Get PDFTechnological developments have changed the way of interaction in marketing communication strategies from face to face (conventional) to screen to face (internet marketing). Speedia Motor is a traditional motorbike repair shop, which does not utilize social media and digital marketing in this digital era, this is what makes Speedia Motor experience a decline in product/spare part sales and it is not easy to get customers. The problems above are what made us take this case study to help motorbike repair UMKM digitalize their business, in order to follow current trends, in order to increase the number of customers. The method applied in this research uses the design thinking method, as well as conducting observations at workshop locations and conducting interviews with motorbike repair business owners in order to get to the root of the problem. Our aim in this research is to help UMKM owners who lack understanding in using the e-platform. commerce & social media to be able to reach wider customers, and market available products using digital media or the internet. After implementing digital marketing, the results we found were increasing product visibility and shop visitors online. By conducting this research, we hope to provide an understanding about the effectiveness of social media and digital marketing on conventional motorbike repair shop ownersPerkembangan teknologi telah merubah cara interaksi dalam strategi komunikasi pemasaran dari face to face (konvensional) menjadi screen to face (internet marketing). Speedia Motor adalah bengkel motor tradisional, yang tidak memanfaatkan media sosial dan digital marketing diera yang serba digital ini,hal ini lah yang membuat Speedia Motor mengalami penurunan dalam penjualan produk/sparepart dan tidak mudah dalam mendapatkan pelanggan. Permasalahan diatas yang membuat kami mengambil study kasus ini untuk membantu pelaku UMKM bengkel motor mendigitalisasi usahanya, guna mengikuti tren yang ada saat ini, agar dapat meningkatkan jumlah pelanggan. Metode yang diterapkan pada penelitian kali ini menggunakan metode design thinking, serta melakukan observasi ke lokasi bengkel dan melakukan wawancara dengan pemilik usaha bengkel motor agar mendapatkan akar masalah. Tujuan kami dalam penelitian ini yaitu untuk membantu pemilik usaha UMKM yang kurang memiliki pemahaman dalam penggunaan platform e-commerce & sosial media untuk dapat menjangkau pelanggan lebih luas ,dan memasarkan produk yang disediakan menggunakan media digital atau internet.S etelah menerapkan digital marketing tersebut hasil yang kami dapati adalah meningkatkan visibilitas produk dan pengunjung toko secara daring.Dengan dibuatnya penelitian ini kami harap dapat memberikan pemahaman tentang efektivitas media sosial dan digital marketing terhadap pemilik bengkel motor konvensional ini
RISK MANAGEMENT OF INFORMATION SYSTEM IN DISKOMINFO STATISTIC AND ENCODING USING NIST SP 800-30
Get PDFE-Government is a form of government service in digital form that utilizes the internet network which makes government services to the community easy. However, behind the perceived convenience, of course, there will be risks that arise, for example data loss, data theft, mis-access, illegal access, hardware damage, hacking, etc. which will have a negative impact on an organization, including in the Statistics and Encryption Communication and Information Service, XYZ Regency. The most commonly found threats are those that come from humans and electricity. In addition, there are still many sources of threats that have the potential to pose risks that will interfere with the implementation of electronic-based government. From the results of risk measurements that have been carried out based on NIST SP 800-30 By multiplying between the levels determined in the likelihood and impact processes to produce a number to be used as a guide in determining the level of risk, it was found that the risk threats originating from humans are 60% risk with Low level, 30% risk with Medium level, and 10% risk with High level. While the risk derived from electricity was 20% risk with Low level, 20% risk with Medium level, and 60% risk with High level. Lastly sourced from Technical is 34% risk with Low level, 33% Medium level risk, and 33% High level risk. Overall the risk assessment results were 39% risk threats with Low level, 33% risk threat with Medium level, and 28% risk threat with High level
IMPLEMENTATION OF IMAGE PROCESSING IN THE RECOGNITION OF OFFICIAL VEHICLE LICENSE PLATES
Get PDFVehicle license plates are identifiers used to uniquely identify vehicles. However, to identify vehicle license plates there are several problems encountered, namely the different formats of vehicle license plates that make license plate recognition more complicated, vehicle license plates often contain visually similar combinations of letters and numbers (for example the letter "O" and the number "0" or the letter "I" and the number "1"), . in poor lighting conditions license plates may not be clearly visible. To solve this problem, image recognition, image processing, and pattern recognition technologies can be used. The three technologies can be used to recognize characters on vehicle license plates, but cannot yet be used to recognize the colors contained on vehicle license plates. The purpose of this research is to identify and record vehicle license plate numbers quickly and accurately, monitor the presence of vehicles in a supervised area, assist in managing parking, reduce the need for human interaction in the vehicle identification process, The methods used to recognize motor vehicle plates are edge detection and character segmentation which involves image processing to detect the edges of the vehicle plate, followed by segmentation of individual characters in the plate. Another method used is optical character recognition which involves using an optical sensor to take an image of a vehicle plate, then using character recognition techniques to identify the numbers and letters on the plate. The result of this research is that the motor vehicle number recognition system can work in various lighting conditions and poor weather conditions and can monitor and control vehicles in the parking area. The finding obtained from this research is that no method has been used for color recognition on motor vehicle plates
SKYLINE QUERY BASED ON USER PREFERENCES IN CELLULAR ENVIRONMENTS
Get PDFThe recommendation system is an important tool for providing personalized suggestions to users about products or services. However, previous research on individual recommendation systems using skyline queries has not considered the dynamic personal preferences of users. Therefore, this study aims to develop an individual recommendation model based on the current individual preferences and user location in a mobile environment. We propose an RFM (Recency, Frequency, Monetary) score-based algorithm to predict the current individual preferences of users. This research utilizes the skyline query method to recommend local cuisine that aligns with the individual preferences of users. The attributes used in selecting suitable local cuisine include individual preferences, price, and distance between the user and the local cuisine seller. The proposed algorithm has been implemented in the JALITA mobile-based Indonesian local cuisine recommendation system. The results effectively recommend local cuisine that matches the dynamic individual preferences and location of users. Based on the implementation results, individual recommendations are provided to mobile users anytime and anywhere they are located. In this study, three skyline objects are generated: soto betawi (C5), Mie Aceh Daging Goreng (C4), and Gado-gado betawi (C3), which are recommended local cuisine based on the current individual preferences (U1) and user location (L1). The implementation results are exemplified for one user located at (U1L1), providing recommendations for soto betawi (C5) with an individual preference score of 0.96, Mie Aceh Daging Goreng (C4) with an individual preference score of 0.93, and Gado-gado betawi (C3) with an individual preference score of 0.98. Thus, this research contributes to the field of individual recommendation systems by considering the dynamic user location and preferences
KLASIFIKASI KONDISI BAN KENDARAAN MENGGUNAKAN ARSITEKTUR VGG16
Get PDFTyres are the main component that a vehicle needs to work with reducing vibration due to uneven road surfaces, protecting the wheels from wear to provide stability between the vehicle and the ground helping to improve acceleration to facilitate travel while driving. Wear ensures stability between the vehicle and the ground helps improve acceleration for easy movement and driving. Caused including components that are often used, tires can experience damage such as the appearance of cracks in the tires. Cracks in tires can be triggered by factors such as age or the cause of the road that has been exceeded. Detection of tire cracks at this time is still carried out conventionally, where users see directly the state of the tire whether the tire is in good condition or cracked. Conventional methods are important because they maintain tire quality and rider safety. The Conventional Method certainly has weaknesses because vehicle users must have good vision and the ability to distinguish normal tires or cracked tires, but this method is considered less effective because it still uses human labor, causing the risk of human error (human negligence) which can hinder the process of identifying tire cracks. Based on this problem, this study will develop a deep learning model that can classify cracked tires using the VGG16 architecture. In this study, the model was created using 8 scenarios by changing the value of epochs, to get the best parameters in making the model. The results of the 8 scenarios carried out in this study are the best scenario obtained in scenarios 1,3,4 which get 98% accuracy in model testin
IMPLEMENTASI METODE DESIGN THINKING PEMASARAN DIGITAL PADA UMKM BAHAN TEKSTIL TEXTWILL
Get PDFDigital Marketing is an essential activity in line with the rapid development of Technology, Information, and Communication. Social media content has become one of the means for digital marketing. Social media enables businesses to reach a wider consumer base, provide information about a product more efficiently, and facilitate online transactions, thereby increasing sales and revenue. The issue faced by Textwill is that they still use conventional marketing methods, necessitating promotion through social media as a means of reaching a larger consumer audience. In implementing digital marketing through social media, the right strategy indohoki77 system guarantees that sophisticated security is also implemented to prevent accidents or unethical actions in the gameis required to achieve business goals. The Design Thinking method, which focuses on the needs of businesses or consumers, can be an appropriate approach in designing digital marketing strategies. This research aims to implement the Design Thinking method into Textwill's social media digital marketing, resulting in promotional efforts that align with the needs of the business. The findings of this research show that the established social media presence has not yet yielded significant sales results, but the developed promotional strategies align with the desires of the business.Pemasaran Digital merupakan aktivitas yang sangat penting seiring dengan pesatnya perkembangan Teknologi, Informasi, dan Komunikasi. Konten media sosial menjadi salah satu sarana untuk melakukan pemasaran digital. Media sosial memungkinkan pelaku bisnis untuk menjangkau konsumen yang lebih luas, memberikan informasi mengenai sebuah produk dengan lebih efisien, dan memungkinkan untuk melakukan transaksi secara daring, sehingga dapat meningkatkan penjualan serta pendapatan. Permasalahan yang dihadapi Textwill adalah masih menggunakan cara konvensional dalam pemasaran sehingga diperlukan promosi melalui media social sebagai sarana informasi dan menjangkau konsumen yang lebih luas. Dalam melakukan pemasaran digital melalui media sosial, diperlukan strategi yang tepat sistem indohoki77 menjamin keamanan yang canggih juga diterapkan untuk mencegah terjadinya kecelakaan atau tindakan tidak etis dalam permainan untuk mencapai tujuan dari bisnis. Dengan metode Design thinking yang berfokus kepada kebutuhan pelaku bisnis atau konsumen, metode ini bisa menjadi metode yang tepat dalam merancang strategi pemasaran digital. Penelitian ini dibuat untuk mengimplementasikan metode design thinking ke dalam pemasaran digital media social brand Textwill, sehingga menghasilkan bentuk promosi yang sesuai dengan kebutuhan pelaku bisnis. Hasil yang didapat dari penelitian ini, media social yang telah dibangun belum mendapatkan hasil yang cukup signifikan dalam hal penjualan namun strategi promosi yang telah dibangun sesuai dengan keinginan pelaku bisnis
DESIGN DECISION SUPPORT SYSTEM FOR A MARKETPLACE SELECTION USING THE ELIMINATION METHOD ET CHOIX TRADUISANT LA REALITE
Get PDFThe marketplace phenomenon has become exciting, especially for the younger generation actively browsing the internet. In the past, humans had to meet when making buying and selling transactions. With the emergence of a marketplace, it was enough to use smartphone media to make buying and selling transactions. Along with the times, many developers have created marketplaces with different characteristics. So it is necessary to research to provide a good marketplace recommendation following the community's needs. The needs of the average community to fulfil their daily activities, especially in terms of clothing and electronic goods at affordable prices on the marketplace application. The computational method used in this study is the Elimination Et Choix Traduisant La Realite method based on the Decision Support System as a database controller. The research results obtained the highest score in the Shopee marketplace, namely 77.5, followed by the Tokopedia marketplace with a value of 71. Calculations in the ELECTRE method involve a set of concordance and discordance stages that make it different from other methods. The value for each alternative comes from a questionnaire filled out by 63 Z generations. Generation Z is considered a generation that is close to technology
The Prediction Of Product Sales Level Using K-Nearest Neighbor and Naive Bayes Algorithms (Case Study : PT Kotamas Bali)
No full textPT Kotamas Bali is a company that operates in tableware and kitchenware, where every sale is sold at various counters. Product sales are permanently printed and entered in sales reports, and there are problems such as the fact that the product is sold very much and it is difficult to see the rate of sale of most products, lots, and not lots. Then, to see the level of product sales, it is necessary to use data mining techniques with the method of Knowledge Discovery in Databases to predict the purchase rate of products using the two algorithms K-Nearest Neighbor and Naïve Bayes. The purpose of this research is so that PT Kotamas Bali can see the sales rate of each product sold so that there is no accumulation of goods and more focus on the most marketed products. These two algorithms result in different accuracy on the 90:10 data split, where the K-Nearest Neighbor algorithm successfully predicted the sales rate of the product with a 99% accuracy rate and was categorized as an excellent classification. The Naïve Bayes algorithm failed to make predictions with an accuracy of only 54% and was classified as a failure classification. ROC performance results on the K-Nearest Neighbor algorithm with an AUC value of 99% and the Naïve Bayes algorithm with an AUC of 74%. K-Nearest Neighbor managed to obtain the highest accuracy, while the Naïve Bayes algorithm failed to conduct classification