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PERAN LOKASI DAN STRATEGI PENJUALAN DALAM MENSTABILKAN PENDAPATAN UMKM: STUDI KASUS RUMAH MAKAN PADANG
Get PDFPadang restaurants are one of the micro, small, and medium enterprises (MSMEs) offering a variety of typical Minangkabau cuisine from Padang, West Sumatra. In the capital city of Jakarta, there are many Padang restaurant MSMEs with tight competition and various sales methods. Each Padang restaurant has different incomes, depending on its sales strategy and competitiveness in the market. To compete and maintain its income, business owners must have an effective sales strategy. This study aims to understand how the location of the business, sales strategies, and income variations affect the performance of Padang restaurant businesses. The subject of this research is the Padang Restaurant Ampera Saiyo Tipar Cakung. Data collection methods were carried out through field research, direct observation, interviews with owners and employees, and collection of related business documents. The collected data were analyzed using a qualitative case study approach. The observation results show that at the location of Padang Restaurant Ampera Saiyo, there are also two other competitors. When one competitor is not operating, customers tend to switch to Ampera Saiyo restaurant, and vice versa. The problem often faced by Padang Restaurant Ampera Saiyo is income instability. The factors influencing this instability are competition among Padang restaurants. To overcome this challenge, one of the sales strategies applied is to utilize digital marketing, such as GoFood and GrabFood, to expand market reach and increase visibility of Padang Restaurant Ampera Saiyo among potential customers
KAJIAN KEPUTUSAN PEMBELIAN KONSUMEN DI E-COMMERCE: STUDI PADA ERIGO STORE
Get PDFThe use of e-commerce in Indonesia has grown very rapidly and continues to increase. Erigo Store has become one of the leading e-commerce platforms in Indonesia. This study aims to analyze the factors influencing purchase decisions at Erigo Store. This research uses a qualitative method through interviews and observations. The research sample consists of 27 key respondents who are Erigo Store consumers. The results of this study indicate that Indonesian e-commerce consumers tend to look for quality products at affordable prices. Positive reviews from other consumers also become an important factor that can increase consumer trust and encourage them to make purchases. This research provides valuable insights for business owners and marketers in the e-commerce market. These findings affirm that companies need to understand the importance of maintaining a balance between price and product quality to enhance consumer appeal and trust
ACTIVATION FUNCTION IN LSTM FOR IMPROVED FORECASTING OF CLOSING NATURAL GAS STOCK PRICES
Get PDFThe closing price of natural gas stocks greatly influences investment decisions and the energy industry. Predicting prices correctly can greatly help investors, market participants, and all parties involved, as it allows for making better decisions and optimizing investment portfolios. By using deep learning methods to role model various LSTM activation functions, such as Sigmoid, ReLU, and Tanh, this exploration will hopefully help understand complex patterns in time series data. By finding an appropriate forecasting method, all parties involved can reduce the environmental impact. The experimental results show that the model with ReLU activation function has the highest R2 value of 0.960 in both the training and test sets, and the model with Tanh activation function is also successful, with R2 values of 0.950 in the training set and 0.949 in the test set, and an MSE of 0.002. The model with the sigmoid activation function was slightly lower, with R2 values of 0.931 in the training set and 0.943 in the test set, and an MSE of 0.003. These findings indicate that the LSTM model with the ReLU activation function is considered better for predicting the closing price of natural gas stocks. These findings may help investors, stakeholders, and market participants choose the most accurate model to predict the closing price of natural gas stocks
PERFORMANCE OF ROBUST SUPPORT VECTOR MACHINE CLASSIFICATION MODEL ON BALANCED, IMBALANCED AND OUTLIERS DATASETS
Get PDFIn the realm of machine learning, classification models are important for identifying patterns and grouping data. Support Vector Machine (SVM) and Robust SVM are two types of models that are often used. SVM works by finding an optimal hyperplane to separate data classes, while Robust SVM is designed to deal with uncertainty and noise in the data, making it more resistant to outliers. However, SVM has limitations in dealing with class imbalance and outliers in the dataset. Class imbalance makes the model tend to predict the majority class, and outliers can interfere with model formation. This research compares the performance of SVM and Robust SVM on normal, unbalanced and outlier datasets. The software uses Python and Scikit-learn for implementation and comparison of the two models. Key features include automatic data preprocessing, model training, and evaluation with metrics such as accuracy, precision, recall, and F1 score. The results show that Robust SVM is superior in accuracy on normal datasets and is very effective in dealing with class imbalance, achieving a maximum accuracy of 100%. On datasets with outliers, Robust SVM maintains stable accuracy, demonstrating its robustness to outliers. This research contributes to correspondence management by providing more reliable classification models, improving data processing accuracy, and supporting more informed decision making in software developmen
IMPLEMENTING RETRIEVAL-AUGMENTED GENERATION AND VECTOR DATABASES FOR CHATBOTS IN PUBLIC SERVICES AGENCIES CONTEXT
Get PDFRapid developments in information technology, such as chatbots and generative artificial intelligence, have drastically lowered the cost of providing services to the society. This study aims to measure performance of developed chatbot using retrieval augmented generation and vector database. This research compares the performance of existing Large Language Modelling (LLM) in answering questions related to regulations concerning public service agencies.. Using a vector database, questions are assessed and answered by the LLM model, considering cosine similarity scores. The best-performing model, gpt-4, is selected for the deployment process which have average cosine similarity score 0,404. The use of LLM for chatbot creation at the prototyping stage can provide a good response to the question asked related to public service agencies with retrieval augmented generation (RAG) process through regulation-based document extraction
ANALISA DAN PERANCANGAN UI/UX APLIKASI PENJUALAN BESI BETON MENGGUNAKAN METODE DESIGN THINKING
Get PDFThe world of technology today greatly affects human life. Technological advances, especially in the field of information technology, are increasing every year. PT Sumber Jaya Maju Gemilang provides a variety of reinforced concrete products to meet the needs of different consumers for projects, factories, and other construction. During the sales process, it is still done manually, which hinders business because it takes a lot of time and causes errors in processing and reporting transaction data. Because of these problems, a new design for the Sales of Reinforced Concrete website must be designed using the design thinking method. The purpose of this study is to assist in creating sales applications that meet user needs and improve user experience. The results of the study show that the empathy stage, namely determining and observing previous cases, one of the problems that can be concluded from the empathize process is the company's low level of awareness of their service users. In the previous stage, the idea was to create an application that could handle the problems of people who wanted to order iron and delivery of goods but did not have much time or did not want to queue for a long time. At this stage, the prototype must rearrange the flow of iron sales and delivery of goods so that it is easier, and create a pattern for creating features in the application. In the final stage, the application trial process is carried out using the digital prototype in the Figma Application.
 
SISTEM INFORMASI POS PELAYANAN TERPADU BERBASIS WEBSITE MENGGUNAKAN METODE EXTREME PROGRAMMING
Get PDFThe problem in this research is that the technical notification of Posyandu schedules is still done verbally by word of mouth among the community and is also only announced via loudspeakers at local mosques. This method makes the dissemination of information related to the Posyandu schedule less effective. The main problem that often arises is that there are still parents who don't know the Posyandu schedule, there are even parents who forget the Posyandu schedule. The aim of this research is to make it easier for cadres to convey information and make it easier for parents to receive information about posyandu activity schedules via WhatsApp Blast. This research uses the Extreme Programming method which consists of 4 stages, namely planning, designing, coding and testing. Extreme Programming is a method that is considered effective in its application because it can produce a system that is fast and responsive to changing needs. The result of this research is a posyandu information system based on WhatsApp Blast which was created based on extreme programming stages. Functional testing using the Black Box method shows that the system has met expectations
PEMBUATAN DAN PELATIHAN SISTEM INFORMASI SEBAGAI UPAYA PENINGKATAN KINERJA DC MALL BATAM
Get PDFDigital transformation in Industry 5.0 has become a driving force in moving companies to improve the quality of services provided to customers and ease of work. The company's needs in carrying out strategic work and policies cannot be separated from the use of systems to help manage company data. DC Mall rents out its locations to parties such as shopping centers, supermarkets, exhibition corridors, restaurants and electronics stores. One of the routine tasks in managing DC Mall is paying utilities and rent for each unit. Payments are made to the mall management every month. Efforts to develop an information system that can cover all parts of mall management, including finance, customer service, marketing and others. The aim of this activity is to implement an information system at DC Mall that is beneficial for employee and company performance. The new system is designed to cover the weaknesses of the previous system. This service activity, which includes observation, data collection, design, implementation and evaluation, was carried out for approximately three months, starting from November 10 to January 19 2024. Each member is responsible for making observations, surveying locations, collecting data, helping create information systems and training employees, and compiling service reports. Based on the results of the service, it can be concluded that the creation of the new DC Mall information system has been successful based on feedback from employees in operating and carrying out their duties
CLUSTERING OF POPULAR SPOTIFY SONGS IN 2023 USING K-MEANS METHOD AND SILHOUETTE COEFFICIENT
Get PDFThe rapid advancement of technology and globalization in this era has brought about comprehensive and easily accessible music streaming services, one of which is Spotify. According to Kompas.com, Spotify has experienced a rise in subscribers up to 130 million, as a platform that offers various features besides music streaming. Spotify also provides a better user experience and has the ability to compete with other music streaming platforms. The mission of this research is to classify popular Spotify song data in 2023, which can aid in a deeper understanding of listener preferences or music trends. Based on the test results, there were 2 clusters obtained with cluster 0 containing 863 data and cluster 1 containing 90 data. From the testing results conducted in the K-Means analysis, a Silhouette Coefficient of 0.81 was obtained, which falls into the category of Strong Structure. From these results, it can be suggested that cluster formation was done very well to provide more personalized and relevant music recommendations to Spotify platform users. By understanding the preferences and patterns of listeners revealed through clustering, streaming services can enhance user experience by providing more tailored content
EVALUATION OF IT GOVERNANCE USING COBIT 2019 ON REGIONAL ASSET MANAGEMENT AGENCY OF DKI JAKARTA
Get PDFAn adequate level of IT availability can obtained by implementing IT Governance, which pay attention to all related issues service readiness, including services and resources. This research aimed to assess the IT Governance capability at the Regional Asset Management Agency (BPAD), a government institution responsible for asset management. The study specifically focused on issues related to data and information management, including leadership and risk management challenges. Using the COBIT 2019 Framework, data were collected through interviews and observations. The respondent of this research are 4 who work in the Data and Information Sub-Sector and one Head of Asset Administration. The findings revealed that the EDM 05 process achieved a capability level of 4, surpassing the organization's target. However, the APO 08 and APO 12 processes were rated at level 2, highlighting areas in need of improvement. The study provides recommendations to enhance BPAD's performance and optimize its business activities