Telkom SOC stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Telkom's (TLK) Future Bright as Analyst's Forecast Signals Growth

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Dataset Penelitian Website Atmosphere, Perceived Flow and Its Impact On Purchase Intention

This dataset presents the comprehensive stock price history of PT Telkom Indonesia (TLKM.JK), a multinational telecommunications conglomerate from 2001 to 2023. The dataset includes daily stock prices, trading volume, and other relevant financial metrics. The stock prices are provided in IDR (Indonesian Rupiah) currency. Telkom has major business lines in fixed-line telephony, internet, and data communications. It is operated as the parent company of the Telkom Group, which is engaged in a broad range of businesses which consist of telecommunication, multimedia, property, and financial services.

Dataset Variables:

Date: The date of the stock price data. Open Price: The opening price of the bank's stock on the given date. Close Price: The closing price of the bank's stock on the given date. High Price: The highest price reached by the bank's stock during the trading day. Low Price: The lowest price reached by the bank's stock during the trading day. Adjusted Low Price: The closing price on a given trading day, adjusted to reflect any corporate actions, such as stock splits, dividends, rights offerings, or other adjustments that may affect the stock price. Volume: The number of shares traded on the given date.

Data Sources: The dataset is compiled from reliable financial sources, including stock exchanges, financial news websites, and reputable financial data providers. Data cleaning and preprocessing techniques have been applied to ensure accuracy and consistency. More info: https://finance.yahoo.com/quote/TLKM.JK/history/

Dataset

This dataset was created by AJENG YUGO PANGESTU

Contents

Dataset

This dataset was created by m4rvel

Contents

The usage of online marketplace in Indonesia increases due to Covid-19 pandemic and its supporting environment such as payment systems. This investigation was conducted to determine the effect of Website Quality on Online Impulsive Buying Behavior moderated by Sales Promotion and Credit Card Usage in Indonesian marketplace. This study uses quantitative methods with causal analysis. In this research, data was collected through online questionnaires and 275 respondents who used the marketplace website responded. This research uses PLS-SEM data analysis technique. The results of this study showed that three out of five hypotheses are accepted. This study shows that Website Quality, Credit Card Use, and Sales Promotion have positive significant effect on Online Impulse Buying Behavior. However, the result of this study also revealed interesting findings, that there is not enough evidence to support moderation effect of Credit Card use and Sales Promotion in the relationship between web quality and Online Impulse Buying Behavior.

Explore the historical Whois records related to telkom.org (Domain). Get insights into ownership history and changes over time.

The transportation sector is one of the largest contributors to the greenhouse effect. This causes consumers and industry to look for solutions to reduce the greenhouse effect, one of them is an Electric Vehicles (EV). EV is considered as one of the responses to reduce the use of oil energy and carbon emissions from the transportation sector. However, the EV success depends on the level of people's need for EV. Maslow's hierarchy of needs is widely used to understand consumer buying motivation and consumer buying behavior. This study aims to determine EV Purchase Motivation in Indonesia by using Maslow's Hierarchy of Needs approach. Questionnaires from 385 respondents were then analyzed using multiple linear regression models. Based on the research, the Openness to Experience variable has the most significant effect on EV Purchase Motivation, followed by Environmental Concern, Price Consciousness, and Self Esteem. Meanwhile, the Social Influences variable has a negative and insignificant effect on EV Purchase Motivation.. From a practical point of view, there are several useful recommendations for the government to formulate and implement to determine vehicle electrification and also advice to automotive marketers and manufacturers regarding the motivation of Indonesian consumers for EVs. Keywords: electric vehicles; purchase motivation; Maslow hierarchy of needs.

In financial year 2024, PT Telkom Indonesia (Persero) Tbk's total data, internet and SMS revenue was about 94 trillion Indonesian rupiah. Telkom Indonesia is the largest telecommunication and network provider in Indonesia. The company offers a wide range of network and telecommunication services, including fixed-line connection services, cellular services, network and interconnection services, as well as internet and data communication services.

The Kenyan telecommunications market, valued at $3.79 billion in 2025, exhibits a steady growth trajectory, projected to expand at a compound annual growth rate (CAGR) of 2.24% from 2025 to 2033. This growth is fueled by increasing smartphone penetration, rising data consumption driven by the popularity of mobile money services like M-Pesa, and the expansion of 4G and 5G networks across the country. The market is highly competitive, with major players like Safaricom, Airtel Kenya, Telkom Kenya, and Equitel vying for market share. Growth in the data and messaging services segment is expected to be a significant driver, surpassing voice services in terms of revenue contribution in the coming years. The increasing adoption of Over-The-Top (OTT) services, such as streaming platforms and VoIP applications, also presents both opportunities and challenges for traditional telecom operators, forcing them to adapt their offerings and invest in network infrastructure to support higher bandwidth demands. Regulatory changes and government initiatives aimed at promoting digital inclusion also play a significant role in shaping the market's future. However, challenges remain, including the need for continued investment in network infrastructure to expand coverage and improve quality of service, particularly in rural areas, and the competitive pricing pressures within the market. The segment breakdown reveals a dynamic landscape. Voice services, while still substantial, are predicted to experience slower growth compared to data and messaging. The rapid uptake of mobile internet and the convenience of data-based communication is driving this shift. The OTT and PayTV segment is expected to witness significant expansion, fueled by the rising demand for entertainment and media content. This growth is not without its challenges, however. Competition among OTT providers and the potential for increased regulation will influence the long-term growth trajectory of this segment. The success of Kenyan telecom companies will hinge on their ability to innovate, adapt to evolving consumer needs, and invest strategically in infrastructure and services to capitalize on emerging opportunities. The market's future growth will depend on sustained economic development and continued government support for the expansion of digital infrastructure across the country. Recent developments include: October 2024: Safaricom has expanded its M-PESA Global service to include Ethiopia, enabling users to transfer mobile money from Kenya to Ethiopia. With this growth, the two companies strive to enhance the utilization and reach of mobile money in Ethiopia, which can help stimulate local economies and provide new prospects for people and businesses in the area. This partnership reflects our dedication to providing creative financial options that meet the changing demands of our clients.September 2024: Axian Telecom was reportedly looking to acquire Kenya-based mobile, internet and TV provider Wananchi Group., The Standard reported according to files made with regulator Comesa Competition Commission, Axian Telecom subsidiary Axian Telecom Fibre is looking to acquire 99.63% of Wananchi. It trades under the Zuku brand offering TV, broadband and mobile across Kenya, Tanzania, Uganda, Malawi and Zambia.. Key drivers for this market are: Rising demand for 4G and 5G services, Growth of IoT usage in Telecom. Potential restraints include: Rising demand for 4G and 5G services, Growth of IoT usage in Telecom. Notable trends are: The Demand for 4G and 5G Services is Rising.

data hasil kuesioner

This study aims to provide new learning from consumer behaviour viewpoints by understanding the effects of gender and age on consumer purchase intentions and purchase behaviours, specifically in the context of e-commerce in Indonesia, by developing a hypothetical structural model that comprises nine motivational factors: convenience, perceived website quality, social influence, facilitating conditions, hedonic motivation, economic reasons, security, variety and delivery.

This dataset is artificially generated. It contains container transport data consisting of origin, destination, start time window (in hours), end time window (in hours), time window duration, start time window (in minutes), and end time window (in minutes). The dataset is generated using the following settings: 1. Five locations (terminals) 2. Min. due date = 2, Max. due date = 24 3. Number of trucks = 10 4. Throughput per 6 hours = 7 containers 5. The container movement rate based on: http://dx.doi.org/10.13000/JFMSE.2017.29.2.354

Sales Dataset from Puri Utami

List of Digital Marketing and SME Papers

The pandemic COVID-19 makes Indonesians accustomed to doing various activities from home including shopping. Livestreaming shopping can attract higher purchase intentions than the usual way of selling. The current research aims to determine the influence of consumer perceived value on the purchase intention of Live services with the mediation of customer engagement. The population consisted of Indonesians who watched live streams on Live Shopping feature and interacted with streamers on live streaming. Using the targeted sampling method and calculation of percentage estimates, the minimum number of respondents for this study was 385. The research uses SEM-PLS to analyze data collected. The results of the study indicate that not all perceived value variables are significant to purchase intention. In addition, the mediating impact of customer engagement only mediates through perceived individual and social value. This research provides insight for online shop that use live streaming to attract buyers, especially local consumers in Indonesia.

Dataset contain topic in garuda.kemdikbud.go.id website from 2016 until 2021

Shrimptector

## Overview

Shrimptector is a dataset for object detection tasks - it contains Benur Udang annotations for 457 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Personality dataset