Unlock the meaning in your Indonesian data

Our AI-driven Indonesian sentiment analysis API determines the sentiment in your Indonesian text. All analysis is done natively in Indonesian, leading to greater accuracy.

Your Indonesian Sentiment Analysis Company

Repustate's sentiment analysis API is powered by Indonesian natural language processing (NLP). It analyzes Indonesian data natively, without the need to translate any document into English, thus, giving more accurate and meticulously useful insights.

Table of Contents:

  1. Indonesian Sentiment Analysis API
  2. Benefits of Repustate's Indonesian Sentiment Analytics
  3. Why Choose Repustate Over Others?
  4. Basic Steps in Indonesian Sentiment Analysis
  5. Applications of Sentiment Analysis Tools
  6. Real-World Indonesian Sentiment Analysis Examples
  7. Indonesian Enterprise Search

Indonesian Sentiment Analysis API

Repustate's Indonesian sentiment analysis solution is made dedicatedly for the Indonesian-speaking world. The tool can be used to analyze data from any Indonesian source such as news, social media, blogs, reviews, and surveys.

The solution has its own dedicated Indonesian part-of-speech tagger, Indonesian lemmatizer, and Indonesian-specific sentiment models. It also understands colloquial words and industry jargon. Indonesian natural language processing, coupled with named entity recognition (NER), helps it identify topics and themes in the data for more granular sentiment analysis, leading to key business insights.

See Repustate's Indonesian sentiment analysis in action

What are the benefits of Repustate's Indonesian Sentiment Analytics Tool?

The Repustate Indonesian Sentiment Analysis solution is made specifically for Indonesian data. It is highly customizable and can be calibrated to be an exact fit for your business. Listed below are the main advantages of the tool:

  • Understand your Indonesian speaking customers
  • Visualize all the insights in a customer insights dashboard
  • Obtain granular Indonesian sentiment analysis by aspect
  • Data security with on-premise deployment or through Cloud
  • Custom-made model that can be specific to your brand and industry domain
  • Multilingual sentiment analysis capability to help you scale globally fast

Why Choose Repustate Over Others?

The Repustate model has the highest accuracy in NER compared to other tools. It is not an off-the-shelf product, but a highly personalized, scalable solution with dedicated customer support. Here is why our clients worldwide (NA, EMEA and Asia Pacific) collaborate with us.

  1. Premium Support: As our client, you will have a dedicated engineer assigned to your account.
  2. Technology: We apply artificial intelligence and machine learning to Indonesian natural language processing for the best results.
  3. Indonesian Text: We never translate. Repustate has unique speech taggers and sentiment models made just for Indonesian text analysis. In fact, each of our 23 languages has an ML model based on the natural language natively.
  4. Accuracy: Our aspect-driven approach to sentiment is granular, accurate, and targeted.
  5. Speed: Our API can process 1,000 comments per second.
  6. Customizable: We custom-build the model to capture your most important aspects and topics.
  7. Scale: Our API can easily scale from 1 to 10 million to 100 million documents and beyond.
  8. Integration: The Repustate solution integrates seamlessly with your existing technology. You do not need 3rd party support for any underlying technology.
  9. Competition: Our model is the most accurate in NER compared to the competition that includes Google, Amazon, and Microsoft. Check out our comparison.
  10. Deployment Flexibility: We offer both, a Cloud model, and an on-premise installation for data security, in a one-click solution.
  11. No Hidden Fees: Our pricing includes support, updates, training, and deployment.
  12. Iterative: Our models get more and more intelligent with training and as they process more data.

Indonesian Language Sentiment Models

Repustate has developed sentiment language models specific to Indonesian to capture the various phrases, idioms, and expressions that help define certain sentiments. It turns unstructured Indonesian data into business intelligence you can use to increase your value proposition, brand experience, and value delivery.

Take a quick tour of Repustate's Indonesian text analytics solution

What are the Basic Steps in Indonesian Sentiment Analysis?

Repustate has a massive corpus of Indonesian text that has been tagged manually, as the first step towards Indonesian sentiment analysis. This corpus is then processed by an ML model for high precision in aggregate sentiment scoring. The steps can be laid out as:

  1. Collect a massive, highly varied corpus (collection of texts) of the manually tagged Indonesian text.
  2. Feed this text into an ML-based algorithm to create an Indonesian part-of-speech tagger.
  3. Granulate the algorithm for deeper accuracy using NER.
  4. Extract the sentiment score for each aspect, theme, and topic.

Repustate uses Indonesian Named Entity Recognition (NER) with advanced semantic search to identify brand and business entities in data. No matter how misspelled a word is, the Indonesian NLP model will reproduce the name in the native script and give accurate name search, transliteration, and identity verification measures. This gives high-accuracy ranked results, based on the linguistic, phonetic, and specific cultural variation patterns of the names.

Should translations be used for Indonesian sentiment analysis?

Trying to achieve Indonesian sentiment analysis by using an API that uses translations can yield incorrect results. So, the answer is, no. As your Indonesian sentiment analysis company, Repustate, uses intricate Indonesian NLP for higher accuracy in sentiment scoring of your data. This is because translations dilute the nuance of a statement. If a text has multiple topics, sentiments, and themes, as reviews and comments usually do, the aggregate semantic score of the data (+1 for positive, and -1 for negative) will be inaccurate with translations.

Applications of Indonesian NLP in Sentiment Analysis Tools

Analyze Twitter, Facebook, Insta, TikTok, & YouTube content:

Repustate's Indonesian sentiment analysis API helps you get useful insights through Social media listening from Facebook, Twitter, Instagram, and even video-based platforms like TikTok and YouTube. This is very useful to brands who want to capture sentiments around specific facets of their business, product line, or service.

Analyze news - text, audio & video:

Sentiment analysis from news streams is really easy with Repustate's Sentiment Analysis API. Whether you want Indonesian NLP analysis for employee surveys or product reviews, our tool gives you relevant insights. Furthermore, its visualization dashboard converts the data into charts, graphs, and tables, so you can understand the data easily.

Analyze surveys, forums, and Google reviews:

Companies dedicate a large number of resources to understanding their customers by running feedback campaigns in their stores, social forums, mobile apps, and websites. Repustate's Indonesian Voice of Customer analysis helps you make sense of all that data.

Understand public sentiment:

From policy decisions to bad customer service, whatever the issue may be, people share this information with the world. This data can be vital to a government body, or a company looking to improve its brand perception and market share.

Let Repustate's Indonesian sentiment analysis uncover your hidden insights

Real-World Applications of Indonesian Text Sentiment Analysis

Repustates's Indonesian sentiment analysis API is made for the Indonesian language and its dialects. Powered by Indonesian NLP, the solution gives you accurate and fast insights through aspect based sentiment analysis of your data. Here are some real-world examples of how Repustate has provided Indonesian sentiment analysis to organizations in various industries.

Healthcare Sector:

When the prestigious Nahdi Medical Company, based in Saudi Arabia, approached Repustate, its biggest motivation was the need to understand patients better. They wanted to overhaul the system and deliver a better patient experience. They remained dissatisfied with the speed and accuracy of other tools in the market as they could not grasp the complexity of Indonesian. Repustate's sentiment analysis API was at last able to help the client meet its objectives. Our Indonesian NLP-powered solution gathered impactful insights more accurately and faster than others. It semantically identified various aspects related to patient care and provided the client with key revelations.

Financial Sector:

A Jakarta-based financial corporation realizes that it's not good for business if they are unable to monitor global financial and stock market news accurately and fast. Since even names of companies change when the news is in a foreign language, the company realizes it is missing out on vital information in an industry that thrives on quick decision-making. Repustate's Indonesian sentiment analysis tool provides them with a highly-precise, customized, stock sentiment analysis solution powered by Indonesian NLP. Our sentiment analysis solution gives them insights into market sentiment based on price movements of securities traded, as well as financial news coverage in all major languages. They also leverage the real-time dashboard that shows market sentiment scores and share prices for different debt instruments and equities in an easy-to-understand format.

Government Sector:

A public transport agency from Surabaya wants to improve its service and brand perception and approach Repustate with the problem. They want to provide better service by addressing negative feedback and restructuring resources. They want to have an authentic and detailed understanding of the sentiment of daily commuters using public modes of transport. Repustate's Indonesian sentiment analysis API helps them understand their data. By applying Indonesian natural language processing techniques to all the reviews and comments gathered from public forums, Repustate's solution is able to give them useful insights they can use to achieve their goals.

Repustate's Enterprise Search automatically annotates your Indonesian data with semantic information. This includes relevant entities, topics, and entity-specific metadata. You can search all metadata associated with any given entity that Repustate finds by market cap or industry type for business, or perform your search by nationality. Over 100 metadata properties can be searched, and all of them can be automatically determined by Repustate's Indonesian Enterprise Search.

Tak semua bahasa sama

Aturan tata bahasa berbeda-beda antar bahasa. Aturan konjugasi kata kerja, kesesuaian kata benda-kata kerja dan negasi bervariasi antar bahasa.

Bahasa Indonesia adalah bahasa yang unik dan berbeda dari Bahasa Inggris dalam beberapa hal. Menggunakan teknik dan model bahasa yang sama dengan yang digunakan untuk analisis sentimen bahasa Inggris ketika melakukan analisis sentimen Bahasa Indonesia akan memberikan hasil yang sangat tidak akurat.

Itu sebabnya Repustate mengembangkan alat-alat yang spesifik untuk Bahasa Indonesia untuk membantu dalam analisis sentimen Bahasa Indonesia, termasuk penanda bagian wicara Bahasa Indonesia, pembuat lema Bahasa Indonesia, dan tentu saja model sentimen Bahasa Indonesia.

Penandaan bagian wicara Bahasa Indonesia

Penandaan bagian wicara Bahasa Indonesia memungkinkan Repustate untuk mempersempit ke mana kemungkinan adanya sentimen dalam suatu blok teks. Kata kerja, kata benda, dan kata sifat, memberikan petunjuk yang diperlukan untuk menentukan sentimen.

Untuk membuat penanda bagian wicara Bahasa Indonesia yang cepat dan akurat, Anda harus memiliki korpus besar teks Bahasa Indonesia yang ditandai secara manual. Teks Bahasa Indonesia ini selanjutnya dapat dimasukkan ke algoritma pembelajaran mesin untuk membuat penanda bagian wicara Bahasa Indonesia.

Semakin besar korpus, dan lebih penting lagi, semakin banyak variasi korpus, semakin baik hasil dalam membuat penanda bagian wicara Bahasa Indonesia. Repustate telah membuat korpus teks Bahasa Indonesia yang amat masif, mengumpulkan data dari berbagai sumber untuk memastikan cakupan yang baik.

Model sentimen Bahasa Indonesia

Repustate telah mengembangkan model sentimen bahasa yang spesifik untuk Bahasa Indonesia untuk menangkap berbagai frasa, idiom, dan ungkapan yang membantu menentukan sentimen saat menulis dalam Bahasa Indonesia. Memahami berbagai aspek tata bahasa dalam Bahasa Indonesia yang membuatnya unik dan amat berbeda dari Bahasa Inggris itulah yang memungkinkan analisis sentimen Bahasa Indonesia dari Repustate bisa menjadi cepat dan akurat seperti saat ini.