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querytype of databasesER-RAG ANSWERER-RAG ExplanationAKR-NewAKR-New (Explanation)Ground TruthGround Truth Explanation
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What is the content of Fitriyana's contract?FAISS and MySQLLet me execute the provided f-string logic against the given context to generate the contract details for Fitriyana Dewi.

Contract Details for FITRIYANA DEWI:
- Position: Asisten Ahli
- Contract Date: 2020-08-12
- Base Salary: IDR 12,500,000
- Signatory: Dewi Lestari
- Contract Type: RESEARCHER EMPLOYMENT
- Key Terms:
* Appointment and Position
1. The University hereby appoints Fitriyana Dewi, S.Kom., M.Kom., hereinafter referred to as "the Researcher", to the position of Researcher.
2. The Researcher accepts the appointment and agrees to perform the duties and responsibilities associated with the position in accordance with this Contract and applicable University regulations.
* Roles and Responsibilities
The Researcher shall perform the following roles and responsibilities:
1. Conduct academic and applied research in accordance with the research agenda of the University.
2. Produce and disseminate research outputs through publications, reports, and other scholarly activities.
3. Participate in research projects, grants, and collaborations initiated or endorsed by the University.
4. Support research-related academic activities, including seminars, workshops, and mentoring, as required.
5. Perform other research-related duties reasonably assigned by the University in line with the Researcher's expertise.
* Homebase (School/Faculty)
1. The Researcher's academic homebase shall be the School of Computing, Telkom University.
2. Administrative coordination, academic reporting, and performance evaluation shall be conducted through the School, unless otherwise determined by the University.
ER-RAG queries the employee contract MySQL to obtain Fitriyani’s ID, then queries the JSON for the full contract)The content of Fitriyana's contract includes the following details:
- Lecturer ID: d22
- Contract FAISS ID: 22
- Contract Date: 2020-08-12
- Base Salary: 12,500,000
- Signatory: Dewi Lestari
(AKR search from table employee contract mysql, and isinya seperti ini)		The answer provided is retrieved via MySQL (this can be seen from the LecturerID and ContractFAISSID columns). Because the user’s query/question is not specific about the desired information, the LLM concludes that it is sufficient to provide the information available in the EmployeeContract table in MySQL without retrieving the full contract document.
RESEARCHER EMPLOYMENT CONTRACT TELKOM UNIVERSITY (JSON FAISS)

This Employment Contract (\"Contract\") is made and entered into on 12 August 2020 by and between:

Telkom University, an institution of higher education duly established under the laws of the Republic of Indonesia, having its principal address at Bandung, Indonesia, hereinafter referred to as \"the University,\"

and

Fitriyana Dewi, S.Kom., M.Kom., hereinafter referred to as \"the Researcher.\"

The University and the Researcher are hereinafter jointly referred to as \"the Parties.\"

Article 1
Appointment and Position\n1. The University hereby appoints Fitriyana Dewi, S.Kom., M.Kom., hereinafter referred to as \"the Researcher\", to the position of Researcher.\n2. The Researcher accepts the appointment and agrees to perform the duties and responsibilities associated with the position in accordance with this Contract and applicable University regulations.

Article 2
Roles and Responsibilities
The Researcher shall perform the following roles and responsibilities:
1. Conduct academic and applied research in accordance with the research agenda of the University.
2. Produce and disseminate research outputs through publications, reports, and other scholarly activities.
3. Participate in research projects, grants, and collaborations initiated or endorsed by the University.
4. Support research-related academic activities, including seminars, workshops, and mentoring, as required.
5. Perform other research-related duties reasonably assigned by the University in line with the Researcher's expertise.

Article 3
Homebase (School/Faculty)
1. The Researcher's academic homebase shall be the School of Computing, Telkom University.
2. Administrative coordination, academic reporting, and performance evaluation shall be conducted through the School, unless otherwise determined by the University.

Article 4\nTerm of Contract\n1. This Contract shall commence on 12 August 2020.\n2. The continuation, renewal, or termination of this Contract shall be subject to applicable University regulations and prevailing laws.

Article 5\nRemuneration\n1. The University shall pay the Researcher an initial monthly salary of IDR 12,500,000 (Indonesian rupiahs), subject to applicable taxes and statutory deductions.\n2. The salary shall be paid in accordance with the University's payroll policies and procedures.\n3. Any additional remuneration, incentives, or research-related benefits shall be governed by separate University policies or agreements.

Article 6\nGeneral Obligations\n1. The Researcher shall comply with all applicable University statutes, regulations, codes of conduct, and research ethics policies.\n2. The Researcher shall perform duties with professionalism and integrity and uphold the academic reputation of the University.

Article 7\nAmendment and Termination\n1. Any amendment to this Contract shall be made in writing and signed by both Parties.\n2. Termination of this Contract shall be governed by applicable University regulations and the laws of the Republic of Indonesia.

Article 8\nGoverning Law\nThis Contract shall be governed by and construed in accordance with the laws of the Republic of Indonesia.

Article 9\nFinal Provisions\nThis Contract is executed in two (2) original copies, each having equal legal force. Each Party acknowledges that it has read, understood, and agreed to the terms and conditions set forth herein.\n\nIN WITNESS WHEREOF, the Parties have executed this Contract on the date first written above.\n\nFor Telkom University\n\nName: Dewi Lestari\nTitle: Director of Human Resources\nSignature: ___________________\nDate: 12 August 2020\n\nThe Researcher\n\nName: Fitriyana Dewi, S.Kom., M.Kom.\nSignature: ___________________\nDate: 12 August 2020" },		Ground Truth is taken from the contract it self
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Are there any lecturers whose project areas are different from those of their papers?MySQL', FAISS, 'InternalWikibase']Looking at the context provided, I can see the lecturer data (dosen_data), project assignments (project_assignments), and project data (project_data). However, I notice that there is no paper data (paper_data) included in the context that would be needed to compare paper areas with project areas.

The f-string logic requires paper data with 'title' and 'author_id' fields to compare against project areas, but this data is missing from the context. Without the paper data, I cannot determine which lecturers have different project areas from their paper areas.

Based on the available information, I cannot answer the question about whether any lecturers have different project areas from their paper areas because the paper data is not provided in the context.
To answer this query, complete data on each lecturer’s papers and projects is required.

In this query, the ER-RAG system successfully retrieves lecturer project data but fails to retrieve lecturer paper data.

As a result, the model cannot answer the question because the provided context is incomplete.
Based on the provided context, all the lecturers have their project areas the same as those of their papers. Specifically, for the lecturer ADITYA FIRMAN IHSAN, every project associated with his papers shows the same project area identifier (e.g., Q3420 or Q3422 or Q3432) consistently both for the project and the paper. There is no indication of any lecturer whose project areas differ from those of their papers.

Therefore, there are no lecturers whose project areas are different from those of their papers according to the given data.		AKR-New performs retrieval in parallel, not sequentially. However, to answer this query, sequential retrieval is required. Ideally, the system should first find the lecturer’s project area, then use that result to filter and search for papers that match the project area (two dependent retrieval stages).

However, AKR-New currently only supports parallel retrieval, meaning it can retrieve lecturer project areas and lecturer papers separately, but cannot use one to filter the other. As a result, the amount of retrieved data becomes very large and less relevant.

In this query case, AKR retrieves several lecturer project areas (limited by token constraints), and separately retrieves lecturer papers. When the results of these two retrievals are combined by the LLM, the lecturers appearing in the project area data are not always the same as those in the paper data. Because there is no consistent linkage between them, the system ultimately cannot produce an accurate conclusion.		yes, there are several lecturers whose ongoing project areas differ significantly from the topics they have published papers on.

By comparing the textual and semantic similarity between their project titles and paper titles, here are a few notable examples of lecturers with completely different focuses in their projects versus their publications:

1. Miftahul Adnan Rasyid

Project Areas: Data Engineering, Data Validation and Quality, Cyber Security

Paper Topics: Text processing and linguistics (e.g., Pembangunan Korpus dari Rangkaian Kata yang Berulang pada Al-Quran)

2. Fitri Susanti

Project Areas: Fraud Detection Systems, User Behavior Pattern Analysis, Biomedical Informatics

Paper Topics: Environmental monitoring and IT Governance (e.g., Air pollution monitoring system using LoRa modul, SOA governance and ITIL v3.0, Search Algorithm to Solve Eight-Puzzle Problem)

3. Mohammad Deni Akbar

Project Areas: Cloud Computing, Islamic Intelligence

Paper Topics: Supply chain, green procurement, and logistics optimization (e.g., Supply Chain Reference Operation (SCOR), Capacitated vehicle routing problem)

4. Anisa Dzulkarnain

Project Areas: Knowledge Graph, Biomedical Informatics

Paper Topics: Agriculture simulation and disaster mitigation (e.g., System dynamics simulation to increase paddy production, Analysis of flood identification and mitigation)

5. Azka Khoirunnisa

Project Areas: Smart Systems, User Behavior Pattern Analysis

Paper Topics: Medical disease classification and detection (e.g., Malaria prediction with ensemble learning, Cancer detection based on microarray data)

These examples suggest that several lecturers are undertaking projects in more generalized computer science domains (like Cloud Computing, Data Engineering, or Smart Systems), while their written papers are highly specialized or applied to totally different fields (such as agriculture, medical classification, or supply chain logistics).		Ground Truth is obtained with the help of an LLM because the data is too large to analyze.
Context data is provided to the LLM to be analyzed and summarized.
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Who are the partnerts of Telkom University who have positive news?MongoDB Based on the provided data, here are Telkom University's partners with positive news coverage:

- ACCA Indonesia
- Admedika
- Alibaba Cloud
- Asosiasi Penyelenggara Jasa Internet Indonesia (APJII)
- Bank Muamalat
- Bank Negara Indonesia Tbk. (BNI)
- Bank Syariah Indonesia (BSI)
- Dinas Komunikasi, Informatika, dan Statistik Kabupaten Kapuas Hulu
- Feedloop AI
- Global Institute
- Horizon University Indonesia
- Indosat Ooredoo Hutchison
- Institut Seni Indonesia Bali
- Institut Seni Indonesia Padang Panjang
- Institut Teknologi Batam
- Klinik Bona Mitra Keluarga Grup
- Komisi Pengawas Persaingan Usaha
- Lancaster University
- MultiIntegra Technology Group
- Pemerintah Kabupaten Kapuas Hulu
- Pengelola Nama Domain Internet Indonesia (PANDI)
- Politeknik Internasional Bali (PIB)
- Politeknik Penerbangan Medan (Poltekbang Medan)
- Politeknik Siber Cerdika Internasional (SCI)
- PT Artajasa
- PT Citra Niaga Abadi (CNA)
- PT Gapura Liqua Solutions
- PT Media Telekomunikasi Mandiri (MTM)
- PT PLN Energi Primer Indonesia
- PT ZTE Indonesia
- Telecom Infra Project
- Telecom Infra Project (TIP)
- Toyota Motor Corporation
- Universitas Al Ihya Kuningan
- Universitas Borneo Tarakan
- Universitas Garut (UNIGA)
- Universitas Jember
- Universitas Kristen Petra
ER-RAG retrieves partner data from MongoDB, then analyzes which partners have positive news.
The partners of Telkom University who have positive news mentioned in the sources are as follows:

1. PT. Gapura Liqua Solutions
2. Universitas Borneo Tarakan
3. Institut Seni Indonesia (ISI) Bali
4. Komisi Pengawas Persaingan Usaha
5. Klinik Bona Mitra Keluarga
6. Alibaba Cloud
7. Universitas Al Ihya Kuningan
8. Indosat Ooredoo Hutchison
9. XL Smart
10. META
11. NEC
12. ASKALSI
13. APJII
14. ICPC
15. GSMA
16. Telin
17. Telkominfra
18. ISD Council
19. Alita
20. Ciena
21. Ajari Technology
22. Viavi
23. Universitas Garut (UNIGA)
24. Institut Teknologi Garut (ITG)
25. MultiIntegra Technology Group / PT MultiIntegra
26. Telecom Infra Project
27. Institut Seni Indonesia (ISI) Padang Panjang

These partners are associated with various positive cooperation news including MOUs, MOAs, Memorandums of Understanding, and strategic partnerships covering education, research, community service, institutional development, talent ecosystem development, and industrial collaborations, as detailed in the provided context (Internal Documents #1-#8, Partnership News #1-#8).		AKR-New retrieves partner data and neatly structured news summaries from MongoDB, then determines whether the news is positive or not based on those summaries. After that, the LLM lists the partner names according to the query request.Based on the documents provided, Telkom University has numerous partners associated with positive news (such as successful partnerships, collaborations, awards, and innovations).

Here are the partners of Telkom University, grouped by category:

1. Technology, AI & Telecommunications

Global Tech Giants: Alibaba Cloud, Google, IBM, META (Facebook), Microsoft (Azure OpenAI, Microsoft Clarity)

Telecommunications & Networking: Indosat Ooredoo Hutchison, ZTE (PT ZTE Indonesia), Ciena, NEC, Telecom Infra Project (TIP), GSMA, Viavi

Tech Companies & Startups: Feedloop (Feedloop AI), Ajari Technology, Alita, Matomo, XL Smart

IT Infrastructure & Services: PT Media Telekomunikasi Mandiri (MTM), PT MultiIntegra (MultiIntegra Technology Group)

2. Banking, Finance & Fintech

Banks: Bank Negara Indonesia Tbk. (BNI), Bank Syariah Indonesia (BSI), Bank BJB, Bank Muamalat, Bank Indonesia

Financial Services & Fintech: DANA, PT Artajasa, ACCA (Associations of Chartered Certified Accountants) Indonesia

3. Healthcare & Medical

AdMedika (PT Administrasi Medika)

Rumah Sakit Edelweiss

Klinik Bona Mitra Keluarga

4. Government Agencies, Associations & Institutions

Badan Siber dan Sandi Negara (BSSN)

Kementerian Komunikasi dan Digital

Komisi Pengawas Persaingan Usaha (KPPU)

Asosiasi Penyelenggara Jasa Internet Indonesia (APJII)

Pengelola Nama Domain Internet Indonesia (PANDI)

British Standards Institution (BSI) Group Indonesia

Masyarakat Telematika Indonesia

ASKALSI (Asosiasi Sistem Komunikasi Kabel Laut Seluruh Indonesia)

ISD Council (Indonesia Smart City Council)

5. Domestic & International Universities

International: Lancaster University (UK), Deakin University (Australia)

Domestic Universities: Universitas Jember, Universitas Kristen Petra (UK Petra), Universitas Borneo Tarakan, Universitas Garut, Universitas Mayasari Bakti, Universitas Al Ihya Kuningan

Institutes & Polytechnics: Institut Seni Indonesia Padang Panjang, Institut Teknologi Batam (ITEBA), Institut Teknologi Garut, Politeknik Internasional Bali, Politeknik Penerbangan Medan, Politeknik LP3I Bandung, Politeknik Siber Cerdika Internasional (SCI), Batam Tourism Polytechnic, Global Institute, Horizon University

6. Corporate, Energy & Investments

Toyota Motor Corporation

PT PLN Energi Primer Indonesia

PT Citra Niaga Abadi (CNA Investment)

PT Gapura Liqua Solutions

Telin

EDOTCO

Yayasan Vitka		Ground Truth is obtained with the help of an LLM because the data is too large to analyze.
Context data is provided to the LLM to be analyzed and summarized.
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Which lecturer has written a paper on sentiment analysis?Internal WikibaseBased on the provided data, the lecturers who have written papers on sentiment analysis are:

- Kemas M. Lhaksmana
- B. Bunyamin
- Berlian Rahmy Lidiawaty
- Sri Hidayati
- Rafi Andi Hidayah
- Arini Pramesta Setyaningtitah
ER-RAG performs a search in Wikibase using the keyword "sentiment analysis," then returns several papers along with their authors.The lecturers who have written papers on sentiment analysis according to the provided context are:

1. ADIWIJAYA
2. AGUS SULISTYA
3. ANGELINA PRIMA KURNIATI
4. ANISA DZULKARNAIN
5. ASNIAR
6. BUNYAMIN
7. DONNI RICHASDY
8. FITRIYANI
9. HASMAWATI
10. I WAYAN PALTON ANUWIKSA
11. IZZATUL UMMAH
12. KEMAS MUSLIM LHAKSMANA
13. KEMAS RAHMAT SALEH WIHARJA
14. MIRA KANIA SABARIAH
15. MOCH. ARIF BIJAKSANA
16. RACHMADITA ANDRE SWARI
17. SARI DEWI BUDIWATI
18. SRI HIDAYATI

These lecturers have authored various papers related to sentiment analysis as shown in the context.		AKR performs retrieval on an internal Wikibase containing papers and lecturer names by generating a SPARQL query with a "sentiment analysis" filter on the papers, then retrieves the authors/lecturers of those papers through the Has Paper property.terdapat banyak dosen (lecturers) yang telah menulis paper terkait sentiment analytics atau analisis sentimen. Berikut adalah daftar dosen tersebut beserta beberapa contoh topik paper yang mereka tulis:

Dr. Kemas Muslim Lhaksmana, S.T., M.ISD. (Contoh: Sentiment analysis of the 2024 Indonesia presidential election on twitter)

Prof. Dr. Adiwijaya, S.Si., M.Si (Contoh: Aspect-based sentiment analysis to review products using Naïve Bayes)

Dr. Moch. Arif Bijaksana (Contoh: Sentimen Analysis Social Media for Disaster using Naïve Bayes and IndoBERT)

Dr. Warih Maharani, S.T., M.T. (Contoh: Microblogging sentiment analysis with lexical based and machine learning approaches)

Rachmadita Andreswari, S.Kom., M.Kom. (Contoh: Sentiment analysis of social media Twitter with case of Anti-LGBT campaign)

Muhammad Azani Hasibuan, S.Kom., M.T.I. (Contoh: Sentiment analysis of product reviews using naive bayes algorithm)

Bunyamin, M.Kom. (Contoh: Sentiment Analysis of Indonesian TikTok Review Using LSTM and IndoBERTweet Algorithm)

Dr. Fitriyani, S.Si., M.T. (Contoh: Customer Sentiment Analysis of Local Skincare Reviews using IndoBERT and Graph Neural Networks)

Hasmawati, S.Kom., M.Kom. (Contoh: Implementation of IndoBERT for Sentiment Analysis of Indonesian Presidential Candidates)

Angelina Prima Kurniati, Ph.D. (Contoh: Implementation of Long Short-Term Memory Method for Financial Sentiment Analysis)

Donni Richasdy, S.T., M.T. (Contoh: BERT implementation on news sentiment analysis)

Dr. Mira Kania Sabariah, S.T., M.T. (Contoh: Sentiment analysis on Twitter about the use of city public transportation)

Sari Dewi Budiwati, S.T., M.T., Ph.D. (Contoh: Analyzing Instagram User Sentiment Toward MSME Using Naive Bayes and Logistic Regression)

Anisa Dzulkarnain, S.Kom., M.Kom. (Contoh: Sentiment Analysis of Student Complaint Text for Finding Context)

Kemas Rahmat Saleh Wiharja, S.T., M.Eng., Ph.D. (Contoh: Sentiment Analysis on Banking Chatbot using Graph-based Machine Learning Model)

Agus Sulistya, S.T., M.Sc., Ph.D (Contoh: Sentiment Analysis of Public Complaints)

Dr. Arie Ardiyanti Suryani, S.T., M.T. (Contoh: Analisis Sentimen Berbahasa Indonesia dengan Pendekatan Lexicon-Based Pada Media Sosial)

Dr. Asniar, S.T., M.T. (Contoh: A Framework for Sentiment Analysis Implementation of Indonesian Language Tweet)

Azka Khoirunnisa, S.Kom., M.Kom. (Contoh: An Integrated Random Forest for Analyzing Public Sentiment)

I Wayan Palton Anuwiksa, S.Si., M.Si. (Contoh: Optimizing Book Recommendation Systems through Integration of Sentiment Analysis)

Imelda Atastina, S.Si., M.T., Ph.D. (Contoh: Seleksi Fitur dengan Metode Categorical Proportional Difference pada Analisis Sentimen)

Izzatul Ummah, S.T., M.T. (Contoh: Public Sentiment Analysis on X Using the Bi-GRU and IndoBERT Methods)

Sri Hidayati, S.Si., M.Stat. (Contoh: Sentiment Analysis of Student Complaint Text for Finding Context)

Assoc. Prof. Dr. Z K Abdurahman Baizal, S.Si., M.Kom. (Contoh: Aspect Based Sentiment Analysis with FastText Feature Expansion)		Ground Truth is obtained with the help of an LLM because the data is too large to analyze.
Context data is provided to the LLM to be analyzed and summarized.
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Which lecturer has written a paper on sentiment analysis or Internet of Things?Internal WikibaseBased on the provided context, here are the lecturers who have written papers on sentiment analytics or Internet of Things:

▒ K. Lhaksmana: Sentiment analysis on movie review using ensemble stacking model
▒ P. Mahendra Dwifebri: Sentiment analysis on movie review using ensemble stacking model
▒ Berlian Rahmy Lidiawaty: Sentiment Analysis of Student Complaint Text for Finding Context
▒ Sri Hidayati: Sentiment Analysis of Student Complaint Text for Finding Context
▒ Rafi Andi Hidayah: Sentiment Analysis of Student Complaint Text for Finding Context
▒ Arini Pramesta Setyaningtitah: Sentiment Analysis of Student Complaint Text for Finding Context

Paper: 'Internet of Things Device for Clay Moisture Measurement'
Authors: Not specified in the data

ER-RAG performs a search in Wikibase twice using the keywords "sentiment analysis" and "internet of things," then returns several papers along with their authors.

However, for the papers retrieved from the "internet of things" search, some do not have an author property. This may be due to incomplete data.
The lecturers who have written papers on sentiment analysis or Internet of Things according to the provided context are:

1. ADIWIJAYA
- Papers on sentiment analysis include:
- "Aspect based sentiment analysis on beauty product review using random forest"
- "Aspect-based sentiment analysis to review products using Naïve Bayes"
- "Implementation of sentiment analysis movie review based on imdb with naive bayes using information gain on feature selection"
- "On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis"
- "Sentiment analysis of movie review using Naïve Bayes method with Gini index feature selection"
- "Sentiment analysis on beauty product review using modified balanced random forest method and chi-square"
- "Sentiment analysis on indonesian movie review using knn method with the implementation of chi-square feature selection"
- "Sentiment analysis on movie reviews using Information gain and K-nearest neighbor"

2. AGUS SULISTYA
- "Sentiment Analysis of Public Complaints: A Machine Learning Comparison of SVM, Naive Bayes, Random Forest, and XGBoost"

3. ANGELINA PRIMA KURNIATI
- Papers on sentiment analysis include:
- "A Comparison of Machine Learning, Deep Learning, and Transformer Approaches for Amazon Product Reviews Sentiment Analysis"
- "Implementation of Long Short-Term Memory Method for Financial Sentiment Analysis"
- "TinyBERT-Based Sentiment Analysis for Large-Scale Educational Feedback: A Case Study on Coursera Reviews"

4. ANISA DZULKARNAIN
- "Sentiment Analysis of Student Complaint Text for Finding Context"

5. ASNIAR
- "A Framework for Sentiment Analysis Implementation of Indonesian Language Tweet on Twitter"

6. BUNYAMIN
- Multiple papers on sentiment analysis, e.g.,
- "Aspect-level Sentiment Analysis on GoPay App Reviews Using Multilayer Perceptron and Word Embeddings"
- "Comparison of TF-IDF and GloVe Word Embedding for Sentiment Analysis of 2024 Presidential Candidates"
- "Sentiment analysis of beauty product reviews using the indobert method and naive bayes classification"
- "Sentiment Analysis of Indonesian TikTok Review Using LSTM and IndoBERTweet Algorithm" and others

7. DONNI RICHASDY
- Papers on sentiment analysis:
- "BERT implementation on news sentiment analysis and analysis benefits on branding"
- "Partner Sentiment Analysis for Telkom University on Twitter Social Media Using Decision Tree (CART) Algorithm"
- "Sentiment Analysis of Telkom University as the Best BPU in Indonesia Using the Random Forest Method"

8. FITRIYANI
- Papers on sentiment analysis include:
- "Customer Sentiment Analysis of Local Skincare Reviews using IndoBERT and Graph Neural Networks"
- "Sentiment Analysis Of Indihome Service Based On Geo Location Using The Bert Model On Platform X"
- "Sentiment Analysis of Political Discourse on Platform X using Graph Neural Network (GNN)"
- "Temporal Sentiment Analysis of Politician XYZ on Social Media X Using FastText Word Embedding and Graph Neural Network Model"

9. HASMAWATI
- Multiple papers on sentiment analysis, e.g.,
- "Aspect-level Sentiment Analysis on GoPay App Reviews Using Multilayer Perceptron and Word Embeddings"
- "Comparison of TF-IDF and GloVe Word Embedding for Sentiment Analysis of 2024 Presidential Candidates"
- "Implementation of IndoBERT for Sentiment Analysis of Indonesian Presidential Candidates"
- "Sentiment Analysis of Public Opinions on the McDonald's Boycott Movement Using CNN and Word2Vec Feature Extraction"
- "Sentiment Analysis of Telkom University using the Long Short-Term Memory and Word2Vec Feature Expansion"
- "Sentiment Analysis of University Social Media Using Support Vector Machine and Logistic Regression Methods"

10. I WAYAN PALTON ANUWIKSA
- "Optimizing Book Recommendation Systems through Integration of Sentiment Analysis on User Reviews"

11. IZZATUL UMMAH
- "Public Sentiment Analysis on X Using the Bi-GRU and IndoBERT Methods: Case Study The 2024 DKI Jakarta Regional Head Election"

12. KEMAS MUSLIM LHAKSMANA
- Multiple papers on sentiment analysis, e.g.,
- "2024 presidential election sentiment analysis in news media using support vector machine"
- "Deep Learning and Imbalance Handling on Movie Review Sentiment Analysis"
- "Sentiment analysis about legislative elections using deep learning with LSTM and CNN models"
- "Sentiment Analysis of Indonesian TikTok Review Using LSTM and IndoBERTweet Algorithm" and several other papers on sentiment analysis using various methods including CNN, LSTM, Word2Vec, and more.

13. KEMAS RAHMAT SALEH WIHARJA
- "Sentiment Analysis on Banking Chatbot using Graph-based Machine Learning Model"

14. MIRA KANIA SABARIAH
- "Sentiment analysis on Twitter about the use of city public transportation using support vector machine method"
- "Sentiment analysis on Twitter using the combination of lexicon-based and support vector machine for assessing the performance of a television program"

15. MOCH. ARIF BIJAKSANA
- "BERT implementation on news sentiment analysis and analysis benefits on branding"
- "Sentiment analysis of student satisfaction on Telkom University Language Center (LaC) services on Instagram using the RNN method"

16. RACHMADITA ANDRE SWARI
- Numerous papers on sentiment analysis including but not limited to:
- "Comparison of K-Nearest Neighbor and Logistic Regression Algorithms on Sentiment Analysis of Covid-19 Vaccination on Twitter with Vader And Textblob Labeling"
- "Comparison of support vector machine and random forest algorithms in sentiment analysis on COVID-19 Vaccination on Twitter using VADER and TextBlob labelling"
- "Development of youtube sentiment analysis application using K-Nearest Neighbors (Nokia Case Study)"
- "Implementation of Robotic Process Automation for Sentiment Analysis of Lecturer Evaluation By Students (EDOM) At Higher Education Information System"
- "Sentiment analysis of product reviews using naive bayes algorithm: A case study"
- "Sentiment analysis of social media Twitter with case of Anti-LGBT campaign in Indonesia using Naïve Bayes, decision tree, and random forest algorithm"
- "Sentiment analysis of social Media users using naïve Bayes, decision tree, random forest algorithm: A case study of draft law on the elimination of sexual violence (RUU PKS)"
- "SENTIMENT ANALYSIS OF ‘INDONESIAN NO DATING CAMPAIGNS’ ON TWITTER USING NAÏVE BAYES ALGORITHM"
- "Sentiment analysis on youtube social media using decision tree and random forest algorithm: A case study"
- "Sentiment analysis to measure celebrity Endorsment’s effect using support vector machine algorithm"
- "Sentiment Analysis Website of Online Hotel Booking Application Reviews Using the Naive Bayes Algorithm"
- "Vectorizer comparison for sentiment analysis on social media youtube: A case study"

17. SARI DEWI BUDIWATI
- "Public Sentiment Analysis of Telkom University: A Comparative Study of SVM and Decision Tree Models"
- "Sentiment Analysis on Vocational High School: A Machine Learning Approach"

18. SATRIA AKBAR MUGITAMA
- Paper on Internet of Things:
- "Internet of Things Device for Clay Moisture Measurement"

19. SRI HIDAYATI
- "Sentiment Analysis of Student Complaint Text for Finding Context"

Hence, these lecturers have written papers on either sentiment analysis or Internet of Things based on the given data.

No other lecturers or papers related to these topics were found in the provided information.		AKR searches the internal Wikibase via SPARQL using filters for "Internet of Things" and "Sentiment Analysis" on the paper titles, then retrieves the authors and titles of those papers.
Dosen dengan Paper Terkait Internet of Things (IoT):

Bambang Subeno, S.T., M.Kom. (Contoh paper: Implementasi IoT untuk Kontroling Lampu dan Suhu Rumah Berbasis Android)

Satria Akbar Mugitama, S.Kom., M.Kom. (Contoh paper: Internet of Things Device for Clay Moisture Measurement)

Dosen dengan Paper Terkait Sentiment Analytics / Analisis Sentimen:

Dr. Warih Maharani, S.T., M.T. (16 paper, m. misal: Microblogging sentiment analysis with lexical based and machine learning approaches)

Prof. Dr. Adiwijaya, S.Si., M.Si (15 paper, misal: Aspect-based sentiment analysis to review products using Naïve Bayes)

Rachmadita Andreswari, S.Kom., M.Kom. (14 paper, misal: Sentiment analysis of social media Twitter with case of Anti-LGBT campaign)

Dr. Kemas Muslim Lhaksmana, S.T., M.ISD. (13 paper, misal: Sentiment analysis of the 2024 Indonesia presidential election on twitter)

Bunyamin, M.Kom. (8 paper, misal: Sentiment Analysis of Indonesian TikTok Review)

Dr. Fitriyani, S.Si., M.T. (7 paper, misal: Customer Sentiment Analysis of Local Skincare Reviews)

Hasmawati, S.Kom., M.Kom. (7 paper, misal: Implementation of IndoBERT for Sentiment Analysis of Indonesian Presidential Candidates)

Muhammad Azani Hasibuan, S.Kom., M.T.I. (6 paper)

Dr. Moch. Arif Bijaksana (5 paper)

Angelina Prima Kurniati, Ph.D. (4 paper)

Donni Richasdy, S.T., M.T. (4 paper)

Dr. Mira Kania Sabariah, S.T., M.T. (4 paper)

Sari Dewi Budiwati, S.T., M.T., Ph.D. (4 paper)

Anisa Dzulkarnain, S.Kom., M.Kom. (3 paper)

Agus Sulistya, S.T., M.Sc., Ph.D

Assoc. Prof. Dr. Z K Abdurahman Baizal, S.Si., M.Kom.

Azka Khoirunnisa, S.Kom., M.Kom.

Dr. Arie Ardiyanti Suryani, S.T., M.T.

Dr. Asniar, S.T., M.T.

I Wayan Palton Anuwiksa, S.Si., M.Si.

Imelda Atastina, S.Si., M.T., Ph.D.

Izzatul Ummah, S.T., M.T.

Kemas Rahmat Saleh Wiharja, S.T., M.Eng., Ph.D.

Sri Hidayati, S.Si., M.Stat.		Ground Truth is obtained with the help of an LLM because the data is too large to analyze.
Context data is provided to the LLM to be analyzed and summarized.
7
Since when has Fitriyana been teaching at Telkom University? How many papers has she written?MySQL', 'InternalWikibase']Based on the earliest teaching record from 2020, Fitriyana Dewi has been teaching at Telkom University since 2020. She has written 48 research papers.ER-RAG performs searches across two databases: MySQL and Wikibase.

ER-RAG queries MySQL to find when Mrs. Fitriyana started teaching at Telkom.

ER-RAG queries Wikibase to determine how many papers she has written.		The provided context does not contain information about since when Fitriyana Dewi has been teaching at Telkom University. However, according to the context, Fitriyana Dewi has written 57 papers.The system attempts to find the earliest academic year for lecturer Fitriyani through the MySQL *Mengajar* table, but fails to generate a valid query. This failure is caused by a discrepancy in institution naming, where the query uses “Telkom University” while the value stored in the database is “Universitas Telkom”.

In addition, AKR does not identify a more efficient alternative solution, such as using the contract date in the *EmployeeContract* table. This is likely because AKR assumes that the contract date is not the same as the teaching start date.

From a strategy perspective, AKR’s approach is actually correct, but it is still not optimal in the execution stage, particularly in terms of data naming consistency and exploration of alternative information sources.
Based on the available data, the lecturer named Fitriyana Dewi, S.Kom., M.Kom. has written 48 papers and has been teaching since 2020.
Ground Truth was taken and analyzed manually to verify correctness
8
How many partners does Telkom University have, what is the total number of papers in the current database?Internal WikibaseBased on the information provided, Telkom University has 0 partners and the total number of papers in the database is 0.
ER-RAG fails because it is unable to retrieve the context. Since ER-RAG is entity-based, the system likely attempts to fetch data directly from MongoDB, but the fetched keywords do not exist or do not match, resulting in no data being returned from MongoDB.Telkom University has 393 partners, and the total number of papers in the current database is 2470.A search is performed on Wikibase, which contains data on papers and Telkom University partners. The search is conducted using SPARQL to count the number of entities with the Is Paper property for papers and the Has Partnership property for partners.telkom university has many partner
Ground Truth is obtained by directly checking how many Telkom University partners are in MongoDB and how many papers are in Wikibase.
9
who are the co-authors of Kemas Rahmat Saleh WiharjaInternal WikibaseBased on the retrieved data, Kemas Rahmat Saleh Wiharja has researched 68 papers and holds 2 patents. However, no co-author information is available in the retrieved data.
ER-RAG attempts to retrieve the co-author property from the entity of the given name. However, since the co-author data is structurally stored within the paper entity, the system does not obtain the co-author list, resulting in a failure to correctly answer the query.The co-authors of Kemas Rahmat Saleh Wiharja found in the context are:

- Dana Sulistiyo Kusumo (paper: Analisis Aspek Behavioral Pada Business Process Model And Notation Menggunakan Causal Footprints)
- Nungki Selviandro (paper: Analisis Dan Implementasi Algoritma Gspan Dan Lpboost Pada Klasifikasi Struktur Molekul Kimia)
- Anisa Herdiani (paper: Analisis Dan Implementasi Graph Clustering Pada Berita Online Menggunakan Algoritma Chinese Whispers)
- Hasmawati (paper: Early Detection of Heart Disease with Graph Neural Network)
- Alfian Akbar Gozali (paper: Implementasi Dan Analisis Performansi Mapreduce Di Lingkungan Sistem Basisdata Berbasis Dokumen Terdistribusi Homogen)
- Bayu Munajat (paper: Pengembangan 2D Platformer Game Engine menggunakan Data-driven Programming)
- Satwika Parama Putra (paper: Perencanaan Strategis Sistem Informasi Menggunakan Metode Ward and Peppard Pada PT. Medika Antapani)
- Erda Guslinar Perdana (paper: Perencanaan Strategis Sistem Informasi Menggunakan Metode Ward and Peppard Pada PT. Medika Antapani)
- Medika (paper: Perencanaan Strategis Sistem Informasi Menggunakan Metode Ward and Peppard Pada PT. Medika Antapani)
- Antapani (paper: Perencanaan Strategis Sistem Informasi Menggunakan Metode Ward and Peppard Pada PT. Medika Antapani)
- Saleh Wiharja (appears as co-author with Kemas Rahmat in some papers)
- Muhammad Faizal Eko Saputro (paper: Graph Edit Distance optimized with Greedy Algorithm for Similarity Search in Business Process Graphs)
- Z. Baizal (paper: Recommending Higher Education Student Profile Using Knowledge Graph-based Conversational Recommender System)
- Muhammad Arya Fikriansyah (paper: Comparative Analysis of Transformer Models in Object Detection and Relationship Determination on COCO Dataset, though this is co-authoring with K. Wiharja, not explicitly Kemas Rahmat Saleh Wiharja)
- M. Bijaksana (paper: Sentiment Analysis on Banking Chatbot using Graph-based Machine Learning Model, likely with K. Wiharja, no explicit mention of Kemas Rahmat Saleh Wiharja)
- Kusuma Ayu Laksitowening (paper: Implementasi Iso 25010: 2010 Untuk Evaluasi Kualitas Perangkat Lunak, mentioned as other lecturer, not co-author)

Specifically co-authors with Kemas Rahmat Saleh Wiharja from the data are:

- Dana Sulistiyo Kusumo
- Nungki Selviandro
- Anisa Herdiani
- Hasmawati
- Alfian Akbar Gozali
- Bayu Munajat
- Satwika Parama Putra
- Erda Guslinar Perdana
- Medika
- Antapani
- Saleh Wiharja

According to several entries, the exact co-author names with him explicitly are as above.

(See papers: Q132, Q164, Q163, Q141, Q167, Q173, Q134, Q150, Q155)		Data is retrieved from Wikibase. Note that there are incorrect entries in the results: "antapani" and "medika" are data errors in the database, where in a paper, Antapani and Medika are listed as co-authors.
Based on the data you provided, the following is the list of co-authors of Mr. Kemas Rahmat Saleh Wiharja:

Martin Kollingbaum

Jeff Z. Pan

Yu Deng (邓豫)

Erda Guslinar Perdana

Dana Sulistiyo Kusumo

Danang Triantoro Murdiansyah

Gia Septiana Wulandari

Alfian Akbar Gozali

Kusuma Ayu Laksitowening

Siti Saadah

Imelda Atastina

Mira Kania Sabariah

Naufal Rezky Ananda

Erwin Budi Setiawan

Kiki Maulana Adhinugraha

Adiwijaya

Fitriyani Fitriyani
Ground Truth is obtained by providing context data to the LLM, then the LLM analyzes and generates a summary from the data.
10
How many lecturers with doctoral degrees are active and have written more than 5 papers?MySQL', 'InternalWikibase']There are 20 active lecturers with doctoral degrees who have written more than 5 papers.
ER-RAG performs a search in MySQL to find lecturers whose highest education is a PhD (S3) and who have active status.

Then, the names of those lecturers are used to search for their papers in Wikibase.		Based on the provided data, the lecturers with doctoral degrees who are active (listed in the MySQL database) and have written more than 5 papers (according to the internal knowledge graph) are:

1. KEMAS RAHMAT SALEH WIHARJA - 68 papers
2. ARIE ARDIYANTI SURYANI - 86 papers
3. ASNIAR - 10 papers
4. ATI SUCI DIAN MARTHA - 48 papers
5. DZIBAN NAUFAL - 15 papers
6. MOCH. ARIF BIJAKSANA - 99 papers
7. FHIRA NHITA - 53 papers
8. FITRIYANI - 39 papers
9. GIA SEPTIANA WULANDARI - 60 papers
10. GUNTUR PRABAWA KUSUMA - 56 papers
11. HANUNG NINDITO PRASETYO - 99 papers
12. KEMAS MUSLIM LHAKSMANA - 81 papers
13. I DEWA ALIT DWIJA PUTRA - 43 papers
14. I WAYAN PALTON ANUWIKSA - 13 papers
15. IMELDA ATASTINA - 72 papers
16. KUSUMA AYU LAKSITOWENING - 62 papers
17. MAHMUD IMRONA - 61 papers
18. MIRA KANIA SABARIAH - 99 papers
19. MOHAMMAD DENI AKBAR - 50 papers
20. ADITYA FIRMAN IHSAN - 76 papers
21. NUNGKI SELVIANDRO - 72 papers
22. SARI DEWI BUDIWATI - 75 papers
23. ADIWJAYA - 99 papers
24. ANGELINA PRIMA KURNIATI - 79 papers

There are 24 lecturers who meet the criteria of having doctoral degrees, being active, and having written more than 5 papers.		AKR retrieves data using SPARQL from the internal Wikibase, then obtains lecturer names and their highest education from MySQL. After that, it filters and displays only those who have a PhD (S3) degree.
Based on the data provided, there are 24 active lecturers with a doctoral degree (S3) who have written more than 5 papers.
11
What are positive news about Telkom University in March 2026?external wikidataBased on the information available, no positive news about Telkom University was found for March 2026.
ER-RAG attempts to access news data, but the query is too complex for ER-RAG to execute, resulting in no news context being retrieved.
There is no information about positive news concerning Telkom University in March 2026 in the provided context. All sources either contain no relevant information or focus on events from years prior to 2026.AKR is not yet able to filter dates for news data. The strategy used by AKR is to retrieve news documents from FAISS, then filter the results based on the requested date. However, after filtering, the number of retrieved documents becomes 0. A better strategy would be to first filter documents by date in MongoDB, and then retrieve the positive news.
Based on news reports in March 2026, there were several achievements and positive developments from Telkom University (Tel-U), including:

1. **DILAN LAB Tel-U Secures BESTARI SAINTEK 2026 Grant (March 16, 2026)**
The Faculty of Communication and Social Sciences (FKS), through its research unit DILAN LAB (Digital Language and Humanities), successfully won the BESTARI SAINTEK 2026 grant. They proposed an innovative project titled *"Living Lab for Globally Competitive Empowered Persons with Disabilities."* This project aims to create an inclusive learning and empowerment ecosystem (especially for the Deaf community) to enhance digital literacy and economic independence.

2. **Cross-Country Innovation Collaboration with Cyberport Hong Kong (March 10–13, 2026)**
Telkom University, through Bandung Techno Park (BTP), successfully organized a Business Matching event that connected various university Centers of Excellence with 12 technology companies from the Cyberport Hong Kong delegation. This strategic collaboration focuses on innovations in Artificial Intelligence (AI), smart cities, and cybersecurity. As part of this program’s success, Cube Studio, a Telkom University startup specializing in gamified IT solutions, was selected to participate in the global landing program at Cyberport Hong Kong.

3. **International Recognition at Youth SDGs Ambassador (March 12, 2026)**
Telkom University students once again achieved recognition by receiving a prestigious award at the Youth SDGs Ambassador event. This achievement highlights the active role of Tel-U students in innovating and contributing to Sustainable Development Goals (SDGs) programs at both national and global levels.

These three highlights emphasize Telkom University’s commitment not only to academic and technological excellence (global presence), but also to inclusive and sustainable social contributions.