sinta-scraper 0.14.7

Retrieves information from Sinta (https://sinta.kemdikbud.go.id) via scraping.

Sinta Scraper

Retrieves information from Sinta (https://sinta.kemdikbud.go.id) via scraping.

Code Sample

Code sample for all functions is available as a Google Colab notebook:

Installation

pip install sinta-scraper

Dependencies: beautifulsoup4, requests, dicttoxml, dict2xml, and python-string-utils.

Importing

import sinta_scraper as sinta

Available Functions

• author()

Retrieves a single author's information by Sinta ID. For example:

author_id = '5975467'
author = sinta.author(author_id)

print(author)

The output format is the Python dictionary. The structure is given in the following sample output.

{
    "id": "5975467",
    "name": "AGUS ZAINAL ARIFIN",
    "url": "https://sinta.kemdikbud.go.id/authors/detail?id=5975467&view=overview",
    "affiliation": {
        "id": "417",
        "name": "Institut Teknologi Sepuluh Nopember",
        "url": "http://sinta.ristekbrin.go.id/affiliations/detail/?id=417&view=overview"
    },
    "department": "Teknik Informatika",
    "areas": [
        "computer vision",
        "image processing",
        "information retrieval",
        "medical imaging",
        "machine learning"
    ],
    "score": {
        "overall": 48.1,
        "3_years": 3.13,
        "overall_v2": 4726.0,
        "3_years_v2": 1377.5
    },
    "rank": {
        "national": 723,
        "3_years_national": 1099,
        "affiliation": 32,
        "3_years_affiliation": 30
    },
    "scopus": {
        "documents": 69,
        "citations": 469,
        "h-index": 10,
        "i10-index": 10,
        "g-index": 1,
        "articles": 39,
        "conferences": 30,
        "others": 0,
        "Q1": 6,
        "Q2": 12,
        "Q3": 13,
        "Q4": 3,
        "undefined": 35
    },
    "scholar": {
        "documents": 294,
        "citations": 1444,
        "h-index": 16,
        "i10-index": 36,
        "g-index": 31
    },
    "wos": {
        "documents": 1,
        "citations": null,
        "h-index": null,
        "i10-index": null,
        "g-index": null
    },
    "sinta": {
        "S0": 1,
        "S1": 8,
        "S2": 3,
        "S3": 3,
        "S4": 7,
        "S5": 0,
        "uncategorized": 272
    },
    "books": 0,
    "ipr": 2
}

• authors()

Retrieves several author's information by Sinta ID. For example:

author_ids = ['5975467', '6005015', '29555']
authors = sinta.authors(author_ids)

The output is a list of dictionaries with the same structure given by the author() function.

• dept_authors()

Retrieves a list of authors associated with a department. Department ID and affiliation ID must be specified. The output structure is different from that given by the previous function. This function retrieves only the ID and name of each author. For example:

dept_id = '55001'
affil_id = '417'
authors = sinta.dept_authors(dept_id, affil_id)

print(authors)

Output:

[
    {
        "id": "29555",
        "name": "Riyanarto Sarno"
    },
    {
        "id": "6023328",
        "name": "Nanik Suciati"
    },
    {
        "id": "5975467",
        "name": "Agus Zainal Arifin"
    },
    {
        "id": "5993318",
        "name": "Handayani Tjandrasa"
    },
    {
        "id": "5993763",
        "name": "Joko Lianto Buliali"
    },
    {
        "id": "5995823",
        "name": "Supeno Djanali"
    }
]

• depts_authors()

Does the same thing as dept_authors() except that you can specify a list of department ID's as argument. For example:

dept_ids = ['55001', '20201']
affil_id = '417'
authors = sinta.depts_authors(dept_ids, affil_id)

print(authors[:5])

Output:

[
    {
        "id": "29555",
        "name": "Riyanarto Sarno"
    },
    {
        "id": "6023328",
        "name": "Nanik Suciati"
    },
    {
        "id": "5975467",
        "name": "Agus Zainal Arifin"
    },
    {
        "id": "5993318",
        "name": "Handayani Tjandrasa"
    },
    {
        "id": "5993763",
        "name": "Joko Lianto Buliali"
    }
]

• affil()

Retrieves information about an affiliation. For example:

affil_id = '417'
affil = sinta.affil(affil_id)

print(affil)

Output:

{
    "name": "Institut Teknologi Sepuluh Nopember",
    "url": "https://its.ac.id",
    "score": {
        "overall": 37400,
        "overall_v2": 540707,
        "3_years": 5222,
        "3_years_v2": 182038
    },
    "rank": {
        "national": 7,
        "3_years_national": 11
    },
    "journals": 25,
    "verified_authors": 1115,
    "lecturers": 961
}

• affils()

Retrieves information about several affiliations. For example:

affil_ids = ['417', '404']
affils = sinta.affils(affil_ids)

print(affils)

Output

[
    {
        "name": "Institut Teknologi Sepuluh Nopember",
        "url": "https://its.ac.id",
        "score": {
            "overall": 37400,
            "overall_v2": 540707,
            "3_years": 5222,
            "3_years_v2": 182038
        },
        "rank": {
            "national": 7,
            "3_years_national": 11
        },
        "journals": 25,
        "verified_authors": 1115,
        "lecturers": 961
    },
    {
        "name": "Universitas Brawijaya",
        "url": "www.ub.ac.id",
        "score": {
            "overall": 53982,
            "overall_v2": 538192,
            "3_years": 5946,
            "3_years_v2": 217740
        },
        "rank": {
            "national": 9,
            "3_years_national": 8
        },
        "journals": 67,
        "verified_authors": 2318,
        "lecturers": 2052
    }
]

• affil_authors()

Retrieves authors associated with the specified affiliation. This function usually takes more time to complete. For example:

affil_id = '417'
authors = sinta.affil_authors(affil_id)

print(authors[:5])

Output:

[
    {
        "id": "29555",
        "name": "Riyanarto Sarno",
        "nidn": "0003085905"
    },
    {
        "id": "6005015",
        "name": "Mauridhi Hery Purnomo",
        "nidn": "0016095811"
    },
    {
        "id": "5976088",
        "name": "Chastine Fatichah",
        "nidn": "0020127508"
    },
    {
        "id": "29653",
        "name": "Adhi Yuniarto",
        "nidn": "0001067304"
    },
    {
        "id": "5998915",
        "name": "Didik Prasetyoko",
        "nidn": "0016067108"
    }
]

• author_researches()

Retrieves an author's researches. For example:

author_id = '6005015'
researches = sinta.author_researches(author_id)

print(researches[:2])

Output:

[
    {
        "title": "Monitoring Kestabilan Transient dengan Mempertimbangkan Parameter Sudut Rotor, Frekuensi, dan Tegangan Berbasis Computational Intelligence",
        "scheme": "Penelitian Penugasan ( WCR )",
        "source": "Simlitabmas",
        "members": [
            "Mauridhi Hery Purnomo",
            "Ardyono Priyadi",
            "Vita Lystianingrum B P"
        ],
        "application_year": 2020,
        "event_year": 2021,
        "fund": 118488700,
        "field": "Energi",
        "sponsor": "Ristekdikti"
    },
    {
        "title": "Intelligent Teledermatology System untuk Smart Hospital",
        "scheme": "Penelitian Penugasan ( KRU-PT )",
        "source": "Simlitabmas",
        "members": [
            "I Ketut Eddy Purnama",
            "Anak Agung Putri Ratna",
            "Ingrid Nurtanio",
            "Afif Nurul Hidayati",
            "Reza Fuad Rachmadi",
            "Mauridhi Hery Purnomo",
            "Supeno Mardi Susiki Nugroho"
        ],
        "application_year": 2020,
        "event_year": 2021,
        "fund": 436800000,
        "field": "Kesehatan",
        "sponsor": "Ristekdikti"
    }
]

• author_scholar_docs()

Retrieves an author's Google Scholar items. For example:

author_id = '6005015'
scholar = sinta.author_scholar_docs(author_id)

print(scholar[:2])

# Output:
[
    {
        "title": "Konsep Pengolahan Citra Digital dan Ekstraksi Fitur",
        "url": "https://scholar.google.com/scholar?oi=bibs&cluster=11975243569176755366&btnI=1&hl=en",
        "publisher": "Yogyakarta: Graha Ilmu, 2010",
        "year": 2010,
        "citations": 0
    },
    {
        "title": "Supervised Neural Networks dan Aplikasinya",
        "url": "https://scholar.google.com/scholar?oi=bibs&cluster=4803627219094543302&btnI=1&hl=en",
        "publisher": "Yogyakarta: Graha Ilmu; ISBN:978-979-756-123-9 1 (2006), 176",
        "year": 2006,
        "citations": 0
    }
]

• author_scopus_docs()

Retrieves an author's Scopus documents. For example:

author_id = '6005015'
scopus = sinta.author_scopus_docs(author_id)

print(scopus[:2])

Output:

[
    {
        "title": "Adaptive modified firefly algorithm for optimal coordination of overcurrent relays",
        "url": "https://www.scopus.com/record/display.uri?eid=2-s2.0-85026658931&origin=resultslist",
        "publisher": "IET Generation, Transmission and Distribution",
        "date": "2017-07-13",
        "type": "Journal",
        "quartile": 1,
        "citations": 77
    },
    {
        "title": "Controlling chaos and voltage collapse using an ANFIS-based composite controller-static var compensator in power systems",
        "url": "https://www.scopus.com/record/display.uri?eid=2-s2.0-84869223917&origin=resultslist",
        "publisher": "International Journal of Electrical Power and Energy Systems",
        "date": "2013-03-01",
        "type": "Journal",
        "quartile": 1,
        "citations": 62
    }
]

• author_scopus_journal_docs()

Retrieves an author's Scopus journal documents. For example:

author_id = '6005015'
scopus = sinta.author_scopus_journal_docs(author_id)

• author_scopus_conference_docs()

Retrieves an author's Scopus conference documents. For example:

author_id = '6005015'
scopus = sinta.author_scopus_conference_docs(author_id)

• author_wos_docs()

Retrieves an author's Web of Science documents. For example:

author_id = '6005015'
wos = sinta.author_wos_docs(author_id)

print(wos[:2])

# Output:
[
    {
        "title": "Adaptive B-spline neural network-based vector control for a grid side converter in wind turbine-DFIG systems",
        "publisher": "IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING",
        "issn": "1931-4973",
        "doi": "-",
        "uid": "WOS:000362748500009"
    },
    {
        "title": "ARIMA Modeling of Tropical Rain Attenuation on a Short 28-GHz Terrestrial Link",
        "publisher": "IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS",
        "issn": "1536-1225",
        "doi": "10.1109/LAWP.2010.2046130",
        "uid": "WOS:000276520900002"
    }
]

• author_comm_services()

Retrieves an author's community service items. For example:

author_id = '5996278'
comm_svc = sinta.author_comm_services(author_id)

print(comm_svc)

Output:

[
    {
        "title": "IbM Pembelajaran Elektronik Untuk SMK",
        "scheme": "Pengabdian Kepada Masyarakat Kompetitif Nasional ( PKM )",
        "source": "Simlitabmas",
        "members": [
            "Candra Dewi",
            "Adharul Muttaqin",
            "Achmad Basuki"
        ],
        "application_year": 2015,
        "event_year": 2016,
        "fund": 50000000,
        "field": "",
        "sponsor": "Ristekdikti"
    }
]

• author_ipr()

Retrieves an author's intellectual property right (IPR) items. For example:

author_id = '5996278'
ipr = sinta.author_ipr(author_id)

print(ipr)

Output:

[
    {
        "id": "EC00202016549",
        "title": "Panduan Pembelajaran Daring Saat Kondisi Darurat COVID-19",
        "category": "paten",
        "year": "2020",
        "holder": "Universitas Brawijaya"
    }
]

Other Output Formats

Other formats can be used by specifying the output_format argument:

author = sinta.author(id, output_format='json')

Avalable output formats:

• 'dictionary' (default)
• 'json'
• 'xml'

JSON output can be pretty-printed by setting pretty_print=True:

author = sinta.author(id, output_format='json', pretty_print=True)

For XML output, there are two library options which can be specified in the xml_library argument. These libraries give different output formats. The options are:

• dicttoxml (default)
• dict2xml

Please note that the output is not wrapped in a root element. For example:

author = sinta.author(id, output_format='xml', xml_library='dict2xml')

Output:

<affiliation>
  <id>417</id>
  <name>Institut Teknologi Sepuluh Nopember</name>
  <url>http://sinta.ristekbrin.go.id/affiliations/detail/?id=417&amp;view=overview</url>
</affiliation>
<areas>computer vision</areas>
<areas>image processing</areas>
<areas>information retrieval</areas>
<areas>medical imaging</areas>
<areas>machine learning</areas>
<books>0</books>
<department>Teknik Informatika</department>
<id>5975467</id>
<ipr>2</ipr>
<name>AGUS ZAINAL ARIFIN</name>
<rank>
  <_3_years_affiliation>30</_3_years_affiliation>
  <_3_years_national>1099</_3_years_national>
  <affiliation>32</affiliation>
  <national>723</national>
</rank>
<scholar>
  <citations>1444</citations>
  <documents>294</documents>
  <g-index>31</g-index>
  <h-index>16</h-index>
  <i10-index>36</i10-index>
</scholar>
<scopus>
  <Q1>6</Q1>
  <Q2>12</Q2>
  <Q3>13</Q3>
  <Q4>3</Q4>
  <articles>39</articles>
  <citations>469</citations>
  <conferences>30</conferences>
  <documents>69</documents>
  <g-index>1</g-index>
  <h-index>10</h-index>
  <i10-index>10</i10-index>
  <others>0</others>
  <undefined>35</undefined>
</scopus>
<score>
  <_3_years>3.13</_3_years>
  <_3_years_v2>1377.5</_3_years_v2>
  <overall>48.1</overall>
  <overall_v2>4726.0</overall_v2>
</score>
<sinta>
  <S0>1</S0>
  <S1>8</S1>
  <S2>3</S2>
  <S3>3</S3>
  <S4>7</S4>
  <S5>0</S5>
  <uncategorized>272</uncategorized>
</sinta>
<url>https://sinta.kemdikbud.go.id/authors/detail?id=5975467&amp;view=overview</url>
<wos>
  <citations>None</citations>
  <documents>1</documents>
  <g-index>None</g-index>
  <h-index>None</h-index>
  <i10-index>None</i10-index>
</wos>

If you want the XML output to be pretty-printed, you need to choose dict2xml instead of xmltodict since the latter does not produce pretty-printed XML output. By pretty-printing, the output is wrapped in a root element. For example:

author_id = '5975467'
author = sinta.author(author_id, output_format='xml', xml_library='dict2xml', pretty_print=True)

print(author)

Output:

<author>
    <affiliation>
        <id>417</id>
        <name>Institut Teknologi Sepuluh Nopember</name>
        <url>http://sinta.ristekbrin.go.id/affiliations/detail/?id=417&amp;view=overview</url>
    </affiliation>
    <areas>computer vision</areas>
    <areas>image processing</areas>
    <areas>information retrieval</areas>
    <areas>medical imaging</areas>
    <areas>machine learning</areas>
    <books>0</books>
    <department>Teknik Informatika</department>
    <id>5975467</id>
    <ipr>2</ipr>
    <name>AGUS ZAINAL ARIFIN</name>
    <rank>
        <_3_years_affiliation>30</_3_years_affiliation>
        <_3_years_national>1099</_3_years_national>
        <affiliation>32</affiliation>
        <national>723</national>
    </rank>
    <scholar>
        <citations>1444</citations>
        <documents>294</documents>
        <g-index>31</g-index>
        <h-index>16</h-index>
        <i10-index>36</i10-index>
    </scholar>
    <scopus>
        <Q1>6</Q1>
        <Q2>12</Q2>
        <Q3>13</Q3>
        <Q4>3</Q4>
        <articles>39</articles>
        <citations>469</citations>
        <conferences>30</conferences>
        <documents>69</documents>
        <g-index>1</g-index>
        <h-index>10</h-index>
        <i10-index>10</i10-index>
        <others>0</others>
        <undefined>35</undefined>
    </scopus>
    <score>
        <_3_years>3.13</_3_years>
        <_3_years_v2>1377.5</_3_years_v2>
        <overall>48.1</overall>
        <overall_v2>4726.0</overall_v2>
    </score>
    <sinta>
        <S0>1</S0>
        <S1>8</S1>
        <S2>3</S2>
        <S3>3</S3>
        <S4>7</S4>
        <S5>0</S5>
        <uncategorized>272</uncategorized>
    </sinta>
    <url>https://sinta.kemdikbud.go.id/authors/detail?id=5975467&amp;view=overview</url>
    <wos>
        <citations>None</citations>
        <documents>1</documents>
        <g-index>None</g-index>
        <h-index>None</h-index>
        <i10-index>None</i10-index>
    </wos>
</author>

Todo

• Other output formats: CSV.
• find_affil(keyword) function.
• affil_depts(affil_id) function.
• dept(dept_id) function.
• find_dept(keyword) function.
• dept_scholar_docs(dept_id) function.
• dept_scopus_docs(dept_id) function.
• dept_scopus_journal_docs(dept_id) function.
• dept_scopus_conference_docs(dept_id) function.
• dept_wos_docs(dept_id) function.
• affil_scholar_docs(dept_id) function.
• affil_scopus_docs(dept_id) function.
• affil_scopus_journal_docs(dept_id) function.
• affil_scopus_conference_docs(dept_id) function.
• affil_wos_docs(dept_id) function.
• author_scholar_citations_count(author_id) function.
• author_scopus_citations_count(author_id) function.
• author_wos_citations_count(author_id) function.
• dept_scholar_citations_count(dept_id) function.
• dept_scopus_citations_count(dept_id) function.
• dept_wos_citations_count(dept_id) function.
• affil_citations_count(author_id) function.
• Filter by date/year (only applicable for Google Scholar and Scopus).
• Sinta 3.