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November 22, 2022
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March 31, 2023
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PDF Implementasi Business Intelligence untuk Analisa dan Visualisasi Data Penyebab Kematian Di Indonesia Menggunakan Platform Tableau
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Abstract

Factors causing death in Indonesia are increasing, and many of them cannot identified with certainty. This study aims to identify the most common causes of death in Indonesia. such as causes of death due to social disasters, causes of death due to natural disasters, and causes of death due to non-natural disasters and diseases. This study employs a dataset method from www.kaggle.com with a time span of 2012-2021. The results of this study are reports in the form of a visualization dashboard using Tableau that contains information on the most common causes that occur in Indonesia with a range from 2012 to 2021 so that it can be used as a reference to support decision-making. In conclusion, the number of deaths in 2012–2021 was caused by the highest number of deaths due to natural disasters caused by earthquakes and tsunamis, which accounted for 2,615 deaths. Furthermore, the most cases of death due to non-natural disasters and diseases were caused by COVID-19, namely 144,094 deaths. And the most cases of death due to social disasters were caused by social conflict or social unrest, with 69 deaths.

Keywords

Business Intelligence Causes of Death Tableau Visualization

Article Details

Author Biographies

Lathifah Dini Rachmawati, Universitas Muhammadiyah Prof.Dr Hamka

Program Studi Teknik Informatika

Firman Noor Hasan, Universitas Muhammadiyah Prof.Dr Hamka

Program Studi Teknik Informatika

References

  1. Adila, N., & Andri, A. (2021). Desain Dan Implementasi Data Warehouse Pada Perpustakaan Daerah Provinsi Sumatera Selatan. Jurnal Nasional Ilmu Komputer, 2(1), 33–50. https://doi.org/https://doi.org/10.47747/jurnalnik.v2i1.520
  2. Afikah, P., Avorizano, A., Afandi, I. R., & Hasan, F. N. (2022). Implementasi Business Intelligence Untuk Menganalisis Data Kasus Virus Corona Di Indonesia Menggunakan Platform Tableau. 9, 25–32. https://doi.org/10.33369/pseudocode.9.1.25-32
  3. Anardani, S., Yunitasari, Y., & ... (2022). Analisis Penerapan Business Intelligence System Pada Pengelolaan Data Alumni Program Studi Teknik Informatika Universitas PGRI Madiun. RESEARCH: Journal of …, 5(1), 35–40. https://doi.org/http://doi.org/10.25273/research.v5i1.7148
  4. Ashriyyah, J. Al. (2020). Kematian Dalam Prespektif Al-Quran. 6(1). https://doi.org/https://doi.org/10.53038/alashriyyah.v6i01.126
  5. Batt, S., Grealis, T., Harmon, O., & Tomolonis, P. (2020). Learning Tableau: A data visualization tool. Journal of Economic Education, 51(3–4), 317–328. https://doi.org/10.1080/00220485.2020.1804503
  6. Falissard, L., Morgand, C., Roussel, S., Imbaud, C., Ghosn, W., Bounebache, K., & Rey, G. (2020). A deep artificial neural network-based model for prediction of underlying cause of death from death certificates: Algorithm development and validation. JMIR Medical Informatics, 8(4), 1–15. https://doi.org/10.2196/17125
  7. Ferawati, K., Bayu Nirwana, M., Pratiwi, H., Sulistijowati Handajani, S., Respatiwulan, R., Susanti, Y., & Qona’ah, N. (2021). Pemanfaatan Excel untuk Analisis dan Visualisasi Data Kesehatan Masyarakat Kabupaten Sukoharjo. Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat Dan Corporate Social Responsibility (PKM-CSR), 4, 528–535. https://doi.org/10.37695/pkmcsr.v4i0.1133
  8. Hasan, F. N., & Febriandirza, A. (2021). Perancangan Data Warehouse Untuk Data Penelitian Di Perguruan Tinggi Menggunakan Pendekatan Nine Steps Methodologhy. Pseudocode, 8(1), 49–57. https://doi.org/10.33369/pseudocode.8.1.49-57
  9. Labib, M., Wibisono, B. A., Damayanti, S. A., & Arianto, M. R. (2022). Implementasi Business Intelligence Pada Golongan Darah Menggunakan Tableau Public ( Studi Kasus : Kota Bandung ). April. https://doi.org/10.31219/osf.io/fj2zg
  10. Maesaroh, S., Lubis, R. R., Husna, L. N., & ... (2022). Efektivitas Implementasi Manajemen Business Intelligence pada Industri 4.0. ADI Bisnis Digital …, 0–7. https://doi.org/https://doi.org/10.34306/abdi.v3i2.764
  11. Mz, Y., Bororing, J. E., Rahayu, S., & Ramadhani, T. A. (2022). Edumatic: Jurnal Pendidikan Informatika Aplikasi Dashboard Visualisasi Data Calon Mahasiswa Baru mengunakan Metabase. Pendidikan Informatika, 6(1), 116–125. https://doi.org/10.29408/edumatic.v6i1.5483
  12. Nurmalasari, D. (2021). Implementasi Business Intelligence Dashboard pada Data Pasien Puskesmas Kecamatan Rokan. Jurnal Komputer Terapan, 7(2), 174–183. https://doi.org/https://doi.org/10.35143/jkt.v7i2.4986
  13. Pandensolang, F., Manoppo, F., & Sumendap, A. (2022). Implementasi Business Intelligence Untuk Analisa dan Visualisasi Perbandingan Perencanaan dan Realisasi Anggaran pada BNNP Sulawesi Utara. 1–8. https://doi.org/10.31219/osf.io/fj2zg
  14. Pratama, B. A., Proboyekti, U., & Wijana, K. (2021). Penerapan Metode User Centered Design (UCD) Dalam Pembangunan Layanan Online Jual Beli Barang Bekas. Jurnal Terapan Teknologi Informasi, 4(1), 33–43. https://doi.org/10.21460/jutei.2020.41.192
  15. Saepuloh, D. (2020). Visualisasi Data Covid 19 Provinsi DKI Menggunakan Tableau. Jurnal Riset Jakarta, 13(2), 55–64. https://doi.org/https://doi.org/10.37439/jurnaldrd.v13i2.37
  16. Sari, N., Rokhmah, D., & Ma’rufi, I. (2020). Ketidaktepatan Kode Sebab Dasar Kematian menjadi Penyebab Kerugian 600 Juta Dana di Unit ICCU RSUD dr Moh Saleh Probolinggo. Multidisciplinary Journal, 3(1), 19. https://doi.org/10.19184/multijournal.v3i1.23683
  17. Sariasih, F. A. (2022). Implementasi Business Intelligence Dashboard dengan Tableau Public untuk Visualisasi Propinsi Rawan Banjir di Indonesia. 6, 14424–14431. https://doi.org/https://doi.org/10.31004/jptam.v6i2.4715
  18. Suhendar, A., & Hikmatunnisa, T. (2022). Penerapan Business Intelligence Pada Peluang Jenis Usaha Baru Usaha Mikro Kecil Menengah Dengan Menggunakan Teknologi Online Analytical Processing. JSiI (Jurnal Sistem Informasi), 9(2), 115–118. https://doi.org/10.30656/jsii.v9i2.5183
  19. Thanavanh, B., Hackpaserd, S., Inthaphatha, S., Kariya, T., Suzuki, Y., Yamamoto, E., & Hamajima, N. (2022). Underlying cause of death at medical facilities in Xaiyabouli Province, Lao People’s Democratic Republic. Nagoya Journal of Medical Science, 84(2), 448–461. https://doi.org/10.18999/nagjms.84.2.448
  20. Welhelmina, F., Viatiningsih, W., Widjaja, L., & Yulia, N. (2022). Ketepatan Kode Diagnosis Penyebab Dasar Kematian Di Rumah Sakit Di Indonesia : Literatur Review. 3(September), 514–520. https://doi.org/https://doi.org/10.31004/jkt.v3i3.7693
  21. Wibowo, A. S., & Andri, A. (2021). Dashboard Business Intelligence Vusialisasi Data Akreditasi Sekolah Pada SMP Negeri 1 Sembawa. Jurnal Nasional Ilmu Komputer, 2(4), 249–256. https://doi.org/10.47747/jurnalnik.v2i4.536
  22. Wicaksana, A. (2021). Pelatihan Kebidanan Lanjutan pada Bidan terhadap Penurunan Angka Kematian Ibu. Keperawatan Silampari, 4, 618–624. https://doi.org/https://doi.org/10.31539/jks.v4i2.1941
  23. Widayati, Q., & Effendi, I. (2021). Pemanfaatan Software Tableau Dalam Pembuatan Dashboard Bencana Karhutla Di BPBD Sumatera Selatan. Jurnal Pengabdian Kepada Masyarakat Bina Darma, 1(2), 132–141. https://doi.org/10.33557/pengabdian.v1i2.1449