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Journal : POSITIF

Perancangan Service Catalogue Pada Layanan IT Di Industri Pulp and Paper Divisi Teknikal Dokumen Kontrol Berdasarkan Framework ITIL Versi 3 Lestari, Indri Endang; Cholil, Widya; Antoni, Darius; Syamsuar, Dedy; Akbar, Muhammad
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 7 No 2 (2021): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v7i2.1137

Abstract

IT services are one of the important factors in business operations in the technical document control division. The document control technical division is a division that has a vital role in supporting the construction, production and maintenance processes. This study aims to design a service catalog management using the ITIL V3 framework. The stages in designing this catalog are problem identification, data collection, data analysis, domain mapping based on the ITIL version 3 framework, domain determination, and e-catalog management design. And this research produces an e-catalog management application that contains information about the service descriptions in the technical division of document control and management of incidents that occur.
Analisa Rekam Medis Elektronik Untuk Menentukan Diagnosa Medis Dalam Kategori Bab ICD 10 Menggunakan Machine Learning Amin, Zulius Akbar; Cholil, Widya; Herdiansyah, M. Izman; Negara, Edi Surya
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 7 No 2 (2021): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v7i2.1140

Abstract

Based on observations of the business process flow at the Siti Fatimah Hospital, the background for this study was the medical record document and ICD-10 code which was carried out manual diagnosis, making it difficult for the medical record section in the proper and fast CHAPTER arrangement of the ICD-10 code. The International Statistical Classification of Diseases and Related Health Problems (ICD) can be used to calculate or record a valid patient history of hospitalization. The Cross-Industry Standard Process For Data Mining (CRISP-DM) method is used in this study to become a strategy to describe the problem in general from the domain or research unit. While the machine learning algorithm for multiclass classification uses the Naïve Bayes algorithm, Support Vector Machine, Logistic Regression to create a diagnostic model for medical action. This study predicts ICD-10 chapter categories from medical action records from electronic medical records. With this research, it is hoped that machine learning can facilitate the medical record section in predicting the ICD-10 chapter category by analyzing electronic medical record data using the Chapter ICD-10 Decision Support System information system
Perancangan Service Catalogue Pada Layanan IT Di Industri Pulp and Paper Divisi Teknikal Dokumen Kontrol Berdasarkan Framework ITIL Versi 3 Indri Endang Lestari; Widya Cholil; Darius Antoni; Dedy Syamsuar; Muhammad Akbar
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 7 No 2 (2021): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v7i2.1137

Abstract

IT services are one of the important factors in business operations in the technical document control division. The document control technical division is a division that has a vital role in supporting the construction, production and maintenance processes. This study aims to design a service catalog management using the ITIL V3 framework. The stages in designing this catalog are problem identification, data collection, data analysis, domain mapping based on the ITIL version 3 framework, domain determination, and e-catalog management design. And this research produces an e-catalog management application that contains information about the service descriptions in the technical division of document control and management of incidents that occur.
Analisa Rekam Medis Elektronik Untuk Menentukan Diagnosa Medis Dalam Kategori Bab ICD 10 Menggunakan Machine Learning Zulius Akbar Amin; Widya Cholil; M. Izman Herdiansyah; Edi Surya Negara
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 7 No 2 (2021): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v7i2.1140

Abstract

Based on observations of the business process flow at the Siti Fatimah Hospital, the background for this study was the medical record document and ICD-10 code which was carried out manual diagnosis, making it difficult for the medical record section in the proper and fast CHAPTER arrangement of the ICD-10 code. The International Statistical Classification of Diseases and Related Health Problems (ICD) can be used to calculate or record a valid patient history of hospitalization. The Cross-Industry Standard Process For Data Mining (CRISP-DM) method is used in this study to become a strategy to describe the problem in general from the domain or research unit. While the machine learning algorithm for multiclass classification uses the Naïve Bayes algorithm, Support Vector Machine, Logistic Regression to create a diagnostic model for medical action. This study predicts ICD-10 chapter categories from medical action records from electronic medical records. With this research, it is hoped that machine learning can facilitate the medical record section in predicting the ICD-10 chapter category by analyzing electronic medical record data using the Chapter ICD-10 Decision Support System information system
Co-Authors A.Haidar Mirza Ade Ramadhan Dalimunthi Adiktia Adiktia Agiyani, Gina Ali Imron Amin, Zulius Akbar Andriani, Nia Andryani, Ria Anita Muliawati Antoni, Darius AR, Hasmawaty Ariandi, Muhamad Aristian Aristian Asmanita . Azim Zaliha binti Abd Aziz Bayu Hardiono Chairul Mukmin Chindi Seftylia Darius Antoni Darius Antoni Darius Antoni Darusalam, Darusalam Dea Vitara Dedy Syamsuar Dedy Syamsuar duince fernande Dwi Mardiana Edi Surya Negara Eva Eva Evi Novilia Fajar Prayoga Fandy Kurniawan Febriyanti Panjaitan Firdaus Fitria Rahmadayanti Fosu , Agyei Friska Aryani Hadi Syaputra Herdiansyah, M. Izman Herdiansyah, M. Izman Ilham Muammar Choiri Ilham, Mohammad Indri Endang Lestari Isnainiyah, Ika Nurlaili Jayanta Jayanta Kraugusteeliana Kraugusteeliana Lestari, Indri Endang Lily Pebriana. S Linda Atika Linda Atika Linda Atika Lingga Tiara Mahardika, Billi Mahdalena, Desi Mohammad Ilham Muhamad Akbar Muhammad Akbar Muhammad Izman Herdiansyah Muhammad Kamil Mukron Roni Mutia Mawardah Nizar Firliansa Nizar Firliansa Nurmayanti Nurmayanti Prihandoko . Raden Muhammad Mirza Prasetyo Rama Andriya Saputra Renaldi dwi putra Renal Rendi Septriadi Reni Septiyanti Ria Aprinda Ria Astriratma Rolia Wahasusmia Rolia Wahasusmiah Rumondang Martha Ambarita Ryan Andrian Safta Hastini Siti Ratu Delima Siti Sauda Sukmawati, Ade Susan Dian Purnamasari Syahril Rizal, Syahril Tata Sutabri Timur Dali Purwanto Harkespan Tjahjanto Tjahjanto Tri Basuki Kurniawan Tri Basuki Kurniawan Usman Ependi Widi Pradnyana, I Wayan Wulandari, Intan Fitriana Yesi Novaria Kunang Yoga Pratama Yupika, Eva Zaid Amin, Zaid Zaidiah, Ati Zulius Akbar Amin