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Uce Indahyanti
Informatika, Universitas Muhammadiyah Sidoarjo, Indonesia
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Journal : academia open

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Revolutionizing Hospital IT Security through ISO 27001 Launched in Indonesia: Merevolusi Keamanan TI Rumah Sakit melalui ISO 27001 Diluncurkan di Indonesia Tasya Rafiiqa; Uce Indahyanti; Umi Khoirun Nisak
Academia Open Vol. 9 No. 2 (2024): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.9.2024.7052

Abstract

This study examines the security of the E-HOS System at RSUD Ibnu Sina Kab. Gresik, identifying critical threats and vulnerabilities, and offering mitigation strategies. Using qualitative methods, including interviews, observations, and documentation, data was collected from December 2022 to May 2023. The OCTAVE framework revealed 17 potential risk events, with user-related risks being the most significant, showing an RPN as high as 162 for access rights abuse. The study recommends implementing ISO 27001 controls—Access Control, Human Resource Security, and Communications Security—to enhance system security. These findings highlight the importance of robust IT security governance in healthcare settings. Highlight: Critical Risks: 17 events, highest risk in user access rights abuse. Methodology: Used OCTAVE framework, interviews, observations, documentation. Recommendations: Implement ISO 27001 controls: Access Control, HR Security, Communications Security. Keyword: E-HOS System, SIMRS security, OCTAVE method, risk assessment, ISO 27001
Sentiment Analysis of Potential Presidential Candidates 2024: A Twitter-Based Study: Analisis Sentimen Calon Presiden Potensial 2024: Sebuah Studi Berbasis Twitter Yulian Findawati; Uce Indahyanti; Yunianita Rahmawati; Ratih Puspitasari
Academia Open Vol. 8 No. 1 (2023): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.8.2023.7138

Abstract

This study aims to analyze the sentiment towards potential presidential candidates for the 2024 election in Indonesia based on Twitter users' opinions. Three prominent figures, Ganjar Pranowo, Anies Baswedan, and Prabowo Subianto, were surveyed to gauge their electability. Using machine learning classification methods, Support Vector Machine, Bernoulli Naïve Bayes, and Logistic Regression, sentiment classification was performed. The findings indicate that Twitter users expressed predominantly positive sentiments towards each potential candidate. The evaluation of the classification algorithms showed SVM with 84% accuracy, Bernoulli Naïve Bayes with 77%, and Logistic Regression with 84%. This research sheds light on public sentiment towards potential leaders, offering valuable insights for political strategists and decision-makers in shaping effective election campaigns. Highlight: Sentiment Analysis: The study employs machine learning techniques to analyze the sentiments expressed by Twitter users towards potential presidential candidates for the 2024 election in Indonesia. Positive Sentiments: The findings reveal that Twitter users predominantly exhibit positive sentiments towards all three potential candidates, Ganjar Pranowo, Anies Baswedan, and Prabowo Subianto. Election Insights: This research provides valuable insights into public sentiment, offering valuable information for political strategists and decision-makers in devising effective election campaigns for the upcoming presidential election. Keyword: Sentiment Analysis, Twitter Users, Potential Presidential Candidates, Machine Learning, Election 2024
Optimization of Stunting Prevention and Reduction through Early Detection Application, Sunting, based on Forward Chaining Inference Machine. : Optimalisasi Pencegahan dan Penurunan Stunting Melalui Aplikasi Deteksi Dini Sunting Berbasis Mesin Inferensi Forward Chaining Ika Ratna Indra Astutik; Uce Indahyanti; Evi Rinata
Academia Open Vol. 8 No. 2 (2023): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.8.2023.7267

Abstract

Stunting is a chronic malnutrition problem caused by a prolonged lack of sufficient nutrient intake, resulting in impaired growth and shorter stature (dwarfism) in children compared to age standards. In Indonesia, the prevalence of stunting remains high according to WHO standards, mainly due to the limited information available on stunting, particularly regarding preventive measures. In the era of Industry 4.0, rapid technological advancements, especially in the field of healthcare, have provided enhanced access to information and early disease diagnosis through expert system-based applications. The objective of this research is to design an application that assists the community in early detection of stunting in children, enabling timely intervention. The chosen approach involves forward chaining inference machine, testing input symptoms to draw conclusions based on the knowledge rules stored in the knowledge base. The outcome of this research is an application that facilitates parents and integrated service posts in preventing stunting disorders in children. Highlight: Intervensi Tepat Waktu: Aplikasi ini memungkinkan deteksi dini stunting, memungkinkan intervensi tepat waktu untuk mencegah gangguan pertumbuhan pada anak. Pendekatan Sistem Pakar: Memanfaatkan inferensi rantai maju, aplikasi menggunakan pengetahuan Integrasi Teknologi dan Layanan Kesehatan: Memanfaatkan kemajuan Industri 4.0, aplikasi ini menjembatani kesenjangan antara teknologi dan layanan kesehatan, memberdayakan masyarakat dan pos layanan terpadu untuk memerangi stunting secara efektif. Kata kunci: Stunting, Sistem pakar, Deteksi dini, Pelayanan kesehatan terpadu, Industri 4
Co-Authors Abidin, Husnul Ade Eviyanti Adiffanani Ramdansyah Aditya, M. Fahrul Rizki Afidah, Dewi Nur Agung Izulhaq Ahmad Angga Handoko Aisha Hanif Alfinda Ayu Hadikasari Alfitra Oktavian Anis Farihah Ariansyah, Achmad Arif Senja Fitrani Arif Senja Fitroni Aris Hendra Prayoga Awalludin, Krisna Azizah, Risma Nur Azmuri Wahyu Azinar Berlian Putri Pertiwi Brigide Tirenia Loresta Cecep Kusmana Cholifah, Cholifah Cholifah, Cholifah Cindy Cahyaning Astuti Cindy Taurusta Dafit Setiawan Jaya Damasta, Ifanda Reza Deby Kurniawan Armananda Dewi Komala Sari Diah Krisnaningsih Edi Widodo, Edi Eko Agus Suprayitno Eriyanto, Sandi Eko Evi Rinata Fahmawati, Zaki Nur Fahmi, M. Yusril Fery Febbyanto Firdausi Usqi Salsabilah Firmansah, Noval Fitri Nur Latifah Fitroni, Arif Senja Hadikasari, Alfinda Ayu Hamzah Setiawan Hindarto Ika Ratna Indra Astutik Indah Suci Purnamasari Irwan A. Kautsar Irwan Alnarus Alkautsar Irwan Alnarus Kautsar Khubro, Jamaluddin Jumadil Krisfianto, Moh Ifan Kurniawan, Wildan Lely Ika Mariyati Lily Puspa Dewi M Bahrul Ulum M Cholis Afandi Maghfiroh, Alfiah Mahelda Asri Sudarsono Malihatin S, Ulfah Metatia Intan Mauliana Moch. Aji Bagus Firmansyah Mochamad Alfan Rosid Mochammad Donni Kurniawan Mochammad Septa Sandy mochammad zien rifqi zien Muhammad Arsyad Dhani Muhammad Sulthon Abiyyu Muhammad Syamsuddin Nihayatur Rohmah Novia Ariyanti Nuril Lutvi Azizah Pertiwi, Berlian Putri Prayugah, Indra Putra, Rolando Jordan Permana Rafiiqa, Tasya Ratih Puspitasari Rizka Hadiwiyanti Rohman Dijaya Rolando Jordan Permana Putra Saesar Joko Pramono Siti Nur Haliza Suhendro Busono Sukarjadi Sukarjadi Sukma Aji Sumadyo, Sasmito Bagus Sumarno Sumarno Suryani, Siti Dwi Suseno Ardiansyah Syahrul Ibnu Rafi Tasya Rafiiqa Tutut Anjarsari Umi Khoirun Nisak Usabili, Syaikhina Veros Ariferdinand Vevy Liansari via nabila banda Wahyu Santoso Yahya Anugerah Dwi Khurrota A'yunan Yoyok Supriyono Yulian Findawati Yulius Hari Yunianita Rahmawati Yunianita Rahmawati Yuwanto, Mahmud Adi Zamorano, Ifan