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Pemanfaatan Artificial Intelligence dalam Proses Data to Information untuk Mendukung Pengambilan Keputusan di Fasilitas Kesehatan: Systematic Literature Review Nanda Argaswari Yurez; Evi Desiana; Dwi Septi Andria; M Tsaqif Hendana; Budi Hartono
Indo Green Journal Vol. 4 No. 2 (2026): Green 2026
Publisher : Published by Institut Teknologi Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/green.v4i2.439

Abstract

Transformasi digital di sektor kesehatan menghasilkan volume data yang sangat besar, namun belum seluruhnya mampu diolah menjadi informasi yang bermakna bagi pengambilan keputusan. Artificial Intelligence (AI), khususnya Machine Learning (ML), dinilai memiliki potensi besar dalam mendukung proses Data to Information (DTI) di fasilitas kesehatan melalui pembersihan data, analisis prediktif, deteksi pola, dan penyediaan informasi berbasis bukti. Penelitian ini bertujuan menganalisis peran, manfaat, hambatan, kelemahan, serta strategi optimalisasi pemanfaatan AI dalam proses DTI untuk mendukung pengambilan keputusan di fasilitas kesehatan. Metode yang digunakan adalah Systematic Literature Review dengan pendekatan naratif terhadap 10 artikel ilmiah terbitan tahun 2017–2025 yang diperoleh dari database PubMed, PubMed Central, SpringerLink, SINTA, JMIR Medical Informatics, dan Frontiers in Artificial Intelligence. Hasil kajian menunjukkan bahwa AI berperan penting dalam meningkatkan kualitas data, memprediksi kebutuhan klinis dan manajerial, serta mendukung evidence-based decision making di fasilitas kesehatan dan fasilitas pelayanan kesehatan primer. Namun, implementasi AI juga memiliki kelemahan, antara lain ketergantungan pada kualitas data, risiko bias algoritma, rendahnya interpretabilitas model, potensi ketergantungan berlebihan terhadap teknologi, serta risiko privasi dan keamanan data pasien. Oleh karena itu, pemanfaatan AI perlu disertai strategi antisipatif berupa penguatan tata kelola data, interoperabilitas sistem, validasi model, penerapan human in the loop, peningkatan literasi digital SDM, serta regulasi internal terkait etik dan keamanan data. Kesimpulannya, AI dapat menjadi instrumen strategis dalam proses DTI apabila diterapkan secara bertahap, kontekstual, aman, dan akuntabel.
From Crisis to Resilience: Lessons on Health Services, Financing, and Information Systems in the Philippines Delos Santos, Maricris; Alampay, Erwin; Rye, Ranjit
Jurnal Transformative: Ilmu Pemerintahan Vol. 12 No. 1 (2026): JUNE
Publisher : Faculty of Social and Political Science Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.transformative.2026.012.01.4

Abstract

This study introduces scientific novelty through an integrated analysis of four core pillars of the health system—service delivery, financing, health workforce, and information systems—which have often been examined separately, utilizing the COVID-19 pandemic as a 'critical event' lens (Das, 1995). Through a qualitative review of Philippine policies (2019–2025), this research successfully uncovers latent structural vulnerabilities that remain invisible under normal operating conditions. The findings reveal a recurring governance dilemma: centralized direction is effective for standard-setting and resource authorization, but counterproductive when intervening in the operational decisions of local government units (LGUs). This condition is further exacerbated by weak local fiscal readiness and poor health data interoperability. The policy implications of this study emphasize the urgency of transformative institutional reforms, including a clearer assignment of functions across all levels of LGUs, the codification of emergency budget flexibility, and the strengthening of national data system integration. Furthermore, the study recommends the formal integration of pandemic risks into the national Disaster Risk Management framework to foster adaptive health governance.
Sources of information available to senior secondary school student on the nutritional practices adopted in Delta State, Nigeria Oghenevwarhe Itagar; Juliana Ego Azonuche; Diana Oritsegbubemi Arubayi
Humanities Horizon Vol. 3 No. 2 (2026)
Publisher : PT. Pena Produktif Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63373/3047-8014/57

Abstract

Promoting healthy eating among youth is hindered by limited access to reliable dietary guidance, which often leads to poor nutritional practices and adverse long-term health outcomes among adolescents. This study adopted an ex-post facto, descriptive survey design in Delta State, Nigeria. Out of a population of 14,819 public senior secondary students across three senatorial zones, a sample of 390 students from 18 schools was selected using Slovin’s formula and multistage sampling. Data was collected via a validated, 4-point Likert scale questionnaire (Cronbach’s Alpha = 0.81) with a 100% retrieval rate. Analysis involved percentages, mean scores, standard deviations, and t-test statistics using SPSS version 22. Based on 390 respondents, senior secondary students agreed that television (M = 3.47), friends/classmates (M = 3.26), radio (M = 2.90), and social media (M = 2.76) are available nutritional information sources, exceeding the 2.50 cut-off. Conversely, they disagreed on home economics textbooks, newspapers, and fiction books (M = 2.23 – 2.40). Standard deviations ranged from 0.63 to 0.99. Hypothesis testing revealed a significant locational difference in information sources between urban (N = 219, M = 21.42, SD = 2.62) and rural (N = 171, M = 12.35, SD = 2.38) students. With t-cal = 35.32 and p = 0.00 (at alpha = 0.05), the null hypothesis was rejected. In conclusion, secondary students rely heavily on electronic and social media for nutritional knowledge, while print media remains ineffective. Significant urban-rural disparities highlight the urgent need for equitable, localized nutritional interventions.
Challenges and Opportunities for Christian Religious Education in the Development of Information Technology in Class IX Rahani Rahani; Karolina Karolina; Dwi Sartica; Urbanus Urbanus
EDUJAVARE: International Journal of Educational Research Vol. 4 No. 01 (2026): EDUJAVARE: International Journal of Educational Research
Publisher : CV. Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/edujavare.1448

Abstract

The rapid development of information technology has transformed almost every aspect of human life, including the educational sector. This study aims to analyze the challenges and opportunities of Christian Religious Education (CRE) in the development of information technology and to examine how teachers optimize technology integration in learning among Grade IX students at SMP Negeri 8 Palangka Raya. The study employed a descriptive qualitative approach, with data collected through interviews, observations, and documentation. The findings reveal that the major challenges faced by Christian Religious Education include students’ excessive use of digital devices, exposure to online content that may contradict Christian values, disparities in teachers’ digital competencies, and limitations in technological infrastructure. Despite these challenges, information technology provides significant opportunities to enhance access to religious learning resources, improve student engagement through interactive multimedia, facilitate collaborative learning, and support spiritual formation through digital faith-based platforms. The study also found that teachers optimize technology use by integrating multimedia resources into instruction, utilizing digital communication platforms, promoting digital literacy and ethical technology use, and continuously improving their technological and pedagogical competencies. The study concludes that the effective implementation of Christian Religious Education in the digital era requires a balanced approach that embraces technological innovation while maintaining the core mission of nurturing students’ faith, character, moral values, and spiritual development.
Digital Transformation in Strengthening the Pedagogic and Professional Competence of Madrasah Teachers through the Utilization of Service Administration Information System (SIAP) Muhibut Tibri; Rahmat Hidayat; Jamilus Jamilus
EDUJAVARE: International Journal of Educational Research Vol. 4 No. 01 (2026): EDUJAVARE: International Journal of Educational Research
Publisher : CV. Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/edujavare.1451

Abstract

The rapid development of digital technology has encouraged madrasahs to adopt information systems to improve educational services and teacher performance. This study aims to identify and analyze the planning, implementation, and evaluation of the utilization of the Administrative Service Information System (SIAP) in improving the pedagogical competence and professionalism of madrasah teachers. A qualitative approach with a case study design was employed. Research participants consisted of madrasah principals, teachers, SIAP operators, and administrative staff involved in system implementation. Data were collected through in-depth interviews, observations, and documentation studies and analyzed using the interactive model of Miles, Huberman, and Saldaña, including data condensation, data display, and conclusion drawing. The findings indicate that SIAP utilization was systematically planned through needs assessment, program design, infrastructure preparation, and user training. Its implementation improved administrative efficiency, facilitated access to educational information, reduced teachers’ administrative workload, and enabled greater focus on teaching and learning activities. Furthermore, the system contributed to enhancing teachers’ digital literacy and professional competence. Regular evaluation through monitoring, supervision, and user feedback helped identify challenges and improve system effectiveness. Overall, SIAP positively contributes to strengthening pedagogical competence, teacher professionalism, and the digital transformation of madrasah education.
Distribution of The #Indonesiagelap Information Network on Social Media in The Audience's Social Movement Against Government Regulations: Distribusi Jaringan Informasi #Indonesiagelap di Media Sosial dalam Gerakan Sosial Khalayak Terhadap Regulasi Pemerintah Radita Gora Tayibnapis; Ana Kuswanti; Tito Dos Santos Baptista Jr; Amaliyah Izzul Islam
Indonesian Journal of Innovation Studies Vol. 27 No. 3 (2026): July
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i3.2143

Abstract

General Background: Digital media has become a major arena for public protest, collective expression, political participation, and hashtag-based social movements. Specific Background: The #IndonesiaGelap movement emerged on social media as a public response to government regulations and policies perceived as unfavorable to society, and it circulated through platforms such as Twitter and TikTok. Knowledge Gap: The manuscript states that previous literature had not positioned #IndonesiaGelap as the main research object, while studies combining social movement analysis with network and survey approaches to identify negative communication remained limited. Aims: This study aimed to examine the distribution of information and communication networks around #IndonesiaGelap, identify actor roles, and analyze negative communication, hoax, and hate speech patterns using Network Society theory. Results: The study found that the social media network functioned as persuasive communication through unfiltered information and hate speech circulation. Actor networks appeared centralized, with driving actors forming sub-networks and anomalous accounts emerging within supporting clusters. Analysis of 64,816 comments on X showed 81% negative sentiment, 13% neutral sentiment, and 6% positive sentiment, with anger dominating negative comments at 22,482 comments. Novelty: The study focuses on #IndonesiaGelap through big data-based network analysis combined with survey logic. Implications: The findings support more transparent policy communication, dialogue-based governance responses, and deeper analysis of digital opinion leaders in contemporary social movements. Highlights: Big data mapping showed clustered actor roles and subgroups. Unfiltered information and hate speech circulated across platforms. Anomalous accounts appeared within supporting subclusters. Keywords: Social Movement, #Indonesiagelap, Social Network, Government Regulation
Web-Based Village Public Service Information System in Nambangan Selogiri Village Wonogiri Fahriza Wahyu Akbar; Wijiyanto Wijiyanto; Hanifah Permatasari
Journal of Artificial Intelligence and Software Engineering Vol 6, No 2 (2026): Juni (OnProgress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i2.9500

Abstract

Digital transformation at the village government level has become a crucial aspect of realizing efficient, transparent, and responsive public services. However, Nambangan Village currently faces administrative bottlenecks due to its reliance on a conventional service system. The process of issuing various certificates, such as the Certificate of Inability (SKTM), domicile letters, and cover letters, requires residents to physically visit the village hall. This practice leads to crowded queues, potential errors in population data recording, and low time efficiency in service delivery. This study aims to design and develop a web-based Village Public Service Information System that adapts to the operational needs of both village officials and the community of Nambangan Village. The system development method applied is the Software Development Life Cycle (SDLC) using the Waterfall model, which encompasses the stages of requirements analysis, system design, implementation, testing, and maintenance. The system is built using PHP, HTML, CSS, and JavaScript programming languages, supported by a MySQL database for integrated data management. The primary features implemented include online document submission, population data management, service tracking for village officials, public village information delivery, and a public grievance reporting system. Software quality assurance was functionally evaluated through the Black Box Testing method. The final outcome of this research is expected to provide an applicable technological solution for Nambangan Village to optimize public administrative governance and provide accessible services for the community without spatial or temporal constraints.
Implementation of SMOTE and Information Gain Feature Selection in Learning Vector Quantization for Asthma Disease Classification Diah Ayu Kinanti; Fitri Insani; Novi Yanti; Muhammad Affandes
Journal of Artificial Intelligence and Software Engineering Vol 6, No 2 (2026): Juni (OnProgress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i2.9354

Abstract

Asma adalah penyakit pernapasan akibat peradangan saluran udara di paru-paru yang menyebabkan penyempitan dan kesulitan bernapas. Prevalensinya terus meningkat secara global, sehingga diperlukan metode deteksi dini yang akurat. Masalah yang ditemukan dalam proses pengklasifikasian penyakit asma adalah distribusi kelas yang tidak seimbang pada dataset. Penelitian ini menerapkan algoritma Learning Vector Quantization (LVQ) yang dioptimalkan dengan seleksi fitur Information Gain dan teknik penyeimbangan data SMOTE untuk klasifikasi penyakit asma. Dataset penelitian mencakup 2.392 data pasien dengan 28 fitur dan 1 kelas target yang diperoleh dari platform Kaggle. Pengujian dilakukan pada lima skenario dengan tiga fungsi jarak Euclidean , Chebyshev, Manhattan, learning rate 0,001–0,005, dan rasio pembagian data 90:10, 80:20, serta 70:30. Hasil terbaik diperoleh pada skenario SMOTE, Information Gain, dan LVQ menggunakan fungsi jarak Euclidean  dengan learning rate 0.004 dan rasio 90:10, menghasilkan akurasi 77.97%, precision  73.61%, recall  87.22% dan F1-score 79.84%. Penerapan SMOTE menjadi komponen penting karena tanpa SMOTE model gagal mengenali kelas asma, terbukti pada percobaan tanpa menggunakan SMOTE menghasilkan precision , recall , dan F1-score bernilai 0% meskipun akurasi mencapai 94–95%.
Information Gain and Random Forest for Sex Classification Based on Craniometric Measurements Nabilla Alya Firana; Iis Afrianty; Novriyanto Novriyanto; Febi Yanto
Journal of Artificial Intelligence and Software Engineering Vol 6, No 2 (2026): Juni (OnProgress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i2.9409

Abstract

Sex identification from human skulls is a crucial aspect of forensic anthropology; however, traditional methods still face limitations such as subjective assessment and inter-population variation. This study proposes the application of Information Gain as a feature selection technique and Random Forest as a classification algorithm for sex determination based on craniometric data. The dataset used is the Howells dataset consisting of 2,524 samples with 83 skull measurement features. Feature selection using Information Gain was performed with threshold values of 0.01, 0.05, and 0.09, followed by additional testing across a threshold range of 0.01 to 0.09. Model evaluation was conducted using 10-Fold Cross Validation with default Random Forest parameters. The results show that a threshold of 0.02 produced 57 selected features from the original 83, achieving the best performance with an accuracy of 87.40%, precision of 87.53%, recall of 87.40%, and F1-score of 87.41%. These results outperform the baseline model without feature selection, which achieved an accuracy of 86.57%. This study demonstrates that Information Gain feature selection can reduce data dimensionality by 31.3% while simultaneously improving sex classification performance based on craniometric data.
Application of Information Gain Feature Selection and SMOTE in XGBoost Algorithm for Asthma Disease Classification Fioni Nikmatul Fajar; Fitri Insani; Suwanto Sanjaya; Iis Afrianty
Journal of Artificial Intelligence and Software Engineering Vol 6, No 2 (2026): Juni (OnProgress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i2.9384

Abstract

Asma merupakan salah satu penyakit kronis pada sistem pernapasan yang prevalensinya terus meningkat dan memerlukan deteksi dini untuk mencegah komplikasi serius. Salah satu tantangan dalam klasifikasi asma menggunakan machine learning adalah ketidakseimbangan kelas yang menyebabkan model cenderung memprediksi kelas mayoritas sehingga kemampuan mendeteksi kasus asma menjadi rendah. Penelitian ini mengusulkan penerapan SMOTE dan seleksi fitur Information Gain dalam algoritma XGBoost untuk mengatasi permasalahan tersebut. Dataset yang digunakan terdiri dari 2.392 data dengan 28 atribut, di mana tahapan penelitian meliputi preprocessing, seleksi fitur menggunakan Information Gain yang mengurangi fitur menjadi 22 fitur, penyeimbangan data menggunakan SMOTE, pembagian data dengan rasio 90:10, 80:20, dan 70:30, serta klasifikasi menggunakan XGBoost. Pengujian dilakukan terhadap empat skenario pendekatan untuk membandingkan kontribusi setiap metode yang diterapkan. Evaluasi dilakukan menggunakan data uji seimbang dan data uji asli dengan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa skenario terbaik diperoleh pada kombinasi Information Gain + SMOTE + XGBoost dengan rasio 90:10 pada data uji seimbang, menghasilkan akurasi 75%, presisi 87,5%, recall 58,33%, dan F1-score 70%. Hasil tersebut menunjukkan bahwa kombinasi seleksi fitur dan penyeimbangan data mampu meningkatkan kemampuan model dalam mendeteksi penyakit asma.

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