Citation Analysis

Lianzi, I., & Pitaloka, E. (2024). Hubungan Pengetahuan Tentang Rokok dan Perilaku Merokok Pada Staf Administrasi Universitas Esa Unggul. Jurnal Inohim, 2(1), 67–81. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208612419&partnerID=40&md5=442ff3b15783bff8a52c59ee40a3c22c

Suadnyana, I. A. A., Negara, N. L. G. A. M., & Wiraguna, I. W. (2023). The relationship between smoking dose with oxygen saturation and cardiorespiratory endurance on young adult men. Physical Therapy Journal of Indonesia, 4(1), 50–54. https://doi.org/10.51559/ptji.v4i1.75

Puteri, F. S., Achmad, N., & Sa’diyah, R. (2022). Determinants of Smoking Behavior in Workers Handling Public Facilities and Infrastructure (PPSU) Rambutan Village Jakarta. Media Publikasi Promosi Kesehatan Indonesia, 5(3), 265–271. https://doi.org/10.56338/mppki.v5i3.2045

 

Widiyanto, W. W. (2022). SIMRS Network Security Simulation Using Snort IDS and IPS Methods. Indonesian of Health Information Management Journal (INOHIM), 10(1), 10–17. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174605024&partnerID=40&md5=7c357e9be5e2cb0d5e8ebe20684661db

Jáuregui-Velarde, R., Celis, D. H., Arias, C. Y., & Andrade-Arenas, L. (2023). A critical review of the state of computer security in the health sector. Bulletin of Electrical Engineering and Informatics, 12(6), 3805–3816. https://doi.org/10.11591/eei.v12i6.5394

 

Kurniato, E., Putra, D. H., Fannya, P., & Dewi, D. R. (2021). Tinjauan Karakteristik dengan Kasus Positif Covid-19 di Puskesmas Kecamatan Matraman. Indonesian of Health Information Management Journal (INOHIM), 9(2), 102–108. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174413516&partnerID=40&md5=3c3c51a466459690b01ca0c9723ef9c6

Aulia, G., Fadhilah, H., Amalia, T. R., Indah, F. P. S., & Poddar, S. (2023). Relationship Between Patient Characteristics and Severity With the Use of Antiviral Drugs Among Covid-19 Patients at Rumah Sakit Ichsan Medical Centre Bintaro. Malaysian Journal of Medicine and Health Sciences, 19, 121–125. https://doi.org/10.47836/mjmhs.19.s9.18

Sitompul, T. H., Meilani, P., Salsabila, S., & Hariwangi, L. L. (2021). SILACAK: Bagaimana Penggunaan Aplikasi Pelacakan Kasus Kontak Erat COVID-19 di Indonesia. Indones Heal Inf Manag J, 9(2), 127–137. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179163084&partnerID=40&md5=1517855464ab30f347230181bc435529

Heriana, C., & Said, F. B. M. (2023). Evaluation of Functionally and Usability Case Tracing Information System (Silacak App) Covid-19 in Indonesia. AIP Conference Proceedings, 2854(1). https://doi.org/10.1063/5.0164143

 

Rahayu, S., & Hosizah, H. (2021). Implementasi Sistem Rujukan Layanan Kesehatan: Systematic Literature Review. Indonesian of Health Information Management Journal INOHIM, 9(2), 138–152. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105001660623&partnerID=40&md5=22f9cef137d26968ec65eb78082f4a40

Yani, M. F., Ramadani, L., & Mukti, I. Y. (2024). Enhancing Community Development with Information and Communication Technology: An In-Depth Analysis of Successful Strategies and Approaches. 2024 International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024, 93–98. https://doi.org/10.1109/ICICYTA64807.2024.10912996

 

Nurmalasari, M., Temesvari, N. A., & Maula, S. N. (2020). Analisis Sentimen terhadap Opini Masyarakat dalam Penggunaan Mobile-JKN untuk Pelayanan BPJS Kesehatan Tahun 2019. Indonesian of Health Information Management Journal (INOHIM), 8(1), 35–44. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105001623119&partnerID=40&md5=8c9931290b05fa6b36fc18cfab635895

Lusiani, S., & Princes, E. (2024). Evaluating the Effectiveness of Mobile JKN Application in Indonesia: A User-Centric Approach Using the ISO 25010 Quality Model. Journal of Logistics, Informatics and Service Science, 11(10), 485–500. https://doi.org/10.33168/JLISS.2024.1028

 

Noviandi, N. (2018). Implementasi algoritma decision tree C4.5 untuk prediksi penyakit diabetes. Jurnal INOHIM, 6(1), 1–5. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147729066&partnerID=40&md5=965bcd09260a1ee47dc032eb19b0cbec

Dewi, A. M., & Zarlis, M. (2020). Optimization of Smooth Support Vector Machine Algorithm Using Backpropagation Nguyen Widrow Algorithm in Classification of Mellitus Diabetes Disease. MECnIT 2020 - International Conference on Mechanical, Electronics, Computer, and Industrial Technology, 132–136. https://doi.org/10.1109/MECnIT48290.2020.9166628       

Anggoro, D. A., & Permatasari, D. (2023). Performance Comparison of the Kernels of Support Vector Machine Algorithm for Diabetes Mellitus Classification. International Journal of Advanced Computer Science and Applications, 14(1), 580–585. https://doi.org/10.14569/IJACSA.2023.0140163

Fauziah, S., Renaldi, F., & Santikarama, I. (2022). Prediction of Length of Stay and Cost for Diabetes Inpatient using C4.5 Algorithm. 2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022. https://doi.org/10.1109/ICCIT55355.2022.10118754

 

Ulfa, H. M. (2018). Analisa kelengkapan informed consent tindakan operasi DI rumah sakit sansani pekanbaru. J Inohim, 6(1), 22. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135410255&partnerID=40&md5=3d5eb5bf2763b9182e5abfb2ba543979

Cahya, R., & Wibowo, A. (2023). A Well-understood Surgical Informed Consent: A Scoping Review. Unnes Journal of Public Health, 12(1), 21–32. https://doi.org/10.15294/ujph.v12i1.57731 

Firdaus, S. U. (2022). The urgency of legal regulations existence in case of COVID-19 vaccination refusal in Indonesia. Journal of Forensic and Legal Medicine, 91. https://doi.org/10.1016/j.jflm.2022.102401

 

Fithri, N. K. (2017b). Analisis faktor yang mempengaruhi gangguan fungsi paru pada pekerja penjaga pintu tol Tangerang Karawaci (Analysis of factors that affect lung function disorders in Tangerang Karawaci toll gate attendants). Jurnal INOHIM, 5(1). https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200009961&partnerID=40&md5=4a7ee9cbca8247cb621c3910b1fc11fb

Maharja, R., Gani, H., Maharja, R., Syamsul, M. A., Latief, A. W. L., Juliani, A., Anas, M., & Bahar, S. N. (2023). Study of Lung Function Disorders of Headstone and Stone Mortar Crafters and Factors That Affect Them. Malaysian Journal of Medicine and Health Sciences, 19(6), 208–214. https://doi.org/10.47836/mjmhs.19.6.28

 

Indawati, L. (2017). Identifikasi Unsur 5M Dalam Ketidaktepatan Pemberian Kode Penyakit dan Tindakan (Systematic Review). Jurnal INOHIM, 5(2). https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056159997&partnerID=40&md5=ea89c9035a8c7f0c23609e14d5001566

Ningsih, E. R., Mohammad, I., Marlinae, L., Arifin, S., & Soediono, J. B. (2018). Quality of medical record document management system in banjarmasin islamic hospital installation in 2017. Indian Journal of Public Health Research and Development, 9(10), 504–508. https://doi.org/10.5958/0976-5506.2018.01395.5

 

Rumana, N. A., Sitoayu, L., & Sa’pang, M. (2018). Korelasi Kadar Gula Darah Puasa Terhadap Kualitas Hidup Pasien Diabetes Mellitus Type 2 di Puskesmas Jakarta Barat Tahun 2018. Indonesian of Health Information Management Journal (INOHIM), 6, 41–45. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152102634&partnerID=40&md5=b9543281ab97c65aefad163b133aba3a

Widowati, N., & Ningtyias, F. W. (2024). Analysis of Maternal Factors with the Incidence of LBW Infants at Situbondo Health Center: Study of Cohort Register Data in 2020. Amerta Nutrition, 8(3), 368–375. https://doi.org/10.20473/amnt.v8i3.2024.368-375

 

Fithri, N. K. (2016). Hygiene and sanitation of food handlers at esa unggul university canteen. INOHIM Journal, 4(2), 55–65. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054526493&partnerID=40&md5=43cadc7e14e102ce1711b5f55d7a8744

Siagian, A., Julianti, E., & Setianingsih, R. M. (2018). The environmentally sound management model for catering service. International Journal of Civil Engineering and Technology, 9(9), 666–680. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054505288&partnerID=40&md5=438437f36594774980f386d30dd1a154

 

Rachman, F. F., & Pramana, S. (2020). Analisis Sentimen Pro dan Kontra Masyarakat Indonesia tentang Vaksin COVID-19 pada Media Sosial Twitter. Indonesian of Health Information Management Journal, 8(2), 100–109.

Abdurrahim, A., Syafa’ah, L., & Lestandy, M. (2022). Sentiment analysis of Covid-19 vaccine tweets utilizing Naïve Bayes. AIP Conference Proceedings, 2453. https://doi.org/10.1063/5.0094607

Agustiningsih, K. K., Utami, E., & Al Fatta, H. (2021). Sentiment Analysis of COVID-19 Vaccine on Twitter Social Media: Systematic Literature Review. Proceedings - 2021 IEEE 5th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Science and Artificial Intelligence Technologies for Global Challenges During Pandemic Era, ICITISEE 2021, 121–126. https://doi.org/10.1109/ICITISEE53823.2021.9655960

Alvinika, Y., Prasetyo, W., & Mudjihartono, P. (2022). Analysis of Twitter User’s Sentiment Against COVID-19 Vaccination Using the Lexicon Based Method. Lecture Notes in Networks and Systems, 420 LNNS, 13–19. https://doi.org/10.1007/978-3-030-96305-7_2

Amin, A. R. M., Syatar, A., Abubakar, A., & Alimuddin, H. (2024). Between Ḍarūrah and Halal Integrity: MUI Fatwas on Harm-Derived Vaccines and Medicines. Samarah, 8(2), 1239–1256. https://doi.org/10.22373/sjhk.v8i2.8938

Atabik, A., & Muqtada, M. R. (2024). Maqashid Quran’s critical view on Indonesian Ulema Council’s fatwa on Halal certification of COVID-19 vaccine. HTS Teologiese Studies / Theological Studies, 80(1). https://doi.org/10.4102/hts.v80i1.9050

Azis, A. (2021). Application of the Vector Machine Support Method in Twitter Social Media Sentiment Analysis Regarding the Covid-19 Vaccine Issue in Indonesia. Journal of Applied Data Sciences, 2(3), 102–108. https://doi.org/10.47738/jads.v2i3.40

Fitriyah, Z., & Kartikasari, M. D. (2023). Text Classification Of Twitter Opinion Related To Permendikbud 30/2021 Using Bidirectional LSTM. Barekeng, 17(2), 1113–1122. https://doi.org/10.30598/barekengvol17iss2pp1113-1122

Haay, H. A., & Setiawan, A. (2022). Latent dirichlet allocation (Lda) method analysis about covid-19 vaccine on twitter social media. Barekeng, 16(1), 189–198. https://doi.org/10.30598/barekengvol16iss1pp189-196

Hadiyanto, H., Suryadin, A., Mulyadi, E., Rhamadani, A. F., Saepul, M., Said, F. B. M., & Hassan, H. C. (2022). Knowledge Survey of Coronavirus Disease (Covid-19) Prevention and Vaccination in Sukabumi, West Java, Indonesia. Malaysian Journal of Medicine and Health Sciences, 18, 67–69. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124606334&partnerID=40&md5=57993f9e53fab0b303c92bba5f4caa7c

Hasti, I., Nurmandi, A., Muallidin, I., & Kurniawan, D. (2022). Pros and Cons of Vaccine Program in Indonesia (Social Media Analysis on Twitter). Lecture Notes in Networks and Systems, 319, 100–107. https://doi.org/10.1007/978-3-030-85540-6_13

Kurniawan, K. D., Bachtiar, H., & Al-Fatih, S. (2024). Utilitarian Policy of Criminalization for the COVID-19 Vaccine Refusal in Indonesia. Jurnal Media Hukum, 31(1), 134–149. https://doi.org/10.18196/jmh.v31i1.21564

Latifah, R., Baddalwan, R., Meilina, P., Saputra, A. D., & Adharani, Y. (2021). Sentiment Analysis of COVID-19 Vaccines from Indonesian Tweets and News Headlines using Various Machine Learning Techniques. Proceedings - 3rd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021, 69–73. https://doi.org/10.1109/ICIMCIS53775.2021.9699187

Lestandy, M., Abdurrahim, A., & Syafa’ah, L. (2021). Analisis Sentimen Tweet Vaksin COVID-19 Menggunakan Recurrent Neural Network dan Naïve Bayes. Jurnal RESTI, 5(4), 802–808. https://doi.org/10.29207/resti.v5i4.3308

Maylawati, D. S., Arianti, N. D., Septiadi, M. A., Hay’s, R. N., Annisa, N. N., & Ramdani, Z. (2022). Social-Politic in a Pandemics Indonesian Citizens’ Twitter Conversation Analysis using Latent Dirichlet Allocation. Proceeding of 2022 8th International Conference on Wireless and Telematics, ICWT 2022. https://doi.org/10.1109/ICWT55831.2022.9935415

Prakoso, D. A. A., Hermawan, D., & Efendi, A. M. (2023). Analysis of the Effects Using BERT Feature Extraction Method on Case of Sentiment Classification on Twitter Social Media. 2023 1st IEEE International Conference on Smart Technology: Advances in Smart Technology for Sustainable Well-Being, ICE-SMARTec 2023, 54–59. https://doi.org/10.1109/ICE-SMARTECH59237.2023.10461978

Silalahi, S. F., Arini, H. M., & Mulyani, Y. P. (2023). Topic modelling and sentiment analysis during Covid-19 pandemic response: A systematic review. AIP Conference Proceedings, 2654. https://doi.org/10.1063/5.0117344

Stephanie, E. M. A., Ruiz, L. G. B., Vila, M. A., & Pegalajar, M. C. (2024). Study of violence against women and its characteristics through the application of text mining techniques. International Journal of Data Science and Analytics, 18(1), 35–48. https://doi.org/10.1007/s41060-023-00448-y

Utama, F. R., Maylawati, D. S., Syaripudin, U., Ramdania, D. R., Nurlatifah, E., & Septiadi, M. A. (2023). Sentiment Analysis Regarding the Name of “Nusantara” in Indonesia’s New Capital City Using Convolutional Neural Network. 2023 IEEE 9th International Conference on Computing, Engineering and Design, ICCED 2023. https://doi.org/10.1109/ICCED60214.2023.10425579

Wiryawan, I. W. G. (2021). Vaccines for Tourism Business Actors: Fulfilment or Violation of Human Rights? Padjadjaran Jurnal Ilmu Hukum, 8(3), 401–416. https://doi.org/10.22304/pjih.v8n3.a5