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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Hukum Bisnis Bonum Commune Jurnal Teknik Informatika UNIKA Santo Thomas JURNAL KESEHATAN SAMODRA ILMU Parta: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Applied Science and Technology Research Journal Nemui Nyimah
Verdiana, Miranti
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RESIKO MEDIK DOKTER DALAM OPERASI MATA YANG MENGAKIBATKAN KEBUTAAN Narayana, Panca; Dayati, Judhith Vidya; Verdiana, Miranti
Jurnal Hukum Bisnis Bonum Commune Volume 3, Nomor 2 Agustus 2020
Publisher : Faculty of Law, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jhbbc.v3i2.3991

Abstract

AbstractThe research objective is the impersonal relationship between doctor and patient who have a balanced relationship. Using normative research with an orientation that is not based on conceptual. Through this research the researcher offers that the notification center is the medical law and health law. Medical law is a law that regulates the relationship between a doctor and a patient in carrying out medical actions with semantics that may not be ascertained, together with medical compensation that cannot be predicted and does not cause the ability or skill of a doctor, on that basis cannot be sued or convicted. Thus, Medical Practice has provided clear information that will cause and every action needed to be truly needed, allows patients to take compensation. Clinics as providers of care facilities can be sued for not being able to meet patients. The clinic has personnel responsibilities, professional quality of treatment, facilities and equipment, and safety of treatment.Keywords: informed consent; medical risk; medical; informed consentAbstrakTujuan penelitian yaitu hubungan impersonal antara dokter dengan pasien yang memiliki hubungan yang seimbang. Menggunakan penelitian normatif dengan orientasi yang tidak bersumber pada konseptual. Melalui penelitian ini peneliti menawarkan bahwa pusat pemberitahuan adalah Undang-Undang Kedokteran dan Undang-Undang Kesehatan. Hukum kedokteran adalah hukum yang mengatur hubungan dokter dengan pasien didalam melakukan tindakan medis dengan upaya yang semaksimal mungkin yang hasilnya tidak dapat dipastikan, sama dengan resiko medik merupakan kerugian yang tidak dapat diramalkan dan bukan akibat kurangnya kemampuan atau ketrampilan dokter, atas dasar itu dokter tidak dapat digugat atau dipidana. Undang-Undang Praktik Kedokteran telah memberikan penjelasan mengenai resiko-resiko yang akan timbul dan setiap tindakan yang mengandung resiko tinggi harus ada persetujuan tertulis, apabila pasien melakukan persetujuan tertulis maka dokter tidak dapat diminta ganti rugi. Klinik sebagai penyedia sarana pengobatan dapat digugat apabila tidak memenuhi kebutuhan pasien. Klinik mempunyai tanggungjawab personalia, professional terhadap mutu pengobatan, sarana dan peralatan dan keamanan terhadap perawatannya.Kata kunci: kedokteran: resiko medis; tindakan medik
GAMBARAN KARAKTERISTIK IBU MENYUSUI DALAM PEMBERIAN ASI EKSKLUSIF Verdiana, Miranti; Kuswanti, Ina; Rochmawati, Lusa
Jurnal Kesehatan Samodra Ilmu (JKSI) Vol 11 No 1 (2020): JURNAL KESEHATAN SAMODRA ILMU (JKSI)
Publisher : LPPM Sekolah Tinggi Ilmu Kesehatan Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55426/jksi.v11i1.9

Abstract

Latar Belakang: Pemberian ASI memberikan manfaat bagi bayi baru lahir merupakan salah satu untuk mencegah kematian dan masalah kekurangan gizi pada bayi dan balita. Bagi bayi yang diberikan ASI eksklusif akan terhindar dari resiko kematian akibat diare dan ISPA. Karakteristik ibu yang dapat mempengaruhi keberhasilan pemberian ASI eksklusif tersebut berupa usia, tingkat pendidikan, pekerjaan, dan paritas. Menurut Prof Dinkes Kesehatan di DIY 2017 cakupan pemberian ASI eksklusif sebesar 74,90%. Tujuan: Untuk mengetahui gambaran karakteristik ibu menyusui dalam pemberian ASI eksklusif di Puskesmas Umbulharjo I Yogyakarta. Metode: Jenis penelitian ini deskriptif dengan pendekatan cross sectional. Teknik pengambilan sampling secara purposive dengan jumlah sampel 55 orang ibu yang menyusui. Data yang digunakan data sekunder. Instrumen berupa lembar observasi. Analisa data secara univariat, hasil disajikan dalam bentuk distribusi frekuensi. Hasil: Karakteristik ibu menyusui dalam pemberian ASI eksklusif berdasarkan pekerjaan yaitu sebagian besar ibu yang bekerja 37 responden (67,3%), sebagian besar pendidikan SMA 27 responden (49,1%), sebagian besar dalam kategori resiko tinggi <20 & >35 tahun (61,8%), dan sebagian besar memiliki paritas (primipara) sebanyak 21 responden (38,2%). Kesimpulan: Sebagian besar ibu yang menyusui dalam pemberian ASI eksklusif di Puskesmas Umbulharjo I dikarenakan pekerjaan ibu termasuk kategori ibu bekerja.
Comparative Analysis of OpenMP and MPI Parallel Computing Implementations in Team Sort Algorithm Nugroho, Eko Dwi; Ashari, Ilham Firman; Nashrullah, Muhammad; Algifari, Muhammad Habib; Verdiana, Miranti
Journal of Applied Informatics and Computing Vol. 7 No. 2 (2023): December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i2.6409

Abstract

Tim Sort is a sorting algorithm that combines Merge Sort and Binary Insertion Sort sorting algorithms. Parallel computing is a computational processing technique in parallel or is divided into several parts and carried out simultaneously. The application of parallel computing to algorithms is called parallelization. The purpose of parallelization is to reduce computational processing time, but not all parallelization can reduce computational processing time. Our research aims to analyse the effect of implementing parallel computing on the processing time of the Tim Sort algorithm. The Team Sort algorithm will be parallelized by dividing the flow or data into several parts, then each sorting and recombining them. The libraries we use are OpenMP and MPI, and tests are carried out using up to 16 core processors and data up to 4194304 numbers. The goal to be achieved by comparing the application of OpenMP and MPI to the Team Sort algorithm is to find out and choose which library is better for the case study, so that when there is a similar case, it can be used as a reference for using the library in solving the problem. The results of research for testing using 16 processor cores and the data used prove that the parallelization of the Sort Team algorithm using OpenMP is better with a speed increase of up to 8.48 times, compared to using MPI with a speed increase of 8.4 times. In addition, the increase in speed and efficiency increases as the amount of data increases. However, the increase in efficiency that is obtained by increasing the processor cores decreases.
Development of YOLO-Based Mobile Application for Detection of Defect Types in Robusta Coffee Beans Nugroho, Eko Dwi; Verdiana, Miranti; Algifari, Muhammad Habib; Afriansyah, Aidil; Firmansyah, Hafiz Budi; Rizkita, Alya Khairunnisa; Winarta, Richard Arya; Gunawan, David
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8886

Abstract

Improving the quality of Robusta coffee beans is a crucial challenge in the coffee industry to ensure that consumers receive high-quality products. However, the identification of defects in coffee beans is still largely performed manually, making the process error-prone and time-consuming. This study aims to develop a YOLO-based mobile application to detect defects in Robusta coffee beans quickly and accurately. The method employed in this study is YOLO, a deep learning-based object detection algorithm known for its real-time object detection capabilities. The application was tested using a dataset of Robusta coffee beans containing various defects, such as broken, black, and wrinkled beans. The test results indicate that the application achieves high detection accuracy, with the black bean class achieving 95.3% accuracy, while the moldy or bleached bean class records the lowest accuracy at 62.2%. This application is expected to assist farmers and coffee industry stakeholders in improving the quality of Robusta coffee beans and enhancing the efficiency of the sorting process.
Evaluasi Logistic Regression dan Neural Network pada Klasifikasi Gagal Jantung Berbasis Threshold Anggraini, Leslie; Akram Abdillah, Attar; Kartadilaga, Muhammad Qaessar; Verdiana, Miranti; Nugroho, Eko; Afriansyah, Aidil; Febrianto, Andre; Bagaskara, Radhinka
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 10 No. 1 : Tahun 2025
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kardiovaskular adalah sistem jantung dan pembuluh darah dalam tubuh manusia yang bertanggung jawab atas sirkulasi darah dalam jantung, pembuluh darah, dan darah sendiri. Gangguan pada fungsi sistem ini dapat menyebabkan penyakit kardiovaskular, seperti gagal jantung, yang menjadi salah satu penyebab utama kematian di seluruh dunia. Kematian yang disebabkan oleh gagal jantung mempengaruhi 1.5 juta pasien di seluruh dunia. Dikarenakan oleh data statistik tersebut, maka ada kebutuhan untuk dapat memprediksi dampak gagal jantung untuk membantu tingkat kelangsungan hidup pasien. Sebagai bentuk kontribusi terhadap kebutuhan tersebut, penelitian ini akan menganalisis sebuah dataset pelayanan kesehatan, yaitu dataset rekam gagal jantung dari UCI. Dataset tersebut akan digunakan untuk mengklasifikasi dan memprediksi peluang kematian dari pasien gagal jantung. Kami akan membandingkan antara dua metode klasifikasi dari machine learning, yaitu Logistic Regression (LR), dan deep learning, yaitu Shallow Neural Network (SNN). Mutual Information (MI) dipilih sebagai metode pemilihan fitur. Hasil menunjukkan bahwa SNN menghasilkan akurasi lebih tinggi dengan skor 0.75, dibandingkan LR dengan akurasi sebesar 0.63.
Analisis Hubungan dan Prediksi Depresi Mahasiswa Berdasarkan Faktor Akademik dan Gender Verdiana, Miranti; Dwi Nugroho, Eko; Anggraini, Leslie; Bagaskara, Radhinka; Yulita, Winda; Afriansyah, Aidil; Habib Algifari, Muhammad
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 10 No. 1 : Tahun 2025
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to analyze the level of depression among university students by examining gender and several academic indicators. The dataset includes responses from 27,901 students across various regions, with variables covering age, gender, academic pressure, study satisfaction, work/study hours, CGPA, and depression status. The analytical methods applied in this study include the chi-square test to eval_uate the association between gender and depression status, point-biserial correlation to examine relationships between numeric variables and depression, and logistic regression to develop a prediction model. The chi-square test results revealed no significant relationship between gender and depression (p = 0.774), indicating that depression affects both genders. In contrast, academic pressure exhibited the strongest correlation with depression status (r = 0.47), followed by work/study hours (r = 0.209) and study satisfaction (r = -0.168). The Logistic Regression model constructed using the four most relevant variables demonstrated satisfactory performance, achieving 75.5% accuracy and 82.1% recall in identifying students experiencing depression. These findings highlight the critical role of academic-related factors—particularly academic pressure—in influencing students’ mental health. Therefore, targeted academic support strategies are essential to mitigate depression risks in higher education environments. Keywords— Student Depression, Academic Pressure, Gender, Logistic Regression, Mental Health Prediction
Evaluasi Logistic Regression dan Neural Network pada Klasifikasi Gagal Jantung Berbasis Threshold Anggraini, Leslie; Akram Abdillah, Attar; Kartadilaga, Muhammad Qaessar; Verdiana, Miranti; Nugroho, Eko; Afriansyah, Aidil; Febrianto, Andre; Bagaskara, Radhinka
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 10 No. 1 : Tahun 2025
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kardiovaskular adalah sistem jantung dan pembuluh darah dalam tubuh manusia yang bertanggung jawab atas sirkulasi darah dalam jantung, pembuluh darah, dan darah sendiri. Gangguan pada fungsi sistem ini dapat menyebabkan penyakit kardiovaskular, seperti gagal jantung, yang menjadi salah satu penyebab utama kematian di seluruh dunia. Kematian yang disebabkan oleh gagal jantung mempengaruhi 1.5 juta pasien di seluruh dunia. Dikarenakan oleh data statistik tersebut, maka ada kebutuhan untuk dapat memprediksi dampak gagal jantung untuk membantu tingkat kelangsungan hidup pasien. Sebagai bentuk kontribusi terhadap kebutuhan tersebut, penelitian ini akan menganalisis sebuah dataset pelayanan kesehatan, yaitu dataset rekam gagal jantung dari UCI. Dataset tersebut akan digunakan untuk mengklasifikasi dan memprediksi peluang kematian dari pasien gagal jantung. Kami akan membandingkan antara dua metode klasifikasi dari machine learning, yaitu Logistic Regression (LR), dan deep learning, yaitu Shallow Neural Network (SNN). Mutual Information (MI) dipilih sebagai metode pemilihan fitur. Hasil menunjukkan bahwa SNN menghasilkan akurasi lebih tinggi dengan skor 0.75, dibandingkan LR dengan akurasi sebesar 0.63.
Analisis Hubungan dan Prediksi Depresi Mahasiswa Berdasarkan Faktor Akademik dan Gender Verdiana, Miranti; Dwi Nugroho, Eko; Anggraini, Leslie; Bagaskara, Radhinka; Yulita, Winda; Afriansyah, Aidil; Habib Algifari, Muhammad
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 10 No. 1 : Tahun 2025
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to analyze the level of depression among university students by examining gender and several academic indicators. The dataset includes responses from 27,901 students across various regions, with variables covering age, gender, academic pressure, study satisfaction, work/study hours, CGPA, and depression status. The analytical methods applied in this study include the chi-square test to eval_uate the association between gender and depression status, point-biserial correlation to examine relationships between numeric variables and depression, and logistic regression to develop a prediction model. The chi-square test results revealed no significant relationship between gender and depression (p = 0.774), indicating that depression affects both genders. In contrast, academic pressure exhibited the strongest correlation with depression status (r = 0.47), followed by work/study hours (r = 0.209) and study satisfaction (r = -0.168). The Logistic Regression model constructed using the four most relevant variables demonstrated satisfactory performance, achieving 75.5% accuracy and 82.1% recall in identifying students experiencing depression. These findings highlight the critical role of academic-related factors—particularly academic pressure—in influencing students’ mental health. Therefore, targeted academic support strategies are essential to mitigate depression risks in higher education environments. Keywords— Student Depression, Academic Pressure, Gender, Logistic Regression, Mental Health Prediction
Digitalisasi Informasi Sebagai Penunjang Efektivitas Pelayanan Administrasi Koperasi Argo Mulyo Lestari Untoro, Meida Cahyo; Kurniawansyah, Apri; Perdana, Agung Mahadi Putra; Praseptiawan, Mugi; Nugroho, Eko Dwi; Afriansyah, Aidil; Yulita, Winda; Verdiana, Miranti
Parta: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/parta.v4i2.4588

Abstract

Koperasi memiliki peran penting dalam perekonomian Indonesia. Argo Mulyo Lestari, salah satu koperasi yang mengelola dan menyediakan bibit pohon dan buah-buahan serta melakukan pendistribusian keseluruh wilayah Indonesia. Hasil observasi dengan cara wawancara mendapatkan data tentang proses bisnis yang dilakukan koperasi masih tergolong kuno, dengan cara mencatat pada buku, menyimpan pada excel. Proses bisnis yang tidak diimbangi dengan Teknologi informasi dan komunikasi mengakibatka, terjadi duplikasi data dan akses terbatas bagi seluruh anggota koperasi. Tim pengusul membuat usulan untuk menyelesaikan permasalahan dengan cara Teknologi Tepat Guna Digitalisasi Administrasi Koperasi Argo Mulyo Lestari. Tujuan dari digitalisasi, mempermudah, meningkatkan, dan keterbukaan data dalam melaksanakan proses bisnis. Digitalisasi mencangkup proses bisnis administrasi umum, simpan pinjam, keuangan dan pelaporan keuntungan serta kerugian. Teknologi tepat guna akan dievaluasi dengan menggunakan usability test. Hasil dari pengambdian, koperasi Argo Mulyo Lestari sudah menerapkan digitalisasi teknologi yang transparan, dan bertanggung jawab. Digitalisasi administrasi merupakan langkah yang tepat dalam menghadapi perkembangan teknologi informasi yang semakin canggih.
Rancang Bangun Sistem Inventaris pada UMKM Girimulyo, Kabupaten Lampung Timur Anggraini, Leslie; Bagaskara, Radhinka; Verdiana, Miranti; Afriansyah, Aidil; Idris, Mohamad
Nemui Nyimah Vol. 5 No. 1 (2025): Nemui Nyimah Vol. 5 No. 1 2025
Publisher : FT Universitas Lampung

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Abstract

We discuss the design and implementation of an Inventory Management System developed specifically for Javamart Girimulyo to enhance accuracy and efficiency in stock control. The primary objective of the system is to automate inventory tracking, monitor stock levels in real time, and generate detailed inventory reports, thus minimizing manual errors and improving overall inventory oversight. The development followed the Modified Waterfall methodology, which provided a clear and systematic process across stages of requirements gathering, system design, coding, testing, and deployment. Key functionalities include automatic stock updates upon item inflow and outflow, low-stock alerts, flexible item categorization, and secure access controls for administrators. The system also offers an intuitive graphical user interface and integrates with a MySQL database backend to ensure data reliability and consistency. Testing outcomes indicate that the system delivers the necessary performance and stability, confirming its suitability for deployment. By digitizing and streamlining stock management processes, this project offers a practical and scalable solution to support inventory operations at Javamart Girimulyo.
Co-Authors Afriansyah, Aidil Akram Abdillah, Attar Algifari, Muhammad Habib Anggraini, Leslie Bagaskara, Radhinka David Gunawan, David Dayati, Judhith Vidya Dwi Nugroho, Eko Eko Dwi Nugroho Eko Nugroho Febrianto, Andre Firmansyah, Hafiz Budi Habib Algifari, Muhammad Idris, Mohamad Ilham Firman Ashari Ina Kuswanti Kurniawansyah, Apri Lusa Rochmawati Muhammad Qaessar Kartadilaga Narayana, Panca Nashrullah, Muhammad Perdana, Agung Mahadi Putra Praseptiawan, Mugi Rizkita, Alya Khairunnisa Untoro, Meida Cahyo Winarta, Richard Arya Yulita, Winda