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All Journal Abdi Laksana : Jurnal Pengabdian Kepada Masyarakat Jurnal Computer Science and Information Technology (CoSciTech) Sevaka: Hasil Kegiatan Layanan Masyarakat
Hafizhah Mardivta
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Health Professions Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Penerapan metode forward chaining dan certainty factor untuk mengetahui gangguan mental pada remaja Hafizhah Mardivta
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6716

Abstract

Mental disorders are a condition where people have mental, social, growth and development problems or disorders that hinder their life processes and interactions with other people. Mental health can be influenced by several factors, for example friendships, family, lifestyle, and many other factors. Many people do not want to undergo mental examinations from psychologists due to several factors, namely people feel embarrassed and afraid to talk about their problems, lack of knowledge of the symptoms and types of mental disorders, and fear of the surrounding environment. One way to help overcome this problem is to use an expert system. This expert system was built to determine mental disorders in adolescents using the Forward Chaining and Certainty Factor methods. The Forward Chaining method will be collaborated with the Certainty Factor method to calculate the level of accuracy of the type of mental disorder experienced. The use of these two methods aims to provide better results in identifying mental disorders in adolescents. The data taken in this research is data on mental disorders at the UPI YPTK Psychology Institute. The data used consists of 50 symptom data and 7 disease data. The results of this research are an Expert System application using the PHP programming language which is used to determine mental disorders in adolescents. From the tests that have been carried out, results were obtained with an accuracy level of 0.9998%. Expert system applications can be used for early action in preventing mental disorders in adolescents.
Penyuluhan Klasifikasi Risiko Infertilitas Pada Pasien Wanita Berdasarkan Data Rekam Medis Menggunakan Algoritma Naive Bayes Fahruzi Sirait; Hafizhah Mardivta; Nailatun Nadrah; Nadya Fitriyani; Baginda Restu Al Ghazali
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 3 No. 3 (2025): Agustus : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v3i3.555

Abstract

Infertility in women is a reproductive health issue that requires early intervention to prevent long-term effects. With the advancement of technology, electronic medical records data can be utilized to assist in the diagnosis and classification of infertility risks. This study aims to classify the risk of infertility in female patients using the Naive Bayes algorithm based on medical record data, which includes factors such as age, health history, and medical test results. The data used in this study were obtained from hospitals and health clinics focused on managing infertility patients. The methods applied include data preprocessing, applying the Naive Bayes algorithm for classification, and evaluating the model using accuracy, precision, recall, and F1-score metrics. The results of the study show that the Naive Bayes algorithm provides fairly accurate classification in predicting infertility risks. The analysis-generated graph shows the distribution of infertility risks, with 60% of patients having a positive risk (1) and 40% having a negative risk (0). This study also suggests implementing the classification results in the form of counseling for patients to increase awareness and encourage early preventive actions. Thus, the Naive Bayes algorithm can be an effective tool in assisting healthcare providers in data-driven decision-making to address infertility risks in female patients.
Pemanfaatan Google Digital Platform Untuk Aktivitas Ekstrakurikuler Di MA Al Jauharotunnaqiyyah Jerang Barat Istiqomah Rohmawati; Hafizhah Mardivta; Bella Yasinta; Dinan Wahyu Wijaya; Intania Novita Putri; Raihan Achmad Ramadhan
Abdi Laksana : Jurnal Pengabdian Kepada Masyarakat Vol 6 No 1 (2025): Abdi Laksana : Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/abdilaksana.v6i1.47001

Abstract

Dengan semakin pentingnya peran teknologi dalam membentuk kegiatan siswa yang efektif dan progresif, terutama di kalangan siswa MA AL JAUHAROTUNAQIYYAH JERANG BARAT mempersembahkan sebuah inisiatif yang bertujuan untuk mendigitalisasi pemilihan ektrakulikuler yang akan diikuti oleh siswa melalui pemanfaatan google digital platform. Program pengabdian kepada masyarakat ini bertujuan untuk menggali potensi penuh dari teknologi informasi guna meningkatkan kualitas dan efisiensi kegiatan ektrakulikuler siswa di lingkungan sekolah.
Co-Authors Baginda Restu Al Ghazali Bella Yasinta Dinan Wahyu Wijaya Fahruzi Sirait Intania Novita Putri Istiqomah Rohmawati Nadya Fitriyani Nailatun Nadrah Raihan Achmad Ramadhan