{"id":50673853,"url":"https://github.com/fikri-rouzan/student-stress-levels-classification","last_synced_at":"2026-06-08T14:02:29.357Z","repository":{"id":360147533,"uuid":"1247521760","full_name":"Fikri-Rouzan/student-stress-levels-classification","owner":"Fikri-Rouzan","description":"Proyek pemodelan machine learning untuk mengklasifikasikan tingkat stres mahasiswa berdasarkan parameter input akademik dan psikologis.","archived":false,"fork":false,"pushed_at":"2026-06-04T11:19:32.000Z","size":1952,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-06-04T13:12:56.563Z","etag":null,"topics":["joblib","jupyter-notebook","matplotlib","numpy","pandas","python","scikit-learn","seaborn","streamlit"],"latest_commit_sha":null,"homepage":"https://edustress.streamlit.app","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"agpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Fikri-Rouzan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-05-23T12:33:13.000Z","updated_at":"2026-06-04T11:19:36.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/Fikri-Rouzan/student-stress-levels-classification","commit_stats":null,"previous_names":["fikri-rouzan/student-stress-levels-classification"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Fikri-Rouzan/student-stress-levels-classification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Fikri-Rouzan%2Fstudent-stress-levels-classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Fikri-Rouzan%2Fstudent-stress-levels-classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Fikri-Rouzan%2Fstudent-stress-levels-classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Fikri-Rouzan%2Fstudent-stress-levels-classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Fikri-Rouzan","download_url":"https://codeload.github.com/Fikri-Rouzan/student-stress-levels-classification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Fikri-Rouzan%2Fstudent-stress-levels-classification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34065354,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-08T02:00:07.615Z","response_time":111,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["joblib","jupyter-notebook","matplotlib","numpy","pandas","python","scikit-learn","seaborn","streamlit"],"created_at":"2026-06-08T14:02:28.088Z","updated_at":"2026-06-08T14:02:29.349Z","avatar_url":"https://github.com/Fikri-Rouzan.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Student Stress Levels Classification\n\n## 📌 Deskripsi\n\nProyek ini berfokus pada pemanfaatan pemodelan machine learning untuk mengklasifikasikan tingkat stres pada mahasiswa berdasarkan parameter akademik dan psikologis. Proses analisis dilakukan terhadap data masukan yang mencakup aspek kesehatan, hubungan sosial, capaian akademik, serta kondisi emosional mahasiswa. Hasil dari proyek ini dirancang sebagai alat bantu bagi pihak perguruan tinggi dalam memantau kondisi psikologis mahasiswa secara terukur untuk mempermudah pengambilan keputusan dan mendukung pengelolaan lingkungan kampus yang kondusif.\n\n---\n\n## 💾 Dataset\n\nDataset yang digunakan dalam proyek ini bersumber dari [Kaggle: Student Stress Monitoring Datasets](https://www.kaggle.com/datasets/mdsultanulislamovi/student-stress-monitoring-datasets). Data ini memuat hasil respons survei anonim dari 84 audiensi mahasiswa perguruan tinggi yang berada pada rentang usia 18 hingga 21 tahun. Pengumpulan data dilakukan menggunakan kuesioner skala Likert lima poin untuk memetakan pengalaman mahasiswa terkait tingkat stres, kondisi kesehatan, hubungan sosial, capaian akademik, serta kondisi emosional guna menganalisis korelasinya dengan performa belajar.\n\n---\n\n## 🛠️ Tech Stack\n\n| Kategori                    | Teknologi yang Digunakan                                             |\n| :-------------------------- | :------------------------------------------------------------------- |\n| 🌐 **Programming Language** | `Python`                                                             |\n| 🌱 **Environment**          | `Jupyter Notebook`                                                   |\n| 🧩 **Framework**            | `Streamlit`                                                          |\n| ⚛️ **Libraries**            | `NumPy`, `pandas`, `Matplotlib`, `seaborn`, `scikit-learn`, `Joblib` |\n| ⚡ **Tool**                 | `Google Colab`                                                       |\n| 🚀 **Deployment**           | `Streamlit Community Cloud`                                          |\n\n---\n\n## ⚙️ Petunjuk Pengaturan\n\n1. **Prasyarat**\n   - Python 3.11 atau lebih baru.\n   - Git terinstal di komputer.\n\n2. **Clone Repositori**\n\n```bash\ngit clone https://github.com/Fikri-Rouzan/student-stress-levels-classification.git\ncd student-stress-levels-classification\n```\n\n3. **Buat Virtual Environment**\n\n```bash\n# Windows\npython -m venv venv\nvenv\\Scripts\\activate\n\n# macOS/Linux\npython3 -m venv venv\nsource venv/bin/activate\n```\n\n4. **Install Dependensi**\n\n```bash\npip install -r requirements.txt\n```\n\n5. **Menjalankan Dashboard Streamlit**\n\n```bash\nstreamlit run dashboard/dashboard.py\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffikri-rouzan%2Fstudent-stress-levels-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffikri-rouzan%2Fstudent-stress-levels-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffikri-rouzan%2Fstudent-stress-levels-classification/lists"}