{"id":30605524,"url":"https://github.com/teresakae/pathspredict","last_synced_at":"2026-02-11T18:33:55.999Z","repository":{"id":311582645,"uuid":"1044154541","full_name":"teresakae/PathsPredict","owner":"teresakae","description":"A web-based application with a machine learning model to predict congestion levels for KRL and Transjakarta in Jakarta, helping commuters choose the least crowded transport option.","archived":false,"fork":false,"pushed_at":"2025-08-25T09:32:22.000Z","size":61,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-08-25T11:38:30.584Z","etag":null,"topics":["commuting-analysis","commuting-patterns","traffic-analysis"],"latest_commit_sha":null,"homepage":"https://arkteam.pythonanywhere.com/","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/teresakae.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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}},"created_at":"2025-08-25T09:09:32.000Z","updated_at":"2025-08-25T09:32:25.000Z","dependencies_parsed_at":"2025-08-25T11:38:41.486Z","dependency_job_id":"7cb92bc8-8ec3-4fda-86e3-d8e4dffdf416","html_url":"https://github.com/teresakae/PathsPredict","commit_stats":null,"previous_names":["teresakae/pathspredict"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/teresakae/PathsPredict","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teresakae%2FPathsPredict","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teresakae%2FPathsPredict/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teresakae%2FPathsPredict/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teresakae%2FPathsPredict/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/teresakae","download_url":"https://codeload.github.com/teresakae/PathsPredict/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teresakae%2FPathsPredict/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29341239,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-11T18:24:36.877Z","status":"ssl_error","status_checked_at":"2026-02-11T18:23:50.867Z","response_time":97,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["commuting-analysis","commuting-patterns","traffic-analysis"],"created_at":"2025-08-30T02:20:30.756Z","updated_at":"2026-02-11T18:33:55.995Z","avatar_url":"https://github.com/teresakae.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"## 🚆 PathsPredict - KRL \u0026 TransJakarta Congestion Predictor 🚌\n\nA web-based application with a machine learning model to predict congestion levels for KRL and Transjakarta in Jakarta, helping commuters choose the least crowded transport option.  \u003cbr\u003e  \u003cbr\u003e \nThis project was developed as an End-of-Semester Project for \"Sistem Informasi Cerdas\" course by ARK (Andrew, Runi, Kae)\n\n## 🚀 Features\n* **Congestion Prediction**: Utilizes a Logistic Regression model to predict \"TINGGI\" (High) or \"RENDAH\" (Low) congestion levels for KRL and Transjakarta.  \n* **Predictive Dashboard**: Forecasts congestion for upcoming days based on historical and real-time data.  \n* **Data Management (CRUD)**: Allows for adding, viewing, updating, and deleting historical ridership data.  \n* **Data Export**: Exports historical and crowdsourced data to an Excel file for further analysis.  \n* **Real-time Data Integration**: Continuously updates predictions based on new data to maintain accuracy.  \n\n## 🛠 Tech Stack\n* **Backend**: Python (Flask, Pandas, scikit-learn), Joblib. \n* **Database**: In-memory simulation. \n* **Frontend**: HTML, CSS, JavaScript.\n* **Data Source**: Satu Data Jakarta (2024-2025).  \n\n## 📂 Folder Structure\n├── Jumlah_Penumpang_Angkutan_Umum_yang_Terlayani_Perhari.csv  \u003cbr\u003e\n├── app.py  \u003cbr\u003e\n├── categorical_features.pkl  \u003cbr\u003e\n├── index.html  \u003cbr\u003e \n├── logistic_regression_penumpang_pipeline.pkl  \u003cbr\u003e\n├── model_features_with_moda.pkl   \u003cbr\u003e\n├── model_training.py  \u003cbr\u003e\n└── numerical_features.pkl  \u003cbr\u003e\n\n## 🧪 Getting Started\n`git clone \u003crepository_url\u003e  \ncd PredictJakarta  \npip install -r requirements.txt  \npython app.py  \nVisit http://localhost:5000 to explore the application.`\n\n## ✅ Future Improvements\n* Integrate with a real live database for persistent data storage.\n* Implement a more sophisticated machine learning model (e.g., a time-series model like ARIMA) for more accurate long-term predictions.  \n* Build a more interactive and user-friendly front-end dashboard with data visualizations (e.g., charts and graphs).  \n* Add a feature to predict congestion for specific routes or times of day, rather than just daily averages.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fteresakae%2Fpathspredict","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fteresakae%2Fpathspredict","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fteresakae%2Fpathspredict/lists"}