Log Analyzer

A log analyzer in a Learning Management System (LMS) environment is a tool designed to process and interpret log data generated by the LMS. Its main purposes are:

1. Monitoring Student Activity: Tracks student interactions with the LMS.
2. Identifying Patterns and Trends: Detects patterns that indicate engagement or potential cheating.
3. Performance Evaluation: Assesses the effectiveness of learning materials and teaching methods.
4. Ensuring Security and Integrity: Monitors for suspicious activities.

Features

1. Data Collection: Gathers log data in real-time from various LMS components.
2. Data Preprocessing: Converts raw log data into a structured, standardized format.
3. Analysis and Visualization.
   • Descriptive analytics for summaries and statistics.
   • Behavioral analysis to identify student behavior patterns.
   • Anomaly detection for unusual patterns indicating issues.

Firebase Authenticator

We have integrated Firebase Authentication into this project to provide a more seamless and secure user experience. Firebase Auth allows users to:

1. Sign up: Create a new account with a strong email and password.
2. Log in: Log in to an existing account using various authentication methods.
3. Log out: Log out of their account at any time.
4. Forgot Password: Reset the password if forgotten.

Images

No	Image	Url
1		/login
2		/dashboard
3		/dashboard/
4		/dashboard/findings
5		/dashboard/alerts
6		/dashboard/alerts

💿 Install

git clone https://github.com/yogiex/vue-log-analyzer
cd vue-log-analyzer
nvm use 16
npm install
npm run dev

npm run dev only for development

Todo list features

• Real time
• Change
• System Reporting into file
• Integrate with flask backend
• Authentification login with firebase
• Backup Data

Backend

Step by step

Persiapan log storage

create table backup_attempt (
    id int auto_increment,
    attempt_id int,
    id_peserta int,
    firstname varchar(99),
    lastname varchar(250),
    course_name varchar(250),
    quiz_name varchar(250),
    unique_id int,
    layout longtext,
    timestart bigint(10),
    timefinish bigint(10),
    score decimal(10,5),
    primary key(id)
);

CREATE TABLE peserta_history (
    id SERIAL PRIMARY KEY, -- auto-incrementing primary key
    firstname VARCHAR(255) NOT NULL,
    lastname VARCHAR(255) NOT NULL,
    userid VARCHAR(255) NOT NULL,
    timedate TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    timestart TIME NULL DEFAULT NULL,
    timefinish TIME NULL DEFAULT NULL,
    timetaken TIME NULL DEFAULT NULL,
    score INT NOT NULL,
    _session VARCHAR(255) NOT NULL,
    _status INT NOT NULL,
    shift VARCHAR(255) NOT NULL,
    CONSTRAINT unique_timestamps UNIQUE (timedate)
);

CREATE TABLE case_history (
  cases longtext NOT NULL
);

CREATE TABLE daftar_proktor (
  chatid int NOT NULL
);

Setelah membuat db tersebut, langsung jalankan app.py

📑 License

MIT

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