Data ini merupakan data cuaca harian sulawesi tenggara, mulai dari tanggal 01 januari 2022 sampai dengan 30 november 2023, dimana data-data dibawah ini meliputi: Tanggal,Temperatur minimum (°C),Temperatur maximum(°C),temperatur rata-rata(°C),kelembapan rata-rata(%),curah hujan(mm),lamanya penyinaran matahari(jam),kecepatan angin rata-rata(m/s). untuk lebih jelasnya bisa di lihat pada keterangan di bawah ini

ID WMO : 97150
Nama Stasiun : Stasiun Klimatologi Sulawesi Tenggara
Lintang : -4.05600
Bujur : 122.44900
Elevasi : 30

keterangan : 8888: data tidak terukur
9999: Tidak Ada Data (tidak dilakukan pengukuran)

Data ini bersumber dari website BMKG https://dataonline.bmkg.go.id/dashboard_user

Data is accessed and collected from Indonesia's Badan Metereologi, Klimatologi, dan Geofisika (BMKG) on 22 October 2025. Original Link: https://dataonline.bmkg.go.id/data-harian

Data ini merupakan data cuaca harian sulawesi tenggara, mulai dari tanggal 01 januari 2022 sampai dengan 20 desember 2023, dimana data-data dibawah ini meliputi: Thn,bln,tgl.
temp_min: Temperatur minimum (°C)
temp_max: Temperatur maksimum (°C)
temp_rata-rata: Temperatur rata-rata (°C)
lembab_rata-rata: Kelembapan rata-rata (%)
ch: Curah hujan (mm)
cahaya_jam: Lamanya penyinaran matahari (jam). untuk lebih jelasnya bisa di lihat pada keterangan di bawah ini

ID WMO : 97150
Nama Stasiun : Stasiun Klimatologi Sulawesi Tenggara
Lintang : -4.05600
Bujur : 122.44900
Elevasi : 30

keterangan : 8888: data tidak terukur
9999: Tidak Ada Data (tidak dilakukan pengukuran)

Data ini bersumber dari website BMKG https://dataonline.bmkg.go.id/dashboard_user

Dataset curah hujan Provinsi Kalimantan Selatan dalam rentang waktu 1 Januari s/d 31 Januari 2025. Diperoleh dari https://dataonline.bmkg.go.id/

Keterangan: Tavg: Temperatur rata-rata(°C) RR: Curah hujan(mm)

Several nations are currently experiencing a significant increase in coronavirus (COVID-19), including Indonesia. A total of 34,874,744 confirmed cases with 1,097,497 deaths (case fatality rate (CFR) 3.1%) were reported in 216 countries based on data from World Health Organization. COVID-19 remains public health problem around the world. It is possible the climate could affect the transmission of COVID-19. The wind is one of the climate factors besides temperature, humidity, and rainfall. Wind speed data can be used to study the spread of COVID-19 cases., The wind speed data was taken from the Meteorology, Climatology, and Geophysics Agency's data website (https://dataonline.bmkg. go.id/home). The wind speed (maximum and mean) in Jakarta from the pandemic inception, specifically between March and September 2020. These records were obtained from the website of the Jakarta Provincial Health Office and the website of the Indonesian Meteorology, Climatology, and Geophysics Agency. Subsequently, the general information was converted into 31-week documentation. Furthermore, a basic map of Jakarta with neighboring community boundaries was obtained using the GADM Map and Data site. Coordinates for the weather monitoring stations were accessed online from (https://www.gps-latitude-longitude.com/).,

This dataset is taken from the official website of BMKG Indonesia dataonline.bmkg.go.id. You can also retrieve other data from the website.

I took this data for research purposes in a competition. I've cleaned it up so it's a quality time-series dataset. I wanted to share it with the Kaggle community. Please upvote the dataset if you find this dataset helpful 😁. note: dataset before this has flaw, i forget to resample it. Now this contain all date that need to belong into dataset. If you feel this dataset still dirty, you can clean it again by yourself.

Dataset Information

Measured city climate: Semarang
Data taken from: https://dataonline.bmkg.go.id/home
Stations that take data: Stasiun Klimatologi Jawa Tengah
Range date in dataset: 1 February 2017 to 31 December 2023
Column explanation:
- Tanggal: Daily time (month/daily/year [hour time, it's can be ignore])
For this column, i don't set it as datetime type. Convert it to datetime first if you want to use it. - Tn: Minimum Temperature (°C) - Tx: Maximum Temperature (°C) - Tavg: Average Temperature (°C) - RH_avg: Average Humidity (%) - RR: Rainfall (mm) - ss: Duration of Sunshine (hours) - ff_x: Maximum Wind Speed (m/s) - ddd_x: Wind Direction at Maximum Speed (°) - ff_avg: Average Wind Speed (m/s) - ddd_car: Most Common Wind Direction (°)

I took this data for research purposes. I've cleaned it up so it's a quality time-series dataset. I wanted to share it with the Kaggle community. Please upvote the dataset if you find this dataset helpful 😁.

Dataset Information

Measured city climate: Semarang
Data taken from: https://dataonline.bmkg.go.id/home
Stations that take data: Stasiun Klimatologi Jawa Tengah
Range date in dataset: 1 January 2020 to 31 December 2023
Column explanation:
- Tanggal: Daily time (day-month-year)
For this column, i don't set it as datetime type. Convert it to datetime first if you want to use it. - Tn: Minimum Temperature (°C) - Tx: Maximum Temperature (°C) - Tavg: Average Temperature (°C) - RH_avg: Average Humidity (%) - RR: Rainfall (mm) - ss: Duration of Sunshine (hours) - ff_x: Maximum Wind Speed (m/s) - ddd_x: Wind Direction at Maximum Speed (°) - ff_avg: Average Wind Speed (m/s) - ddd_car: Most Common Wind Direction (°)