BangJhener commited on
Commit
f814567
·
verified ·
1 Parent(s): 33b6a37

Upload folder using huggingface_hub

Browse files
Files changed (3) hide show
  1. README.md +56 -3
  2. model_oof_ensemble.pkl +3 -0
  3. requirements.txt +4 -0
README.md CHANGED
@@ -1,3 +1,56 @@
1
- ---
2
- license: apache-2.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: xgboost
3
+ tags:
4
+ - air-quality
5
+ - pollution-prediction
6
+ - ispu
7
+ - jakarta
8
+ - environmental-monitoring
9
+ - classification
10
+ language:
11
+ - id
12
+ license: mit
13
+ ---
14
+
15
+ # ISPU Classification Model - Jakarta Air Quality
16
+
17
+ Model prediksi kategori ISPU (Indeks Standar Pencemar Udara) untuk wilayah DKI Jakarta.
18
+
19
+ **Task:** Multi-class Classification
20
+ **Categories:** BAIK, SEDANG, TIDAK SEHAT
21
+ **Region:** DKI Jakarta (5 monitoring stations)
22
+
23
+ ## Output Classes
24
+
25
+ | Category | ISPU Range |
26
+ |----------|------------|
27
+ | BAIK | 0-50 |
28
+ | SEDANG | 51-100 |
29
+ | TIDAK SEHAT | 101-200 |
30
+
31
+ ## Citation
32
+
33
+ ```bibtex
34
+ @software{ispu_jakarta_2025,
35
+ author = {BangJhener},
36
+ title = {ISPU Classification Model for Jakarta Air Quality},
37
+ year = {2025},
38
+ publisher = {Hugging Face},
39
+ url = {https://huggingface.co/BangJhener/TiRex-3.0}
40
+ }
41
+ ```
42
+
43
+ ## Competition
44
+
45
+ Developed for **Datavidia 10.0 Competition** - ISPU Prediction Challenge
46
+ Research Paper: "Sistem Peringatan Dini ISPU untuk Dinas Lingkungan Hidup DKI Jakarta"
47
+
48
+ ## License
49
+
50
+ MIT License
51
+
52
+ ## Contact
53
+
54
+ - **Author:** BangJhener
55
+ - **Competition:** Arkavidia 2026 - Datavidia 10.0
56
+ - **Target:** Dinas Lingkungan Hidup DKI Jakarta
model_oof_ensemble.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a9d947892ddfa3771fbf60e9ca59acc1e0aa9e07698864696664994263237c48
3
+ size 48101
requirements.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ xgboost>=1.7.0
2
+ scikit-learn>=1.2.0
3
+ numpy>=1.23.0
4
+ pandas>=1.5.0