Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Aplikasi Statistika & Komputasi Statistik Prosiding Seminar Nasional Official Statistics
Yohanes Wahyu Trio Pramono
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Pengembangan Search Engine Konten Statistik pada Website Badan Pusat Statistik untuk Mendukung Diseminasi Statistik Resmi Yohanes Wahyu Trio Pramono; Dhoni Eko Wahyu Nugroho
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.081 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1147

Abstract

BPS as a government-owned public agency, has the duties and authorities as an official body that disseminates statistical data. With the increasing penetration of internet usage, the website channel is one of the electronic media that is fast and easy to answer the challenges of data dissemination strategies. The development and implementation of a search engine on the BPS website have now succeeded in providing a search function for diverse statistical content, across website domain areas, and capable of performing image searches using image-to-text techniques and in-depth searches of all PDF texts for PDF publications and Official News Statistics PDF format. With this search engine development strategy, it is hoped that the data dissemination business process at the BPS Dissemination Directorate can run more optimally, being able to provide the data desired by data users more easily, quickly, and precisely.
Integrating Multi-Criteria Decision Analysis and Machine Learning for Fine-Scale Mapping of Safe Drinking Water Access in Bengkulu Province, Indonesia Tampubolon, Andrew Maruli Tua; Josaphat, Bony Parulian; Asriadi Sakka; Yohanes Wahyu Trio Pramono
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 17 No 2 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v17i2.866

Abstract

Introduction/Main Objectives: This study aims to develop a 1 km × 1 km level estimation model of safe drinking water access using multisource satellite imagery, point of interest (POI), and aquifer productivity maps. Background Problems: There is a lack of alternative data sources for estimating safe drinking water access that are cost-, time-, and labor-efficient while maintaining high accuracy and frequent updates. Novelty: This study integrates Multi-Criteria Decision Analysis (MCDA) and machine learning methods to estimate and map safe drinking water access at a 1 km × 1 km resolution. Research Methods: Multisource geospatial data were used to construct the model. Within the MCDA approach, the Weighted Product Model (WPM) was employed to develop the Safe Drinking Water Access Index (SDWAI). Meanwhile, the machine learning regression algorithms Adaptive Boosting Regression (ABR) and Gradient Boosting Regression (GBR) were applied to estimate safe drinking water access at a fine spatial scale. The study was conducted in Bengkulu Province, Indonesia. Finding/Results: WPM yielded the best MCDA performance (  = 0.3699, RMSE = 10.6566, MAE = 9.5427, MAPE = 0.1405), while ABR showed the best machine learning performance (  = 0.4361, RMSE = 10.0813, MAE = 8.3750, MAPE = 0.1333).
Co-Authors Asriadi Sakka Dhoni Eko Wahyu Nugroho Josaphat, Bony Parulian Tampubolon, Andrew Maruli Tua