Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Manajemen Informatika dan Bisnis Digital Jurnal Sistem Informasi dan Ilmu Komputer
Rasti Lani
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management

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

Found 2 Documents
Search

 1 
Menentukan Titik Rawan Malaria Di Provinsi Nusa Tenggara Timur Menggunakan Metode K-Means Clustering Yustina Bete Dos Santos; Rasti Lani; Atfandianus Ewal; Bastian Jumilton Lenggu; Yampi R Kaesmetan
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v1i4.1750

Abstract

Malaria is one of the diseases that is currently affected, but is still a threat and often causes unusual events in NTT province. Malaria in NTT province is the second highest malaria disease in Indonesia after Papua. The method used to analyze the vulnerability to malaria in NTT province is K-Means Clustering. The purpose of analyzing the level of malaria vulnerability is to find out which districts have the highest to lowest vulnerability in NTT province, which is carried out in a geographic information system. The results of the analysis showed tha 7 districts were classified as low malaria vulnerability, 1 district as medium, 12 districts as high and 2 districts as very high. The level of vulnerability can be understood as the level of malaria endemicity.
Pemetaan Penyakit Hewan Ternak di Timor Tengah Selatan Menggunakan GIS dengan Metode K-Means Clustering Rasti Lani; Yampi R Kaesmetan
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 4 No. 1 (2025): Mei 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jumintal.v4i1.5005

Abstract

South Central Timor Regency in East Nusa Tenggara Province faces serious challenges in controlling livestock diseases that impact livestock farmers' welfare and food security. rainfall patterns due to climate change impacts. This study aims to develop a WebGis-based Geographic Information System (GIS) to map the distribution of livestock diseases in the region. This system is expected to assist the Animal Husbandry Service in planning efforts to control and prevent diseases more effectively and on target. The method used is K-Means Clustering to group areas based on disease prevalence, disease type, and environmental factors that influence its spread. Accurate spatial data is collected from various sources and integrated into the WebGis platform, resulting in a livestock disease distribution map that can be easily accessed by related parties. The expected results of this study are the availability of fast, accurate, and efficient disease distribution information to support planning for animal disease control and prevention actions. The developed WebGis allows access to real-time and data-based information, thus supporting more strategic decision-making in improving livestock resilience in South Central Timor Regency
Co-Authors Atfandianus Ewal Bastian Jumilton Lenggu Kaesmetan, Yampi R Yustina Bete Dos Santos