Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal INFOKUM Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer)
Widia Putri
STMIK Pelita Nusantara
Computer Science & IT

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
IMPLEMENTATION OF THE MOORA METHOD IN DETERMINING CANDIDATES FOR VILLAGE HEAD Fricles Ariwisanto Sianturi; Paska Marto Hasugian; Widia Putri; Ira Mayang Sari
INFOKUM Vol. 10 No. 03 (2022): August, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (253.388 KB)

Abstract

One of the community democratization parties is the election of the village head, the election of the village head is carried out at the village level directly to determine the village leader or village head. Decision support system is an interactive alternative system that can assist in decision making through the use of data and decision models to solve semi-structured and unstructured problems. This system was built by applying the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) method where the basic concept of the MOORA method is to find the weighted sum of the performance ratings for each alternative on all attributes. In the calculation of the MOORA method, only the one that produces the largest value will be selected as the best alternative. Calculations will be in accordance with this method if the selected alternative meets the predetermined criteria. By using a decision support system for the selection of village head candidates using the Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) method, it helps community members to find out the ranking of village head candidates from the results of the weighted criteria that have been determined, thus providing additional information when making decisions. determine choices in the democratic party of the citizens of the village of Sitnggaling.
Analisis Daya Tahan Keamanan Data Pada Steganografi Berbasis Teks Dalam Struktur Kalimat Bahasa Indonesia R. Fanry Siahaan; preddy marpaung; ibnu febrian; widia putri
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 22, No 2 (2023): Agustus 2023
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v22i2.8773

Abstract

Data security in text-based steganography needs to be analyzed in depth to ensure the sustainability and security of the method. The purpose of this research is to analyze the durability of data security in text-based steganography. The analysis approach consists of steps to identify and evaluate the vulnerability of text steganography methods with Indonesian sentence patterns. The first step is to review previous relevant work in this field to understand the vulnerabilities that have been identified previously. The text insertion model carried out is dictionary-based as many as 1,929 words which are divided into seven-word classes that correspond to sentence patterns in Indonesian, namely adj (adjective), adv (adverb), nom (noun), num (numeral), par (particle), pro (pronominal) and ver (verb). Each word class is organized into sentence patterns and each has the same bit length of eight bits. The results of the durability analysis show that input data with a length of one word still can be hacked if the message insertion process with a choice of short sentence patterns. Whereas with a choice of sentence patterns that are more than two words it will start to be difficult to hack and even cannot be hacked because the number of possibilities is very large and even infinite or infinity.
Penerapan Data Mining Untuk Pengelompokan Kepadatan Penduduk Kabupaten Deli Serdang Menggunakan Algoritma K-Means Preddy Marpaung; Ibnu Pebrian; Widia Putri
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 6 No. 2 (2023): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kepadatan penduduk diberbagai besar seperti Kabupaten Deli Serdang akan mengakibatkan banyak dampak yang akan dialami oleh masyarakat. Namun sering kali masyarakat baik individu atau kelompok yang ingin betempat tinggal maupun berdomisili di Kabupaten Deli Serdang memilih lokasi tempat tinggalnya semaunya tanpa mengetahui klasifikasi kepadatan penduduk yang ada, sehingga bisa mendapatkan dampak masalah yang besar bagi masyarakat tersebut atau cenderung berada dilingkaran permasalahan yang begitu besar yang akan dihadapinya jika tidak tahu memilih lokasi tempat tinggal yang akan ditempati masyarakat tersebut. Ketidaktahuan masyarakat akan lokasi kepadatan penduduk yang ada di kabupaten Deli Serdang karena tidak adanya pengetahuan atau informasi tentang pengelompokan kepadatan penduduk. Maka perlu dilakukan pengelompokan kepadatan penduduk sebagai pengetahuan baru kepada masyarakat untuk menghidari maupun mengurangi dampak yang akan dialami bagi masyarakat yang ingin bertempat tinggal di daerah Deli Serdang. Pengelompokan kepadatan penduduk ini akan dikelompokan kedalam 3 kelompok (cluster) menggunkan algoritma K-Means , yaitu sangat padat (cluster1), Padat (cluster2), dan sedang (cluster3). Dengan hasil penerapan algoritma K-Means dapat menghasilkan, bahwa dari 22 kecamatan yang ada, terdapat 3 kecapatan Sangat Padat (cluster1), 4 kecamatan padat (cluster2), dan 15 kecamatan sedang (cluster3). Sehingga dengana adanya cluster kepadatan penduduk ini akan memberikan pengetahuan baru kepada masyarakat baik secara individu maupun kelompok yang melakukan urbanisasi, transmigrasi, dan imigrasi karena faktor pekerjaan, faktor ingin menetap, maupun faktor lainnya , sehingga menghindari atau meminimalisi dampak permasalahan karena faktor kepadatan penduduk.
Co-Authors Hasugian , Paska Marto Ibnu Febrian Ibnu Pebrian Ira Mayang Sari Marpaung, Preddy Siahaan, R. Fanry