Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal AKSIOMA : Jurnal Sains Ekonomi dan Edukasi
Panjaitan, Hotnauli Roni Arta
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Social Sciences

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

Found 2 Documents
Search

 1 
Analisis Pengelompokan Jenis Kejahatan di Sumatera Utara Berdasarkan Pola Kejadian Tahunan Menggunakan Algoritma K-Means Clustering Sianturi, Michael Dolly; Lubis, Mery Christyn; Payana, Sandi Dwi; Putri, Alya Nabilla; Panjaitan, Hotnauli Roni Arta
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 6 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/aksioma.v2i6.1366

Abstract

This study aims to cluster various types of crimes occurring in North Sumatra Province based on annual incident patterns using the K-Means clustering algorithm. The data utilized are secondary data obtained from the Central Bureau of Statistics (BPS), comprising 34 types of crimes recorded from 2007 to 2021. Prior to clustering, data were normalized using the Z-score standardization method to ensure uniform scaling across variables. The optimal number of clusters was determined using the Elbow Method and Silhouette Plot. The analysis results indicate that four clusters (k = 4) provide the best balance between model complexity and clustering quality. Each cluster reveals distinct crime patterns in terms of frequency and trend stability over the years. The clustering results offer a clearer understanding of crime characteristics in the region and can serve as a foundation for more targeted policy-making, such as resource allocation for law enforcement and data-driven crime prevention strategies. This study demonstrates that data mining approaches, particularly the K-Means algorithm, can significantly contribute to a systematic and comprehensive understanding of crime patterns.
Pengaruh Jenis Cairan Pelapis terhadap Tingkat Pencoklatan Buah Apel dengan Rancangan Acak Kelompok Lengkap Panjaitan, Hotnauli Roni Arta; Triana, Dinie; Hutapea, Risca Octaviyani; Pulungan, Zakiy Maulana; Ndruru, Albert Servant
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 12 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/aksioma.v2i12.1996

Abstract

This study aims to determine the effect of coating solutions consisting of control, lemon water, and salt water on the browning intensity of fresh-cut apples using a Completely Randomized Design (CRD). Enzymatic browning is a major problem in fresh-cut apples due to the oxidation of phenolic compounds triggered by the activity of the polyphenol oxidase enzyme. Lemon water acts through mechanisms of pH reduction and antioxidant activity, while salt water inhibits browning through ionic effects and osmotic pressure. The experiment was conducted using homogeneous apple units, and the browning scores obtained were analyzed using ANOVA at a 5% significance level. The results showed a significant effect among treatments, with an F-value of 5.136 exceeding the F-table value of 4.226. Lemon water was found to be the most effective in inhibiting browning, followed by salt water, while the control treatment exhibited the highest browning intensity. These findings confirm that simple natural materials can serve as effective anti-browning coatings, especially when applied to homogeneous experimental units using a CRD.
Co-Authors Hutapea, Risca Octaviyani Lubis, Mery Christyn Ndruru, Albert Servant Payana, Sandi Dwi Pulungan, Zakiy Maulana Putri, Alya Nabilla Sianturi, Michael Dolly Triana, Dinie