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Halim Agung
Universitas Bunda Mulia
Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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Journal : G-Tech : Jurnal Teknologi Terapan

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Classification of Remission Data for Prisoners in Tangerang Class IIA Correctional Institution using K-Nearest Neighbor Algorithm Abdillah, Refa Maulana; Agung, Halim; Ramdhan, Syaipul
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7532

Abstract

The classification of remission eligibility for prisoners is a critical issue in correctional institutions, as it directly impacts prison management and the rehabilitation process. Special remission is a reduction of sentence granted to prisoners based on specific criteria, including religious status and the type of remission granted. This research aims to address the challenge of classifying special remission data for prisoners at the Class IIA Tangerang Correctional Facility using the K-Nearest Neighbor (KNN) algorithm. The dataset used in this study includes four indicators: Length of Sentence, Remaining Sentence, Crime Type, and Risk Dimension, which are analyzed to predict the remission status to be granted. The KNN model, with a parameter of k=1, achieved an accuracy of 93.94%. However, the model struggled to accurately classify the "No Remission" class, resulting in failures to detect prisoners who are not eligible for remission. The data processing steps included converting categorical data into numerical format, data normalization, and splitting the data into training and testing sets. Model evaluation was conducted using Confusion Matrix, Precision, Recall, and F1-Score. The findings suggest that while the KNN algorithm can be effectively used to classify remission status, further improvements are needed to address class imbalance and optimize results.
Co-Authors Abdillah, Refa Maulana Abiel Filetus Agung Stefanus Kembau Alvin Juvianto Alvin Juvianto, Alvin Amanda, Mercedes Andreas, Andri Axell Thomas Badri, Wahid Maulana Brigitta Indrawan, Genoveva Budiman Budiman Candra, Ricky Chandra Arief Rahardja Charles Widodo Christanti Christanti CHRISTANTI CHRISTANTI, CHRISTANTI Christian, Michael Christine Christine Christine Citra, Calvin Christopher Claude Calvin Alsher Danny Steveson Edy Andersen Erlando Aubrey Nathaniel Evasaria Magdalena Sipayung, Evasaria Magdalena Farady Marta, Rustono Fauzi, Zidan Wahyu Fendra Mulia Firellsya, Gabriela Fitri Murfianti Hakim, Lukman Handoko, Maulana Bhakti Hariyanto, Ribfan Harvin Seruni I Gede Wisnu Satria Chandra Putra Ivan Ivan Ivan Ivan Januar, Rizky Jeki Sauwani Jessica Jessica Jessica Jessica Jimmy Gunawan Johanes Fernandes Andry Juardi, Try Juniana, Paula Karlo Geofandy Karman Surya Kenny Kevin Ekaputra Kevin Krisnandi Kevin Laurence Hartono Lieta Septiarysa Linda Linda Lukman Hakim M. Bucci Ryando Marchellius Yana Mario Richie Marlina Marlina Maynacky Muhamad Ali Sukrajap Nico Yunus Marselinus Novara Aulist Zakia Oscar Adriyanto Phoan, Nico Prittania Friska Octavia Rahardja, Chandra Arief Rainhard Rainhard Ramdhan, Syaipul Raphael, Stephanus Rarasati, Dionisia Bhisetya Richard Benedict Ricky Candra Ricky Raymond Ricky Ricky Rini Lestari Rizky Januar Rustono - Rustono Farady Marta Rustono Farady Marta Sandi Gautama, Sandi Septiarysa, Lieta Setiawan, Vincent Sinata, Frans SOFIA, DETIN Stefanus Kembau, Agung Stephanus Raphael Steven Steven Andreas Teady Matius Surya Mulyana, Teady Matius Thomas, Axell Tobing, Fery Tri Yatmo Noveary Try Juardi Valerian Hendri Yono Venness, Venness Vicky Budiman Vina Virshella Vitcky Nanda Putra Wang, Changsong Wilibrodus Wilibrodus Willyam Willyam Wiryadinata, Antonius Yessica Putri Santoso Yogi Swara Hendro Leksmono Yogyawan Yogyawan Yohanes Dianrizkita Yosephine, Maria Yuliana Yuliana