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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Portofolio: Jurnal Manajemen dan Bisnis Brand Communication
Hermawan, Febry
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Social Sciences

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Crime of theft prediction using Machine Learning K-Nearest Neighbour Algorithm at Polresta Bandar Lampung Hermawan, Febry; Prianggono, Jarot
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12422

Abstract

The era of the industrial revolution 4.0 is a time where cyber and physical technology collaborate. This study aims to predict the types of theft crimes that occur in the Bandar Lampung Police area with the K-Nearest Neighbor algorithm, evaluate the prediction results and profiling the prediction results carried out by Bandar Lampung Police investigators in efforts to prevent and handle criminal acts of theft in the jurisdiction of the Bandar Lampung Police Lampung. The approach was carried out using the quantitative method of the K-Nearest Neighbor algorithm using the Rapidminer application by utilizing 1671 police report data from the Bandar Lampung Police and a questionnaire survey method conducted on 49 police investigators from the Bandar Lampung Police. Data collection techniques are carried out in a valid and reliable manner as a support for predictive validity. Based on the results of the classification and questionnaire, it was found that the majority of victims of the crime of theft were adult men who did not have a job and lived in urban areas. It was found that the majority of thefts occurred in parking lots in urban areas on Monday morning where the perpetrators used tools and targeted moving objects by tampering with locks which caused losses of around 10-50 million rupiah. This type of theft is theft by weighting (CURAT) which applies to Article 363 of the Criminal Code. The prediction results show that the neighboring value (K) and the distribution ratio of training and testing data are K=3 and 7:3, respectively. Predictions using K values and data sharing ratios show a high level of accuracy, namely 99. 20%. The results of the questionnaire show results that are in line with the results of the classification with an accuracy rate of the actual data of 75. 7122%. So by increasing the understanding skills of Bandar Lampung Police investigators using technology to predict the crime of theft, the number of theft crimes can be reduced.
Penerapan Model Prediksi Untuk Diintegrasikan Dalam Program Analisis Kerja Personel Dalam Mendukung Peningkatan Perencanaan Strategis dan Operasional Kepolisian: di Polresta Bandar Lampung Polda Lampung Hermawan, Febry; Prianggono, Jarot; Hartanto, Dadang
Jurnal Portofolio : Jurnal Manajemen dan Bisnis Vol. 4 No. 2 (2025): Integrasi Teknologi Informasi dan Manajemen Operasional Kerja Lembaga
Publisher : Prisani Cendekia

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

Abstract

In the Indonesian context, the application of predictive technology in the police sector still faces various challenges. Some of them are low accuracy, in-date, and difficulty accessing data that results in government bureaucratic inefficiency. Bandar Lampung City is one of the regions in Indonesia with a high crime rate. Data from the Bandar Lampung Police shows that theft cases dominate crime reports in the area. In this study, the improvement of ML model performance is expected to provide more accurate predictions and support police officers in designing more appropriate strategies to tackle theft crimes This study uses two popular Machine Learning (ML) models, namely K-Nearest Neighbors (k-NN) and Naïve Bayes (NB), to analyze and predict theft crimes in the jurisdiction of the Bandar Lampung Police. The approach is carried out using a quantitative method of algorithm k-Nearest Neighbor and Naive Bayes using the Rapidminer application by utilizing 1671 data from the Bandar Lampung Police police report and a survey method with questionnaires. The data collection technique is carried out validly and reliably, then the police report data will be used for prediction and the questionnaire data will be used to support the validity of the prediction. Based on the results of comparative research conducted using the K-NN model and the Naive Bayes model, it is known that the k-NN model on theft victim data based on the type of theft that occurred is able to predict by 98.80% and for the Naive Bayes model is able to predict by 99.85%. And for suspect data in the k-NN model, it is predicted to be 70.00% while the Naive Bayes model predicts 88.00%. In predicting theft incidents in Bandar Lampung, the selection of the Naive Bayes (NB) model proved to be much more effective and had a very high accuracy compared to K-Nearest Neighbors (K-NN). Based on the test results, the Naive Bayes model provides a prediction accuracy of 99.85%, which is much better compared to K-NN which may not achieve the same level of accuracy.
Analisis Teori Dusta Umberto Eco Dalam Kasus Kopi Sianida Jessica Wongso Hermawan, Febry; Purnomo, Hadi
Brand Communication Vol. 2 No. 4 (2023): Perencanaan dan Implementasi Manajemen Strategi Komunikasi Organisasi Dalam Bid
Publisher : Prisani Cendekia Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70704/bc.v2i4.238

Abstract

In the cyanide coffee case of Jessica Wongso, Umberto Eco's lying theory can be applied to analyze Jessica's testimony. Based on Eco's theory of lies, lying is a complex form of communication that involves various factors, such as motivation, situation and ability to lie. Based on the available evidence, Jessica's testimony that she did not know that the coffee she gave Mirna contained cyanide is considered unreasonable. Such testimony can be considered a lie caused by several factors, such as a motivation to cover up a mistake, a desire to protect others, or an inability to remember the actual incident. The research paradigm is critical, with a qualitative research approach, which does not present specific measurements, but presents meanings from the analysis of the relationship between signs and other signs. This is in accordance with the semiotic research method, which links one sign to another to reach conclusions. The research results show that the analysis of the lie theory put forward by Umberto Eco and its application in the Cyanide Coffee case involving Jessica Wongso, can be seen how the concepts put forward by Eco can provide valuable insight in understanding the dynamics and complexity of the case. In this case, there are narrative elements constructed by the parties involved, including Jessica Wongso, the mass media and the general public. The use of strong narratives and persuasive rhetoric can influence public perception and understanding of the case. Furthermore, the concepts of play and manipulation in Eco's theory of lies are also relevant in the context of this case. There are allegations that Jessica Wongso played a role in the tragic death of Mirna Solihin by using coffee containing cyanide. Eco argues that lies and manipulation can be used to produce certain effects in communication. In this case, the alleged manipulation and games carried out by Jessica Wongso influenced the parties concerned. Apart from that, Eco's lie theory also highlights the importance of context and interpretation in understanding the truth. In this case, there are differences in interpretation and understanding between the parties involved, including Jessica Wongso, Mirna Solihin's family, and the public. The concept of multiple interpretations and subjectivity in understanding the truth can be seen as significant elements in this case.
Co-Authors Hadi Purnomo Hartanto, Dadang Jarot Prianggono