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All Journal Jurnal Ilmu Kepolisian Jurnal Portofolio: Jurnal Manajemen dan Bisnis
Bayuna, Kadek Ari
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Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Social Sciences

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An Analysis of Ferienjob Practices in Germany: Modus Operandi, Legal Actions, Prevention, and Global Comparisons Bayuna, Kadek Ari; Shinto Bina Gunawan Silitonga; Bhaskara Ardhy Anugerah Nasution
Jurnal Ilmu Kepolisian Vol 18 No 3 (2024): Jurnal Ilmu Kepolisian Volume 18 Nomor 3 Tahun 2024
Publisher : Sekolah Tinggi Ilmu Kepolisian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35879/jik.v18i3.621

Abstract

The Ferienjob program in Germany which was started as an opportunity for students to find work and earn an income during vacations has of late come under criticism and allegations of being justifications for more nefarious endeavors such as human trafficking and labor slavery. In the light of this background, this article examines the factors that facilitated the exploitation of over 1,000 Indonesian and Uzbek students engaged in the Ferienjob scheme arguing about weaknesses in the host and the students’ home countries’ labor protection systems. Even though there are labor laws in Germany like the Employengesetz which forbids the exploitation of minor employees and the Mindestlohngesetz which ensures at least a guaranteed pay for every employee’s work, exploited labor has not died down and students remain to be in low wage and unsafe working conditions due to the contracts that they deal with. The research includes questions regarding the qualitative methodology that reflects both primary data collected through the interviews and secondary data obtained from government documents and legislations. The key study findings include the use of false claims in this particular case to lure in students, the stealing of the student’s money via placement fees, and the lack of proper legal care for foreign employees. The article further examines the responses issued by Indonesia and Germany in the court trying to show that it is extremely hard to bring the offending parties to book and to coordinate the protection of labor laws. As a final point the study provides the suggestions of how the preventive measures could be improved including enhanced regulations for recruitment firms, an improvement in the control of international agencies, and improvement of university partnerships.
Prediksi Lokasi Tindak Pidana Pencurian Menggunakan Metode K-Nearest Neighbor di Wilayah Hukum Polres Badung Polda Bali Bayuna, Kadek Ari; Prianggono, Jarot; Wibowo, Didit Bambang
Jurnal Portofolio : Jurnal Manajemen dan Bisnis Vol. 4 No. 1 (2025): Prediksi dan Pemanfaatan Big Data Dalam Manajemen Cyber Digital Dunia Peradaban
Publisher : Prisani Cendekia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70704/jpjmb.v4i1.352

Abstract

This study aims to predict the location of theft crimes in the jurisdiction of the Badung Police by applying the K-Nearest Neighbor (KNN) method. The main focus of the study is to identify crime patterns based on time and location variables in order to improve the effectiveness of police prevention strategies. The problem raised is how machine learning-based models can help detect theft-prone areas and improve accuracy in crime prevention efforts. This study uses a quantitative approach with the CRISP-DM (Cross-Industry Standard Process for Data Mining) method. The data used includes information on time, location of the incident, and theft categories based on police reports. The research process includes business understanding, data exploration and preparation, modeling using KNN, model performance evaluation, and implementation in the form of interactive map visualization. Model performance is analyzed using evaluation metrics such as precision, recall, and F1-score to measure the level of prediction accuracy. The results of the study show that the KNN model is able to identify locations with a high risk of theft with fairly good accuracy. Areas with high activity, such as transportation facilities and commercial areas, are more vulnerable to this crime. In addition, thefts occur more often in the morning, evening, and early morning when people are off guard. In conclusion, the KNN method is effective in predicting theft-prone areas. Implementation of this model can help the police improve the effectiveness of patrols and security strategies. It is recommended that this model be combined with a geographic information system (GIS) to facilitate the analysis of crime patterns in order to improve public security more proactively.
Shielding Public Health: Indonesian National Police (INP)’s Measure Against COVID-19 Vaccine Certificate Forgery Bayuna, Kadek Ari; Adnya Suasti, Ni Made; Syahputra, Aulia Noprizal
Jurnal Ilmu Kepolisian Vol 18 No 2 (2024): Jurnal Ilmu Kepolisian Volume 18 Nomor 2 Tahun 2024
Publisher : Sekolah Tinggi Ilmu Kepolisian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35879/jik.v18i2.461

Abstract

The purpose of this study is to discuss the benefits of implementing several strategies carried out during the COVID-19 period. COVID-19 vaccine certificate forgery has posed a threat to public health. The Indonesian National Police (INP) has implemented various strategies to overcome this crime. The intervention strategies involve early detection and prevention, such as cyber patrol, border control, public involvement, and strict law enforcement. Other countries have also carried out similar measures; however, there are several additional strategies, such as the formation of a special force as well as utilizing blockchain technology for a more secure digital vaccine certificate system. These strategies could be a benchmark for the INP in handling cases of letter forgery.
Co-Authors Adnya Suasti, Ni Made Bhaskara Ardhy Anugerah Nasution Jarot Prianggono Shinto Bina Gunawan Silitonga Syahputra, Aulia Noprizal Wibowo, Didit Bambang