Ichsanudin Ichsanudin, Ichsanudin
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ACTION AGAINST NEW DRUG TYPE GORILLA TOBACCO AT WONOSOBO POLICE REGENCY Ichsanudin, Ichsanudin; Gunarto, Gunarto
Jurnal Hukum Khaira Ummah Vol 18, No 4 (2023): December 2023
Publisher : UNISSULA Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/jhku.v18i4.1857

Abstract

This research aims to determine the implementation of the enforcing process againts the new drug types of tobacco gorilla in Wonosobo Police Resort based on the Criminal Code (KUHAP). This research is a descriptive empirical law research, by doing research on the implementation of the action on the new drug tobacco gorilla in Police Resort Wonosobo. The type of data used is primary data and secondary data. Secondary data sources include primary legal materials, secondary legal materials, and tertiary legal materials. Data collection techniques used are literature studies, in the form of books, and documents and field studies. Data analysis technique use interactive model of analisys, that is process analyze by using three component, that is data collecting, data reduction, and conclusion. Based on the discussion resulted the conclusion, first is the implementation of the action against the new drug type of tobacco gorilla in Wonosobo Police Resort has been done properly according to the law in Indonesia. Secondly, obstacles experienced in the process of action against new types of drugs gorilla tobacco in Wonosobo Police ResortKeywords: Action, Gorilla Tobacco
Klasifikasi Penumpang Kereta Api DAOP 6 Yogyakarta Berdasarkan Kelas Stasiun Menggunakan KNN ichsanudin, Ichsanudin; supatman, supatman
JATISI Vol 11 No 4 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i4.9569

Abstract

Transportation companies continue to adapt to technological developments to improve services to service users. The train is the most crossed mass transportation for service users today. Because of the level of timeliness, comfort and traffic-free so that the train becomes the mainstay mode of transportation for service users. The more service users, of course, the train must improve services to improve services. Therefor The author wants to conduct research on the classification of train passengers, the classification algorithm is used to analyze the number of passengers at the station. This research was conducted using the K-Nearest Neighbor method in determining the number of passengers based on the station class. The K-Nearest Neighbor method is a technique for finding the k target members in the data (training) that are closest to the test data. The dataset in this study uses data sourced from the Passenger Transport Unit DAOP 6 Yogyakarta PT Kereta Api Indonesia from the volume of up and down passengers from 2016 to 2023. The classification results with the K-Nearest neighbor method obtained very good results with an accuracy rate of 93%.