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"Di penelitian ini, penulis beragumen bahwa Jake, karakter utama dalam 10 Years (2012) telah berada dalam fase penyangkalan (denial) sepanjang film. Penelitian ini berfokus pada tipe denial, penyebab denial, dan bagaimana Jake menghadapi denialnya. Teori denial Anna Freud akan menjadi teori pendukung penelitian ini.Menganalisa dialog dan adegan, hasil penelitian mengungkapkan bahwa karakter, Jake, sangat berbeda dengan apa yang mungkin penonton pikirkan pada awalnya karena ulasan-ulasan film di New York Times, LA Times dan Hollywood Reporter menggambarkan Jake sebagai kekasih penuh cinta yang menjadi pusat perhatian di pesta. Penemuan penelitian menegaskan bahwa dengan menggunakan teori denial Anna Freud, karakter, Jake, telah berada dalam fase denial.

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In this research, the writer argues that Jake, the main character in 10 Years (2012), has been in denial throughout the movie. The research focuses on the types of the denial, the cause of the denial, and how Jake dealt with his denial. Anna Freud's denial theory will be the framework of this research.By analyzing the dialogues and scenes, the research findings reveal that the character, Jake, is completely different with what viewers might have in mind initially as movie reviews in New York Times, LA Times and Hollywood Reporter described Jake as a loving boyfriend who got most of the attention at the party. The findings confirm that the character, Jake, has been in denial using Anna Freud's denial theory"

"[ABSTRAKTugas Karya Akhir ini membahas tentang praktik pungutan liar yang dilakukanoleh oknum anggota Satuan Lalu Lintas Polri di Kantor Bersama Samsat yangpenulis nilai sebagai State Based Authority Crime. Tulisan ini menggunakan datasekunder yang berasal dari penelitian-penelitian yang terdapat dalam skripsiataupun artikel-artikel jurnal. Serta tidak lupa juga artikel pemberitaan online.Tulisan ini menyimpulkan bahwa, wajib pajak juga memiliki peran yang cukupbesar dalam mendorong terjadinya praktik pungutan liar di Kantor BersamaSamsat. Selain itu, terdapat tiga aspek yang melatarbelakangi oknum petugasmelakukan praktik pungutan liar, yaitu aspek motivasi, rasionalisasi, dan adanyakesempatan. Sebagai mekanisme pertahanan diri, terdapat lima teknik netralisasiyang dijadikan oknum petugas sebagai dalih atau pembenaran akan praktikilegalnya tersebut, yaitu : denial of responsibility, denial of injury, denial ofvictim, condemnation of the condemners, dan appeal to higher loyalities.

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ABSTRACTThis paper discusses about the practice of facilitation payment committed byunscrupulous members of Traffic Police in Kantor Bersama Samsat whichassessed by author as State Based Authority Crime. This paper uses secondarydata derived from previous studies, include thesis or international journal articles,also taken from online news articles.This paper concludes that the taxpayer also has a considerable role in encouragingthe practice of facilitation payment in Kantor Bersama Samsat. In addition, thereare three aspects underlying the administration officers to do the facilitationpayment, there are motivation, rationalization, and opportunity. As a defensemechanism, there are five techniques of neutralization that serve as a pretext or aself-defense mechanism from unscrupulous members of Traffic Police in KantorBersama Samsat, there are denial of responsibility, denial of injury, denial ofvictim, condemnation of the condemners, and appeal to higher loyalties.;This paper discusses about the practice of facilitation payment committed byunscrupulous members of Traffic Police in Kantor Bersama Samsat whichassessed by author as State Based Authority Crime. This paper uses secondarydata derived from previous studies, include thesis or international journal articles,also taken from online news articles.This paper concludes that the taxpayer also has a considerable role in encouragingthe practice of facilitation payment in Kantor Bersama Samsat. In addition, thereare three aspects underlying the administration officers to do the facilitationpayment, there are motivation, rationalization, and opportunity. As a defensemechanism, there are five techniques of neutralization that serve as a pretext or aself-defense mechanism from unscrupulous members of Traffic Police in KantorBersama Samsat, there are denial of responsibility, denial of injury, denial ofvictim, condemnation of the condemners, and appeal to higher loyalties.;This paper discusses about the practice of facilitation payment committed byunscrupulous members of Traffic Police in Kantor Bersama Samsat whichassessed by author as State Based Authority Crime. This paper uses secondarydata derived from previous studies, include thesis or international journal articles,also taken from online news articles.This paper concludes that the taxpayer also has a considerable role in encouragingthe practice of facilitation payment in Kantor Bersama Samsat. In addition, thereare three aspects underlying the administration officers to do the facilitationpayment, there are motivation, rationalization, and opportunity. As a defensemechanism, there are five techniques of neutralization that serve as a pretext or aself-defense mechanism from unscrupulous members of Traffic Police in KantorBersama Samsat, there are denial of responsibility, denial of injury, denial ofvictim, condemnation of the condemners, and appeal to higher loyalties., This paper discusses about the practice of facilitation payment committed byunscrupulous members of Traffic Police in Kantor Bersama Samsat whichassessed by author as State Based Authority Crime. This paper uses secondarydata derived from previous studies, include thesis or international journal articles,also taken from online news articles.This paper concludes that the taxpayer also has a considerable role in encouragingthe practice of facilitation payment in Kantor Bersama Samsat. In addition, thereare three aspects underlying the administration officers to do the facilitationpayment, there are motivation, rationalization, and opportunity. As a defensemechanism, there are five techniques of neutralization that serve as a pretext or aself-defense mechanism from unscrupulous members of Traffic Police in KantorBersama Samsat, there are denial of responsibility, denial of injury, denial ofvictim, condemnation of the condemners, and appeal to higher loyalties.]"

"Penulisan ini membahas pengaturan Denial of Benefits dalam perjanjian investasi bilateral dan penerapannya dalam sengketa-sengketa arbitrase internasional. Klausul Denial of Benefits merupakan klausul yang memperbolehkan host state untuk tidak memberikan perlindungan dan keuntungan lainnya kepada investor asing dengan persyaratan sebagaimana diatur dalam perjanjian investasi. Klausul ini telah digunakan oleh berbagai lembaga arbitrase untuk menerima ataupun menolak sengketa investasi yang diajukan kepadanya. Untuk menganalisis permasalahan ini, digunakan penelitian hukum normatif dengan analisis yuridisnormatif. Hasil dari penelitian menunjukkan perkembangan penerapan klausul Denial of Benefits dalam menentukan yurisdiksi International Centre for Settlement of Investment Disputes (ICSID) dan Permanent Court of Arbitration (PCA).

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This writing discusses the Denial of Benefits clause under bilateral investment treaty and its application in international arbitration disputes. Denial of Benefits clause allows Host State to deny the treaty protection to foreign investors with certain conditions set forth in the investment treaty. This clause has been used by international arbitration tribunals to accept or reject investment disputes submitted to them. Legal normative study and normative-juridical analysis are used to analyse this issue. The result of this study shows the evolution of the use of Denial of Benefits clause in determining jurisdiction of international arbitration tribunal International Centre for Settlement of Investment Disputes (ICSID) and Permanent Court of Arbitration (PCA)."

"Pemerintah sedang fokus menangani konten negatif pada internet yang memiliki pengaruh buruk dengan membuat regulasi yang mengikat ISP untuk melakukan filtering konten negatif. Awalnya, para pihak ISP melakukan filtering konten negatif dengan pendekatan teknologi DNS yang database situsnya dikirimkan melalui email oleh Kominfo kepada masing-masing ISP dan hal tersebut dirasa kurang efektif, sehingga pemerintah mengeluarkan metode baru dengan menggunakan fitur DNS-RPZ dimana semua data terpusatkan pada database Kominfo yang diupdate melalui aduan konten negatif TRUST dan disebarluaskan ke masing-masing ISP melalui protokol DNS - RPZ tersebut. Akan tetapi DNS rentan oleh serangan, seperti Distributed Denial of Service DDoS. Oleh karena itu, pada penelitian ini akan ditinjau lebih lanjut tentang cara yang dapat dilakukan untuk menangani adanya serangan pada DNS. Serangan DDoS tersebut dapat dideteksi secara otomatis oleh FastNetMon dan juga dimitigasi oleh ExaBGP dengan melakukan injeksi informasi routing BGP FlowSpec pada router mitigasi.

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The government lately has been focusing on handling negative contents on the internet those have bad impacts by establishing regulation that binds ISPs to filter negative contents. Earlier, the ISPs do the filtering with a DNS approach whose database of the site is sent by email by the ministry of communication and information to each ISP, and such method is considered less efficient. Thus, the government has established a new method using the feature of DNS RPZ where all data is centralized to the database of the ministry of communication and information which is updated through TRUST negative content reports and widely spread to each ISP through the DNS RPZ protocol. However, DNS is fragile to attacks, such as Distributed Denial of Service DDoS. Therefore, this research will observe through ways that can be done to handle attacks to DNS. DDoS attacks can be detected automatically by FastNetMon and also mitigated by ExaBGP which injected routing information BGP FlowSpec on the mitigation router."

"Pembahasan mengenai serangan distributed denial of service menjadi salah satu topik utama dalam wacana keamanan internet. Walaupun penggunaannya sudah lebih dari satu dekade dan mekanisme atau cara kerjanya sudah dipahami secara luas, namun hingga saat ini masih sangat sulit untuk mendeteksi secara dini suatu serangan distributed denial of service. Lambatnya pendeteksian serangan distributed denial of service karena sulitnya membedakan antara paket normal dan paket yang berasal dari agen distributed denial of service. Kesulitan lainnya adalah besarnya jumlah paket yang dikirim, hal ini mengakibatkan lamanya waktu yang dibutuhkan untuk menganalisa, dan dapat menyebabkan akurasi pendeteksian serangan distributed denial of service menurun. Melalui penelitian ini peneliti mencoba memberikan solusi yaitu berupa metode untuk mendeteksi serangan distributed denial of service. Adapun metode yang diajukan disini yaitu dengan melakukan pendeteksian secara dini ketika terjadi serangan distributed denial of service terhadap server jaringan. Dalam melakukan pendeteksian dibutuhkan metode yang efektif untuk segera memberikan peringatan atau informasi bahwa telah terjadi serangan distributed denial of service. Metode yang peneliti ajukan adalah metode deteksi menggunakan algoritma self organizing map dengan memanfaatkan lalu-lintas flow pada jaringan dan menggunakan fitur perhitungan dari metode yang sudah ada sebelumnya, yaitu metode IP FLow. Berdasarkan hasil pengujian, metode yang diajukan berhasil meningkatkan akurasi dan mempercepat waktu deteksi serangan distributed denial of service dibandingkan metode IP Flow.

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Discussion about distributed denial of service attack to be one of the main topics on the Internet security discourse. Although it appearance was more than a decade and it works has been widely understood, but it is still very difficult to detect at early stage of distributed denial of service attack. The delay of distributed denial of service attack detection due to difficulties in distinguishing between normal packets and packets originating from distributed denial of service agents. Another difficulty is the huge number of packets sent, it causes the length of time required to analyze, and could lead to decrease accuracy of detection.

Through this study, researcher tried to provide a solution in the form of methods for detecting distributed denial of service attacks. The method proposed here is to perform early detection of a distributed denial of service attacks on a network server. Doing detection certainly needed an effective method for giving immediate warning or information that distributed denial of service attacks have occurred.

The proposed method research is the detection method using self organizing map algorithm based on flow traffic on the network and by using statistical calculation taken from existing method, IP Flow method. Based on test results, the proposed method successfully improves the accuracy and speed time detection of distributed denial of service attacks than using the IP Flow method."

"Serangan Denial of Service adalah salah satu ancaman serius bagi keamanan jaringan yang dapat menyebabkan gangguan dan tidak tersedianya suatu layanan. Security Information and Event Management (SIEM) Wazuh merupakan sebuah solusi open-source yang dirancang untuk memberikan visibilitas, analisis, dan respons terhadap ancaman keamanan dalam jaringan. Penelitian ini bertujuan untuk menganalisis implementasi SIEM Wazuh dalam mendeteksi serangan DoS dengan mengintegrasikan SIEM Wazuh dengan Intrusion Detection System (IDS) Suricata sebagai pengumpul log paket jaringan. Penelitian dilakukan dalam lingkungan mesin virtual dengan tiga skenario serangan, SYN flood, UDP flood, serta ICMP flood yang dilakukan dengan Hping. Dari hasil penelitian didapatkan bahwa Wazuh dapat mendeteksi semua serangan berdasarkan rule kustom yang telah dibuat dengan waktu rerata deteksi tiap serangan secara berurut 13,99 detik, 45,083 detik, dan 1,2 detik. Penelitian ini menunjukkan bahwa Wazuh mendeteksi serangan berdasarkan rule dan fitur seperti pemantauan log real-time, analisis rule-based serta integrasi dengan sistem keamanan lainnya berkontribusi terhadap efektivitas Wazuh dalam mendeteksi serangan DoS.

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Denial of Service attacks pose a serious threat to network security, causing disruption and service unavailability. Security Information and Event Management (SIEM) Wazuh is an open-source solution designed to provide visibility, analysis, and response to security threats within networks. This research aims to analyze the implementation of SIEM Wazuh in detecting DoS attacks by integrating it with the Intrusion Detection System (IDS) Suricata as the network packet logging collector. The study was conducted in a virtual machine environment with three attack scenarios: SYN flood, UDP flood, and ICMP flood simulated using Hping3. The research findings indicate that Wazuh can detect all attacks based on custom rules created, with average detection times for each attack scenario sequentially being 13.99 seconds, 45.083 seconds, and 1.2 seconds. The study demonstrates that Wazuh detects attacks through rules and features such as real-time log monitoring, rule-based analysis, and integration with other security systems contributing to its effectiveness in detecting DoS attacks."

"Dalam suatu jaringan komputer, dibutuhkan sistem keamanan untuk mencegah adanya akses dari pihak yang tidak diinginkan. Firewall dirancang untuk meningkatkan keamanan jaringan dengan mengontrol dan mengawasi tiap arus paket data yang mengalir pada suatu jaringan. Saat ini telah banyak berkembang firewall yang berbasis sumber terbuka (open source) seperti pfSense, ClearOS dan IPFire. Untuk setiap sistem firewall yang berbeda tentunya memiliki kinerja yang berbeda. Kinerja ini dapat dievaluasi dengan melakukan serangan keamanan jaringan seperti scanning, denial of service, dan password attacks terhadap firewall yang bersangkutan. Hasil serangan ini akan dikumpulkan untuk dianalisis membentuk suatu perbandingan kinerja antar firewall. Hasil penelitian menunjukkan bahwa pfSense memiliki kemampuan deteksi terbaik di antara ketiga firewall dengan persentase deteksi 100% untuk port scanning attacks, 25% untuk denial of service attacks dan 50% untuk password attacks. Pada urutan kedua yaitu IPFire dengan kemampuan deteksi 100% untuk port scanning attacks, 0% untuk denial of service attacks, dan 50% untuk password attacks. Dan pada urutan ketiga yaitu ClearOS dengan kemampuan deteksi 75% untuk port scanning attacks, 25% untuk denial of service attacks, dan 0% untuk password attacks. Untuk tingkat presisi, ClearOS memiliki presisi deteksi terbaik dengan persentase presisi 100% untuk port scanning attacks dan 100% untuk denial of service attacks. Pada urutan kedua yaitu IPFire dengan persentase presisi 95,334 % untuk port scanning attacks dan 83,617% untuk password attacks. Dan pada urutan ketiga yaitu pfSense dengan persentase presisi 67,307% untuk port scanning attacks, 100% untuk denial of service attacks, dan 46,488% untuk password attacks. Kendati demikian, firewall pfSense direkomendasikan di antara ketiga firewall yang diteliti dikarenakan kemampuan deteksinya yang terbaik, memiliki kelemahan yang paling sedikit, dan memiliki banyak opsi untuk modifikasi konfigurasi yang tersedia dibandingkan firewall ClearOS dan IPFire.

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In a computer network, a security system is needed to prevent access from unwanted parties. Firewalls are designed to improve network security by controlling and supervising each packet of data flowing in a network. Currently there are many open source-based firewalls such as pfSense, ClearOS and IPFire. For every different firewall system, it certainly has a different performance. This performance can be evaluated by performing network security attacks such as scanning, denial of service, and password attacks against the firewall. The results of this attack will be collected to be analyzed to form a performance comparison between firewalls.

The results showed that pfSense had the best detection capability among the three firewalls with 100% detection capability for port scanning attacks, 25% for denial of service attacks and 50% for password attacks. In the second place, IPFire with 100% detection capability for port scanning attacks, 0% for denial of service attacks and 50% for password attacks. And in the third place is ClearOS with 75% detection capability for port scanning attacks, 25% for denial of service attacks, and 0% for password attacks. For precision, ClearOS had the best detection precision percentage with 100% precision for port scanning attacks and 100% for denial of service attacks. In the second place, IPfire with a precision percentage of 95.334% for port scanning attacks and 83.617% for password attacks. And in the third place is pfSense with a precision percentage of 67.307% for port scanning attacks, 100% for denial of service attacks, and 46.488% for password attacks. However, the pfSense firewall is recommended among the three firewalls because of it had best detection capabilities, had the fewest weaknesses, and had more options for configuration modification available compared to ClearOS and IPFire firewalls."

"Dalam rangka meningkatkan kemampuan Intrusion Detection System (IDS) dalam mendeteksi serangan, beberapa penelitian melakukan penerapan teknik deep learning. Penelitian ini menggunakan salah satu teknik deep learning yaitu Convolutional Neural Network (CNN) dengan algoritma Convolution 1 Dimension (Conv1D) dan dataset Communications Security Establishment and Canadian Institute of Cybersecurity Intrusion Detection System (CSE-CIC-IDS) 2017 dan CSE-CIC-IDS 2018 untuk deteksi serangan DoS-Hulk, DoS-SlowHTTPTest, DoS-GoldenEye, dan DoS-Slowloris. Selain itu, dilakukan penggabungan kedua dataset tersebut untuk meningkatkan kinerja deteksi. Kontribusi dari penelitian ini adalah penerapan teknik resampling sebelum data mengalami proses pembelajaran. Selain itu, dilakukan penambahan fungsi dropout untuk mencegah terjadinya overfitting. Berdasarkan hasil penelitian diperoleh bahwa model CNN yang dibangun dengan dataset CSE-CIC-IDS 2018 memiliki kinerja yang lebih tinggi dalam deteksi serangan DoS dibanding model CNN yang dibangun dengan dataset CSE-CIC-IDS 2017 yaitu akurasi 99,57%, precision 99,58%, recall 99,43% dan f1-score 99,50%.

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To improve the ability of Intrusion Detection System (IDS) to detect attacks, several studies have implemented deep learning techniques. Our study uses one of the deep learning techniques, namely Convolutional Neural Network (CNN) with Conv1D algorithm and dataset Communications Security Establishment and Canadian Institute of Cybersecurity Intrusion Detection System (CSE-CIC-IDS) 2017 and CSE-CIC-IDS 2018 for detection of DoS attacks-Hulk, DoS attacks-SlowHTTPTest, DoS attacks-GoldenEye, and DoS attacks-Slowloris. In addition, the two datasets were combined to improve detection performance. The contribution of our study is the application of resampling techniques before the data undergoes the learning process. In addition, a dropout function was added to prevent overfitting. Based on the results of the study, it was found that the CNN model built with the CSE-CIC-IDS dataset 2018 had a higher performance in detecting DoS attacks than the CNN model built with the CSE-CIC-IDS 2017 dataset, such as accuracy 99,57% precision 99,58% recall 99,43% dan f1-score 99,50%."

"Denial of Service adalah salah satu serangan siber yang dapat mengakibatkan gangguan layanan dan kerugian finansial. Akibat dari serangan DoS tentunya akan memberikan dampak buruk dan sangat merugikan. Untuk dapat menanggulangi dan meminimalisir dampak serangan DoS, dirancanglah sebuah sistem deteksi serangan DoS dan klasifikasi serangan yang terjadi menggunakan machine learning. Pada penelitian ini, akan dilakukan perancangan sistem deteksi serangan DOS melalui pengumpulan traffic data yang dikumpulkan oleh Wireshark dan dikonversi menggunakan CICFlowMeter. Serangan DoS dilancarkan oleh GoldenEye, HULK, dan SlowHTTPTest. Pengklasifikasian diterapkan pada salah satu dataset pada CICIDS2017, menggunakan algoritma Random Forest, AdaBoost, dan Multi-layer Perceptron. Hasil akurasi klasifikasi tertinggi adalah Random Forest sebesar 99,68%, hasil rata-rata Cross-Validation tertinggi juga dipegang oleh Random Forest sebesar 99,67%, dan untuk perbandingan performa antara hasil algoritma yang dilakukan oleh penulis dan paper konferensi DDOS Attack Identification using Machine Learning Techniques yang menjadi acuan, hasil yang paling mendekati adalah Random Forest dengan besar yang sama.

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Denial of Service is a cyberattack that can result in service disruption and financial loss. The consequences of a DoS attack will certainly have a bad and very detrimental impact. To be able to overcome and minimize the impact of DoS attacks, a DoS attack detection system and classification of attacks that occur using machine learning was designed. In this research, a DOS attack detection system will be designed by collecting traffic data collected by Wireshark and converted using CICFlowMeter. DoS attacks were launched by GoldenEye, HULK, and SlowHTTPTest. Classification was applied to one of the datasets in CICIDS2017, using the Random Forest, AdaBoost, and Multi-layer Perceptron algorithms. The highest classification accuracy result is Random Forest at 99.68%, the highest average Cross-Validation result is also held by Random Forest at 99.67%, and for performance comparison between the algorithm results carried out by the author and the conference paper DDOS Attack Identification using Machine Learning Techniques are the reference, the closest result is Random Forest with the same size."

"Jaringan Mobile Internet Protocol adalah suatu fitur yang terdapat pada IPv6 yang memungkinkan Mobile device dapat diidentifikasikan menggunakan IP tunggal walaupun terjadi perpindahan koneksi dari satu jaringan (Home Network) ke jaringan lain (Foreign Network) tanpa mengganggu proses aplikasi yang sedang berjalan. Sementara itu Proxy Mobile adalah suatu fitur pada IPv6 yang memungkinkan Mobile device mendapatkan koneksi dengan performa terbaik jaringan dengan pengaturan koneksi oleh Local Mobility Anchor sehingga seolah-olah Mobile device berada di jaringan asalnya walaupun telah berpindah dari satu jaringan (Mobile Access Gateway 1) ke jaringan lain (Mobile Access Gateway 2). Performa jaringan diuji menggunakan serangan Denial of Service dan diukur dengan parameter Throughput, Delay dan Packet Loss. Aplikasi yang digunakan adalah FTP (File Transfer Protocol).Hasil yang didapatkan pada penelitian ini menunjukkan bahwa Throughput di MAG 1 dan MAG 2 lebih tinggi daripada di HN dan FN sebesar 69.47% dan 74.9% pada DoS 2600 KB. Delay di MAG 1 dan MAG 2 lebih kecil daripada di HN dan FN sebesar 88.99% dan 144.85% pada DoS 2600 KB. Packet Loss di MAG 1 dan MAG 2 lebih kecil daripada di HN dan FN sebesar 765.68% dan 950.44% pada DoS 2600 KB. Proxy Mobile IPv6 lebih baik performansinya dan lebih tahan terhadap serangan Denial of Service bila dibandingkan jaringan Mobile IPv6.

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Mobile Internet Protocol is a feature contained in IPv6 which enable Mobile device to be identified by using a single IP even though the connection is moved from a network (Home Network) to another network (Foreign Network) without intruding application processing. Proxy Mobile is a feature contained in IPv6 which enable Mobile device to get connection with its best performance where the connection is regulate by Local Mobility Anchor, so the Mobile device feels in its domain though already moved (from Mobile Access Gateway 1 moved to Mobile Access Gateway 2). Network performance is tested using Denial of Service attack to measure Throughput, Delay and Packet Loss. The application used in this research is FTP (File Transfer Protocol).

The result of the research shows that Throughput in MAG 1 and MAG 2 is higher than HN and FN for 69.47% and 74.9% at DoS 2600 KB. Delay in MAG 1 and MAG 2 is lesser than HN and FN for 88.99% and 144.85% at DoS 2600 KB. Packet Loss in MAG 1 and MAG 2 is lesser than HN and FN for 765.68% and 950.44% at DoS 2600 KB. Proxy Mobile IPv6 has a better performance than Mobile IPv6 and endure more toward Denial of Service."