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Innovative Model for Logo Counseling Website Jacob Daan Engel; Ventje Jeremias Lewi Engel; Evangs Mailoa
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.7593

Abstract

Logo counseling is a counseling model specifically to treat low spiritual self-esteem problem affecting the life and attitudes of college students. Nevertheless, the problem relies on distance, time, and psychological burdens which preventing face-to-face logo counseling. By reviewing past research regarding online counseling practices, the innovative model for online logo counseling was designed and then demonstrated via logo counseling website. There are four objectives and thirty-five specifications defined in the model. The result showed that logo counseling website is helpful and easy to understand. Further research needed to address the issue of security and confidentiality, furthermore future research needed to examine the integration of text-mining and multimedia analysis techniques to better helping counselors in online counseling intervention.
DETECTION OF CYBER MALWARE ATTACK BASED ON NETWORK TRAFFIC FEATURES USING NEURAL NETWORK Engel, Ventje Jeremias Lewi; Joshua, Evan; Engel, Mychael Maoeretz
Khazanah Informatika Vol. 6 No. 1 April 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i1.8869

Abstract

Various techniques have been developed to detect cyber malware attacks, such as behavior based method which utilizes the analysis of permissions and system calls made by a process. However, this technique cannot handle the types of malware that continue to evolve. Therefore, an analysis of other suspicious activities ? namely network traffic or network traffic ? need to be conducted. Network traffic acts as a medium for sending information used by malware developers to communicate with malware infecting a victim's device. Malware analyzed in this study is divided into 3 classes, namely adware, general malware, and benign. The malware classification implements 79 features extracted from network traffic flow and an analysis of these features using a Neural Network that matches the characteristics of a time-series feature. The total flow of network traffic used is 442,240 data. The results showed that 15 main features selected based on literature studies resulted in F-measure 0.6404 with hidden neurons 12, learning rate 0.1, and epoch 300. As a comparison, the researchers chose 12 features based on the nature of the malware possessed, with the F-measure score of 0.666 with hidden neurons 12, learning rate 0.05, and epoch 300. This study found the importance of data normalization technique to ensure that no feature was far more dominant than other features. It was concluded that the analysis of network traffic features using Neural Network can be used to detect cyber malware attacks and more features does not imply better detection performance, but real-time malware detection is required for network traffic on IoT devices and smartphones.
Model Inferensi Konteks Internet of Things pada Sistem Pertanian Cerdas Engel, Ventje Jeremias Lewi; Angela, Dina; Suakanto, Sinung; Hutagalung, Maclaurin
JURNAL TELEMATIKA Vol 11, No 2 (2016)
Publisher : Institut Teknologi Harapan Bangsa

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Abstract

Sebagian pertanian di dunia sudah mulai memanfaatkan teknologi informasi dan jaringan sensor untuk membantu pengelolaan lahan pertanian. Sistem ini biasa disebut sistem pertanian cerdas. Implementasi sistem pertanian cerdas yang sedikit melibatkan para pemangku kepentingan bidang pertanian membuat implementasi sensor kurang bisa mendukung dalam pembuatan keputusan. Teknik inferensi konteks dapat membantu mengatasi celah permasalahan tersebut. Penelitian ini menyajikan pemodelan inferensi konteks untuk sistem pertanian cerdas yang memperhatikan: (1) jumlah data yang akan diproses, dan (2) pengiriman data dari lahan ke gateway yang tidak selalu aktif. Model inferensi konteks yang diperlukan adalah yang mudah dibuat, mudah dikonfigurasi, dan cepat diproses serta mendukung lintas lingkungan operasi. Penelitian ini menghasilkan model inferensi konteks dan strategi implementasinya untuk penelitian lanjutan.Most farms have started to use information technology and sensor networks to manage farming field. This system is called smart farming. Smart farming implementation which less involving stakeholders in agriculture field makes the technology not really able to support decision making. Context inference techniques can help with that gap problems. This research presents context inference modeling which considers: (1) the amount of data transfer, and (2) periodic data transmisions. The model designed has to be easy to configure, fast to process, and interoperability. This research had resulted context inference model and its implementation strategy.
Pengembangan Sistem Prediksi Harga Pasar Properti Menggunakan Big Data Platform Suakanto, Sinung; Christy, Aldi; Engel, Ventje Jeremias Lewi; Angela, Dina
JURNAL TELEMATIKA Vol 13, No 1 (2018)
Publisher : Institut Teknologi Harapan Bangsa

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Abstract

Property is a industry that will grow. Some of the problems in property sale and purchase transactions are lack of information about fair sale prices. This price information may be above or below market prices. This study will develop a model for predicting the market price of property in an area. The premise of this research is that the selling price of a house is proportional to the land area and building area in a particular area. The datasets used from this study come from information on selling prices and building area prices from several websites. The approach used in research is using regression and modification. The results of this study are expected to produce a model of recommended property market prices in an area.Industri properti adalah salah satu industri yang diprediksi akan terus berkembang. Beberapa permasalahan yang muncul dalam transaksi jual-beli properti adalah sulitnya mendapatkan informasi mengenai harga jual properti yang wajar. Informasi harga tersebut bisa jadi berada di atas atau bawah harga pasaran. Penelitian ini akan mengembangkan model prediksi harga pasaran properti di suatu daerah. Premis dari penelitian ini adalah harga jual rumah sebanding dengan luas tanah dan luas bangunan di daerah tertentu. Dataset yang digunakan dari penelitian ini berasal dari informasi harga jual dan harga luas bangunan yang ada dari beberapa website. Pendekatan yang digunakan dalam penelitian adalah menggunakan regresi dan modifikasinya. Hasil dari penelitian ini diharapkan dapat menghasilkan sebuah model rekomendasi harga pasaran properti pada suatu daerah.
Penerapan NFC Untuk Pembayaran Uang Elektronik pada Self-Payment Machine Engel, Ventje Jeremias Lewi; Albert, Vincentius; Suakanto, Sinung
JURNAL TELEMATIKA Vol 12, No 1 (2017)
Publisher : Institut Teknologi Harapan Bangsa

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Abstract

Consumers nowadays use electronic money for buying and selling at the market. They need easier and faster payment system especially to facilitate the needs in payment on delivery. Therefore, a self-payment machine were designed and implemented with NFC to bring out faster and easier transaction. The system was tested for its functionality, time, and distance between tag and NFC reader.  Self-payment machine can communicate with payment gateway, execute transaction, and evaluate tag used for paying. Time average for a transaction is 27.3345 seconds with 4-5 seconds needed for reading and evaluating the tag. Optimal distance between tag and reader is 0-4 cm.Penggunaan uang elektronik sudah menjadi kebutuhan bagi para pelaku transaksi. Konsumen memerlukan sistem pembayaran yang cepat dan mudah terutama untuk memfasilitasi kebutuhan ketika payment on delivery.. Oleh sebab itu, dirancang sebuah self- payment machine yang berbasis NFC untuk dapat mempermudah dan mempercepat transaksi. Sistem yang dibangun diuji secara fungsionalitas, waktu, dan jarak pembacaan tag NFC.  Sistem self-payment machine yang dibangun mampu berkomunikasi dengan payment gateway, melakukan transaksi, dan mengevaluasi tag untuk pembayaran. Rata-rata waktu yang diperlukan untuk transaksi adalah 27,3345 dengan pembacaan dan evaluasi tag memerlukan 4-5 detik. Jarak optimal antara tag dengan pembaca NFC adalah 0-4 cm.
Sistem Pengawasan Kinerja Jaringan Server Web Apache dengan Log Management System ELK (Elasticsearch, Logstash, Kibana) Tarigan, Claudia; Engel, Ventje Jeremias Lewi; Angela, Dina
JURNAL TELEMATIKA 2018: Industrial Engineering Seminar and Call for Paper (IESC) 2018
Publisher : Institut Teknologi Harapan Bangsa

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Abstract

A server is a software that has a duty and responsibility to provide information to the web. Any process that occurs within the web server will be recorded in a log. A log is a file that contains a list of actions, events (activities) that have been going on in a computer system. By using the log files on a web server, a lot of things that can be done by system administrators to monitor the performance of the web server. However, the log on the web server are difficult to understand and read. Log management system is a system that can handle data services log in large numbers and generate detailed log information. Logstash is the application log management system that can help the system administrator in the performance monitor log of the web server. Logstash will be combined with the Elasticsearch serves as data storage media and Kibana as visualization. ELK (Elasticsearch, Logstash, Kibana) is used to display and keep an eye on the log data from web server so, system administrators can know the performance of the web server.Server sebagai penyedia layanan di jaringan memastikan agar semua aktivitas yang berkaitan dengannya dicatat dalam log. Log adalah file yang berisi daftar aktivitas dan waktu yang terjadi dalam server. Pemantauan kinerja server dengan memanfaatkan log akan meningkatkan ketahanan dan tingkat layanan sebuah server. Masalahnya adalah log yang tercatat tersebar di beberapa tempat dan susah untuk langsung diolah karena bentuknya bukan seperti tabel. Log management system dapat menangani data log dalam jumlah besar, menghasilkan detail informasi aktivitas, dan visualisasi data log yang lebih mudah dimengerti pengguna. Perangkat lunak ELK (Elasticsearch, Logstash, Kibana) bisa dikombinasikan dan diintegrasikan dalam server web untuk mengelola, manampilkan, dan mengawasi data-data log yang ada sehingga administrator jaringan dapat mengetahui kinerja yang terdapat pada server web. Implementasi dan uji coba menunjukkan pengawasan kinerja server web Apache yang lebih mudah dimengerti pengguna.
Interaction monitoring model of logo counseling website for college students’ healthy self-esteem Jacob Daan Engel; Ventje Jeremias Lewi Engel; Evangs Mailoa
International Journal of Evaluation and Research in Education (IJERE) Vol 9, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v9i3.20525

Abstract

The purpose of this research is to develop the client-counselor interaction monitoring model of the logo counseling website. The model attempts to help counselors in guiding and helping the students (clients) to achieve healthy self-esteem. Machine learning techniques integrated into the model will ensure that the recommendations can be available for counselors and supervisors in the near real-time environment. For the first implementation, a chatbot application is developed and tested with excellent responses from the students. Further research is needed to implement the complete specifications of the interaction monitoring model on the logo counseling website.