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                  <text>VOL.  4, NO.  2 (2020)</text>
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                <text>Evaluasi Jaringan dan Interaksi Tim Sukses Pileg Tahun 2019 Melalui Social Network Analysis (SNA)</text>
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                <text>The 2019 Election, SNA, Network Formation, Density and Clique)</text>
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                <text>The 2019 elections in Indonesia was slightly different from the previous elections because the&#13;
elections were held simultaneously. It made more difficult for the community to make their&#13;
choices. Public was faced with a larger number of candidates who were not necessary known&#13;
as legislative candidates’ socialization is very important. This research discussed the process&#13;
of network formation and network structure that was formed. Data collection was carried out&#13;
through observation, interviews and questionnaires with 50 respondents as research samples.&#13;
The data obtained were processed using the UCINET tool which was then analyzed using&#13;
Social Network Analysis (SNA). The results showed that the process of network formation&#13;
occurred because of interpersonal contact between actors, the experiences of being a&#13;
successful team and relationships history between actors. The network structure formed was&#13;
closed with a high level of communication density that is 0,976. It was meant that all actors&#13;
made communication each other intensively. The actor who became the network booster was&#13;
actor id#02 which always appears in every click that was formed.&#13;
Pemilu tahun 2019 di Indonesia sedikit berbeda dengan pemilu sebelumnya karena pada tahun&#13;
2019 ini pemilu dilaksanakan secara serentak. Hal ini membuat masyarakat sulit dalam&#13;
menentukan pilihannya. Masyarakat dihadapkan pada jumlah calon yang banyak terutama&#13;
calon legislatif yang belum tentu dikenal sehingga sosialisasi caleg dirasa sangat penting.&#13;
Penelitian ini bertujuan untuk mengetahui proses pembentukan jaringan dan mempelajari&#13;
struktur jaringan yang terbentuk. Pengumpulan data dilakukan melalui observasi, wawancara&#13;
dan kuesioner terhadap 50 responden sebagai sampel penelitian. Data yang diperoleh diolah&#13;
dengan tools UCINET yang kemudian dianalisa menggunakan Social Network Analysis&#13;
(SNA). Hasil penelitian menunjukkan bahwa proses pembentukan jaringan terjadi karena&#13;
adanya kontak antar aktor, pengalaman menjadi tim sukses dan riwayat hubungan antar aktor.&#13;
Struktur jaringan yang terbentuk bersifat tertutup dengan tingkat density komunikasi tinggi&#13;
yaitu 0,976. Hal ini berarti seluruh aktor dalam jaringan saling berkomunikasi. Aktor yang&#13;
menjadi penggerak jaringan adalah aktor id#02 yang selalu muncul disetiap clique&#13;
(pengelompokan) yang terbentuk</text>
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                <text>Nining Fitriani, Irwan Sembiring, Kristoko Dwi Hartomo&#13;
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                <text>Perpustakaan Horizon Karawang</text>
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                <text>Fajar bagus W</text>
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        <name>Jurnal Nasional Informatika</name>
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                <text>Sistem Absensi Berbasis Pengenalan Wajah Secara Real Time menggunakan Metode Fisherface</text>
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                <text>Pengenalan Wajah, Fisherface</text>
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                <text>The face is a part that can be used for an identity of a person. Face recognition is used to&#13;
produce the detection of a human's face based on the database that is in it with a matching&#13;
process with the training data created. Face retrieval is taken in real time using a webcam&#13;
from a laptop, then the process of using the fisherface method here is used when the face&#13;
grouping process, fisherface is considered very good in the face recognition process because&#13;
fisherface can detect faces without having to be in good lighting. Attendance system using&#13;
face recognition was developed to replace the fingerprint system that is now widely used, this&#13;
system will later work to read the identity of someone by using faces as the recognition&#13;
process, the system is made using python opencv and GUI Tkinter as a display of the&#13;
program. The results obtained in this system are displaying the ID, Name, NIM, and Study&#13;
Program of a student. Furthermore, after the system recognizes faces, the attendance system&#13;
directly produces output ID, Name, and Date and Time which directly enter Ms. Excel. The&#13;
results of the system testing the accuracy of the system reached 80% with test data of 10 faces&#13;
and training data of 100 faces.&#13;
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                <text>Fajar Bagus W</text>
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                <text>Indonesia</text>
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                <text>Fajri, T. Rahmad Effendi, Nurul Fadillah </text>
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                  <text>VOL.  4, NO.  2 (2020)</text>
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            <description>A name given to the resource</description>
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                <text>Rancang Bangun Jaringan Vlan dengan Menggunakan Simulasi Cisco Packet Tracer</text>
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                <text>VLAN, Cisco Packet Tracer, Simulasi</text>
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                <text>Pemanfaatan teknologi komputer pada era digital memiliki peranan yang sangat besar dalam&#13;
dunia industry. Komputer yang telah diprogram memiliki kemampuan untuk melaksanakan&#13;
berbagai macam pekerjaan sehingga dapat meringankan pekerjaan manusia menjadi lebih&#13;
efisien dan efektif. Pemanfaatan komputer tidak hanya untuk dunia industry saja tetapi juga&#13;
dalam dunia pendidikan penggunaan komputer sangat dibutuhkan. Dalam dunia pendidikan&#13;
para peserta didik dari Sekolah Menengah Kejuruan dituntut untuk terus mengasa kemampuan&#13;
agar memiliki kompetensi di bidangnya. Untuk mengasah kemampuan dari peserta didik&#13;
pihak penyelenggara pendidikan akan membuatkan suatu tempat khusus sebagai bahan&#13;
praktek bagi peserta didik. Dalam pengadaan tempat praktek tersebut dibutuhkan suatu biaya&#13;
yang sangat besar, apalagi jumlah jurusan yang ada disekolah lebih dari satu jurusan. Untuk&#13;
dapat menghemat anggaran tersebut maka dibuatkanlah suatu jaringan VLAN. Pada penelitian&#13;
ini akan melakukan perancangan jaringan VLAN dengan menggunakan aplikasi Cisco Packet&#13;
Tracer sebagai media untuk mensimulasikan jaringan. Dengan aplikasi tersebut akan&#13;
dirancang jaringan VLAN dengan membuat kelompok jaringan untuk LAB TKJ dan LAB&#13;
MM dalam satu jalur.</text>
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                <text>Ruhiat Susanto</text>
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                <text>Perpustakaan Horizon Karawang</text>
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                <text>Fajar Bagus W</text>
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                <text>Wireless Network Authentication System Using RADIUS (Remote Authentication Dial In-User Service) Server (Case Study: Universitas Muhamadiyah Riau)</text>
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                <text>Radius; Authentication, Internet; Hotspot; Wireless</text>
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                <text>The Universitas Muhammadiyah Riau has applied the application of wireless internet-based&#13;
networks. As a driving force for services to support academic and non-academic activities, the&#13;
Universitas Muhammadiyah Riau provides hotspots in almost all areas of the campus. This&#13;
study will build an existing network that is available using academic databases as user data to&#13;
connect, monitor the activities of each user's activities. The flow of research is carried out to&#13;
parse the research plan that will be carried out starting from the collection of funds, analysis,&#13;
configuration to testing, aiming that the material presented in the form of reports in accordance&#13;
with the planned research flow. The hotspot authentication system that is integrated into the&#13;
academic database of the Universitas Muhammadiyah Riau was developed using the Python&#13;
programming language, PHP, Java, and the MYSQL database can be implemented properly.&#13;
There are 3 (three) types of tests carried out Testing the user connection side, testing the&#13;
Bandwidth settings and monitoring as well as Testing the computer network profile settings.&#13;
The integration of the Muhammadiyah Riau University database server and RadiusDesk was&#13;
successful so that the priority of sharing access to users could be mapped to the maximum.</text>
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                <text>Mitra Unik , Suryanto , Januar Al Amin </text>
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                <text>Every school in Indonesia have a canteen. The canteen provided by schools to&#13;
meet the needs of students. The diversity of students patterns in buying drinks&#13;
and foods in canteen also varies. to find out how the pattern of these students in&#13;
buying food in the canteen is to use one of the data mining methods, namely&#13;
FP-Growth. FP-Growth is an improvement of apriori algorithm. FP-Growth&#13;
builds FP-Tree. The databases have to be scanned twice in FP-Tree to determine&#13;
frequent itemset, so making it more effective than apriori. The data used in this&#13;
research is transaction data to buy foods and drinks in the canteen. This research&#13;
used Rapidminer software for association rules. The results of this research have&#13;
two forms, the rules that are calculated manually and the rules through&#13;
Rapidminer. Then the results will be used for canteen manager to study the&#13;
patterns of students in buying drinks and foods in the canteen.</text>
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                <text>Design and Control System Monitoring of Water Quality on Tilapia Cultivation Farm based Internet of Things (IoT) with NodeMCU </text>
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                <text>Fish cultivation has a high potential to improve the welfare of the community. One of the&#13;
important factors influencing the success of fish cultivation is the aspect of water quality in&#13;
the pond which is illustrated by several physical parameters such as temperature, degree of&#13;
acidity (pH) and turbidity of the water. The use of water for cultivation must always be&#13;
maintained at turbidity level, the impact of turbid water causes disruption to the physical&#13;
growth of the fish and even death. Due to the limitations of humans who cannot monitor&#13;
ponds 24 hours, a system is created that can monitor and control water quality in real time. To&#13;
get good water quality for cultivation, the authors make this system using a turbidity sensor to&#13;
detect water turbidity, a pH sensor to detect the acidity of the water and a temperature sensor&#13;
to detect the temperature of the water on the pond. While processing and control using a&#13;
microcontroller, namely NodeMCU. Periodically the sensor will send the measurement results&#13;
to the Cayenne application in real time which can be viewed via a smartphone / PC. The&#13;
control system is also made with two modes, namely automatic and manual modes to fill and&#13;
drain water on the pond. Based on the results of system testing, turbidity, pH and temperature&#13;
sensors are very good in detecting any changes in pond water conditions. Cayenne application&#13;
with IoT technology is able to provide action on the water pump in the process of draining and&#13;
filling water in ponds with manual mode. NodeMCU is able to send data with a good internet&#13;
connection.</text>
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                <text>Fathimah Nur Afifah, Emy Haryatmi</text>
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                <text>Penggabungan Gambar Panorama Menggunakan Metode Sift (Scale Invariant Feature Transform)</text>
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                <text>Penggabungan, Panorama, Citra, SIFT </text>
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                <text>Penggabungan gambar merupakan suatu proses menggabungkan gambar yang berbeda dan&#13;
tumpang tindih menghasilkan sebuah gambar panorama. Gambar panorama adalah sebuah&#13;
gambar yang memiliki sudut pandang yang luas dan sering disebut wide angle. Pengenalan&#13;
objek merupakan suatu proses yang memberikan klarifikasi terhadap objek bentuk tertentu&#13;
pada suatu gambar. Pengenalan objek memiliki tahap deteksi dan pengenalan. Ekstraksi fitur&#13;
merupakan salah satu tahap untuk mengambil fitur-fitur penting yang mencirikan objek yang&#13;
ingin dikenali. Salah satu metode ekstraksi fitur yaitu SIFT (Scale Invariant Feature&#13;
Transform) dikatakan bahwa metode ini tidak terpengaruh oleh perubahan ukuran, adanya&#13;
translasi, atau rotasi pada objek. Metode ini digunakan untuk pencarian keypoint. Jumlah&#13;
keypoint dapat berubah berdasarkan nilai threshold. Jikalau nilai threshold lebih tinggi maka&#13;
pencarian keypoint lebih akurat. Pada percobaan dengan nilai threshold 1 ditemukan keypoint&#13;
sebanyak 41 dan nilai erornya 0,2743. Pada saat nilai threshold dinaikkan menjadi 3 jumlah&#13;
keypoint yang ditemukan adalah 90 dan nilai erornya 1,0541</text>
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                <text>Ilmi Hasny, Munawir, Nurul Fadillah</text>
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                <text>Perpustakaan Horizon Karawang</text>
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                <text>Fajar bagus W</text>
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                <text>Implementasi Face Recognition pada Absensi Kehadiran Mahasiswa Menggunakan Metode Haar Cascade Classifier</text>
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                <text>Face Recognition, Face Detection, Multiple Face Recognition, Absensi, Haar Cascade Classifier</text>
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            <description>An account of the resource</description>
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                <text>Face recognition is on of the biometric system that is most used today. The biometric system&#13;
with face recognition can be applied in the attendance process. Attendance is a very useful factor&#13;
for various purposes and is one of the most important valuation criteria in an institution. As well&#13;
as in the educational world, attendance is also very important to know and control the discipline&#13;
of the students. Currently, the attendance process is still carried out manually and judged less&#13;
effectively, so that in this research will be carried out attendance process with face recognition&#13;
that is considered capable to efficiencies recording time Presence. The method used on this&#13;
research is the Haar Cascade Classifier. There are 125 face training data from 25 students who&#13;
have been inputed into the system. Testing is done by the recognition of one face and multiple&#13;
face recognition at once. The results of this research showed that the level of one face&#13;
recognition with 25 data testing face obtained 76%, while the level of many faces recognition&#13;
obtained 33.3%.</text>
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                <text>Munawir, Liza Fitria, Muhammad Hermansyah</text>
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                <text>Perpustakaan Horizon Karawang</text>
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