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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer SEMIRATA 2015 Seminar Nasional Informatika (SEMNASIF) CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Teknik Informatika UNIKA Santo Thomas MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Query : Jurnal Sistem Informasi JOURNAL OF SCIENCE AND SOCIAL RESEARCH KOMPUTA : Jurnal Ilmiah Komputer dan Informatika CSRID (Computer Science Research and Its Development Journal) Jurnal Varian Dinasti International Journal of Education Management and Social Science JTIK (Jurnal Teknik Informatika Kaputama) KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer Jurnal Tekinkom (Teknik Informasi dan Komputer) Jurnal Teknik Informatika C.I.T. Medicom JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JUKI : Jurnal Komputer dan Informatika MEANS (Media Informasi Analisa dan Sistem) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Ipteks Terapan : research of applied science and education Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Dinamika Informatika (JDI) Data Sciences Indonesia (DSI) International Journal of Economic, Technology and Social Sciences (Injects) Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Proceeding Of International Conference On Education, Society And Humanity "Journal of Data Science

Zakarias Situmorang

FIKOM, Universitas Katolik Santo Thomas

Author-ID : 1908151

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Analisis Pengamanan Jaringan Pada Protokol IPv6 Menggunakan Multi-Layer IPSec Asrizal Asrizal; Syahril Efendi; Zakarias Situmorang
Query: Journal of Information Systems VOLUME: 03, NUMBER: 02, OCTOBER 2019
Publisher : Program Studi Sistem Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (855.568 KB)

Security is an important aspect in computer network operations. To support, computer network security, various security methods have been developed, both in application level security, such as Pretty Good Privacy (PGP), end-system level security, such as Socket Secure Layer (SSL), direct-link level security such as Multi Protocol Level Switching (MPLS) and IP layer security such as IP Security (IPSec). IPSec is a collection of protocols for securing networks through authentication and IP packet encryption. On the other hand, Internet Protocol Version 4 (IPv4) as a network protocol is not safe enough and is no longer able to serve the needs of new IP addresses around the world, and will soon be replaced with IPv6. Therefore, it is necessary to examine various security methods that can be developed in IPv6. In this study, the author will analyze the Multi-Layer IPSec in securing IPv6 networks.Keywords: IPv6, IPSec, Multi-Layer IPSec

REGRESI LINIER BERGANDA UNTUK MEMPREDIKSI JUMLAH NASABAH Agus Fahmi Limas Putra; Junaidi Junaidi; Zakarias Situmorang; Asyahri Hadi Nasyuha
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 5, No 2 (2022): June 2022
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v5i2.915

Industri perbankan merupakan sektor penting dalam pembangunan maupun dalam pemodalan usaha dan dipandang sebagai inti dari sistem perekonomian. Melihat hal ini, pemerintah melonggarkan aturan-aturan bagi perbankan dan non perbankan baik dari sektor pemerintah ataupun swasta untuk memberikan pinjaman atau bantuan kepada para nasabah atau pelaku UMKM. Banyaknya nasabah-nasabah dalam penyaluran kredit atau perbankan juga akan banyak terjadi masalah – masalah dalam pinjaman ataupun pengembalian pinjaman dana, maka dari itu pihak penyaluran kredit harus siap menghadapi resiko kredit yang bermasalah atau biasa disebut dengan kredit macet. Penelitian ini bertujuan untuk menciptakan suatu sistem berbasis komputerisasi, kemudian dengan diterapkannya sistem tersebut maka hasil yang didapatkan akan benar-benar akurat dan cepat. Diharapkan metode regresi linier berganda ini dapat menyelesaikan permasalahan dalam menangani atau mengatasi nasabah yang bermasalah sehingga dapat membantu pihak perusahaan untuk memprediksi jumlah kredit macet setiap bulannya.

PERBANDINGAN AKURASI ALGORITMA NAÏVE BAYES, K-NN DAN SVM DALAM MEMPREDIKSI PENERIMAAN PEGAWAI Novendra Adisaputra Sinaga; B Herawan Hayadi; Zakarias Situmorang
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.446

To supporting academic and non-academic activities, the Polytechnic Business Indonesian (PBI) must be supported by employees with reliable Human Resources (HRD) who have good behavior, good abilities and can complete work professionally and responsibly. Conventional techniques for analyzing existing large amounts of data cannot be handled which is the background for the emergence of a new branch of science to overcome the problem of extracting important information from data sets, which is called Data Mining. Utilizing methods to classify data by utilizing methods including: Naïve Bayes method, K-Nearest Neighbor (K-NN) and Supervise Vector Machine (SVM). From this research, in Predicting Applicants Graduation at PBI, the SVM method is better than Naïve Bayes and K-NN. With 33 test data used, SVM has 84.9% accuracy, 85.1% precision while K-NN has 81.8% accuracy, 84.1% precision and Naïve Bayes has 78.8% accuracy and 80.1% precision.

ANALISIS VARIATION K-FOLD CROSS VALIDATION ON CLASSIFICATION DATA METHOD K-NEAREST NEIGHBOR Ridha Maya Faza Lubis; Zakarias Situmorang; Rika Rosnelly
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 14 No. 3 (2020): Re Publish Issue
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

To produce a data classification that has data accuracy or similarity in proximity of a measurement result to the actual numbers or data, testing can be done based on accuracy with test data parameters and training data determined by Cross Validation. Therefore data accuracy is very influential on the final result of data classification because when data accuracy is inaccurate it will affect the percentage of test data grouping and training data. Whereas in the K-Nearest Neighbor method there is no division of training data and test data. For this reason, researchers analyzed the determination of training data and test data using the Cross validation algorithm and K-Nearest Neighbor in data classification. The results of the study are based on the results of the evaluation of the Cross Validation algorithm on the effect of the number of K in the K-nearest Neighbor classification of data. The author tests using variations in the value of K K-Nearest Neighbor 3,4,5,6,7,8,9. While the training and test data distribution using Cross validation uses variations in the number of K-Fold 1,2,3,4,5,6,7,8,9,10

COMPARATIVE OF ID3 AND NAIVE BAYES IN PREDICTID INDICATORS OF HOUSE WORTHINESS Ade Clinton Sitepu; Wanayumini -; Zakarias Situmorang
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 14 No. 3 (2020): Re Publish Issue
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Decision making is method of solving problems using certain way / techniques so that can beaccepted. After making some calculations and considerations through several stages, the decisionhave taken that decision maker goes through. This stage will be selected until the best decision hasmade. Decision-making aims to solve problems that solve problems so that decisions with finalgoals can be implemented properly and effectively. This study uses a simulation of decision makingfrom seven attributes to the proportion of the feasibility of a house based on data from CentralStatistics Agency (BPS). There are several techniques for presenting decision making including: ID3(decision tree) algorithm concept and Naïve Bayes algorithm. Both classification are learningsuperviseddata grouping. ID3 algorithm depicts the relationship in the form of a tree diagramwhereas Naïve Bayes makes use of probability calculations and statistics. As a result, in datatraining, decision trees are able to model decision making more accurately. The prediction resultsusing the decision tree model = 90.90%, while Naïve Bayes = 72.73%. Meanwhile, the speed of theNaive Bayes algorithm is better

ALGORITMA C45 DALAM MEMPREDIKSI MINAT CALON MAHASISWA Zakarias Situmorang; Sartika Mandasari; Yuni Franciska; Karina Andriyani; Puji Sari Ramadhan
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 5, No 1 (2022): February 2022
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v5i1.809

Penelitian ini membahas tentang memprediksi minat calon mahasiswa sebelum mendaftar di program studi yang dituju. Dalam memprediksi minat mahasiswa STMIK Triguna Dharma belum memiliki sebuah sistem yang mampu melakukan prediksi dalam mengetahui minat calon mahasiswa yang akan mendaftar(Haryoto et al., 2021). Untuk menyelesaikan permasalahan tersebut maka dibutuhkan sebuah algoritma yang mampu menghasilkan keputusan tentang minat calon mahasiswa yang akan mendaftar. Berdasarkan penelitian yang telah dilakukan maka diperoleh hasil 4 aturan baru dengan menggunakan kriteria jenis kelamin, minat, jurusan asal sekolah dan hobi. Dengan hasil ini dapat diketahui bahwa algoritma C45 telah terbukti berhasil melakukan analisis terhadap minat calon mahasiswa baru diÂ STMIK Triguna Dharma.

Prototipe Sistem Fire Detector Berbasis Arduino Uno dan Web Rubianto Rubianto; Zakarias Situmorang; Yusfrizal Yusfrizal
JTIK (Jurnal Teknik Informatika Kaputama) Vol 6, No 2 (2022): Volume 6, Nomor 2 Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Banyaknya bencana kebakaran yang dapat muncul dari hal-hal yang sepele yang dapat menimbulkan kerugian berupa materil, psikologis bahkan korban jiwa. Prototipe ini dirancang untuk dapat mendeteksi kebakaran pada suatu ruangan, yang terdiri dari Sensor Suhu LM35DZ, Sensor Gas MQ-135, Mikrokontroler Arduino Uno, Modul Ethernet Shield W5100 dan adaptor sebagai catu daya. Kemudian, sensor suhu akan mendeteksi suhu di sekitar ruangan (dalam satuan ⁰C) dan sensor gas akan mendeteksi gas yang ada di sekitar ruangan, khusunya karbon monoksida (dalam satuan ppm). Ketika kedua sensor mendeteksi suhu dan gas dalam jumlah tertentu, maka akan dibandingkan dengan setpoin yang sudah di tetapkan pada mikrokontroler Arduino Uno. Jika hasil pengukuran kedua sensor lebih kecil dari setpoin, maka tidak ada tampilan peringatan. Tetapi jika hasil pengukuran kedua sensor lebih besar dari setpoint, maka akan muncul peringatan. Peringatan akan ditampilkan dalam web menggunakan bantuan Modul Ethernet Shield W5100 melalui koneksi LAN. Tampilan pada web, berupa peringatan “Bahaya”. Jadi ketika hasil pengukuran lebih besar dari setpoin, dapat dimungkinkan terjadi kebakaran pada ruangan tersebut. Prototipe ini dapat bekerja baik di dalam ruangan. Selisih perbandingan suhu antara LM35 dengan termometer batang adalah 0,18 ⁰C.

Optimization Of Determination Against K-Means Cluster Algorithm Using Elbow Creation Melda Pita Uli Sitompul; Opim Salim Sitompul; Zakarias Situmorang
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.176.pp1-9

Clustering is a data mining method for grouping data that have similar or different characters in each section. One of the methods is using K-Means by measuring the distance between clusters using the shortest distance or Euclidean Distance. K-means entails weakness, which is the determination of clusters in k-means clustering, resulting in the different data grouping and affecting the results of the data cluster distribution. To overcome this issue, the elbow creation method is employed to determine the similarity level in the cluster by observing the comparison between Root Means Square and R Square to measure the homogeneity and heterogeneity of the cluster where this method is applied by considering the changes in the comparison between the RMSSTD (Root Means Square Standard Deviation) and RS (R Squared) values which have the intersection of the RMSSTD and RSquared values. The difference between RMSSTD cluster 1 and RMSSTD cluster 2 was 0.066 and RS cluster 1 and RS cluster 2 was -0.304. Based on those figures, the highest difference was found in cluster 2. All considered, tourist destinations in East Asia frequently visited or interested to visitors are grouped into cluster 2, comprising criteria 6, 7, 8, and 10, or in other words, resort destination, picnic area, beaches, and religious institutions

Analisa Distance Metric Algoritma K-Nearest Neighbor Pada Klasifikasi Kredit Macet Khairul Fadhli Margolang; Muhammad Mizan Siregar; Sugeng Riyadi; Zakarias Situmorang
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Data mining is a method that can classify data into different classes based on the features in the data. With data mining, non-performance loan categories can be classified based on data on lending from cooperatives to their members. This study uses K-Nearest Neighbor to classify non-performance loan categories with various distance metric variations such as Chebyshev, Euclidean, Mahalanobis, and Manhattan. The evaluation results using 10-fold cross-validation show that the Euclidean distance has the highest accuracy, precision, F1, and sensitivity values compared to other distance metrics. Chebyshev distance has the lowest accuracy, precision, sensitivity, while Mahalanobis distance has the lowest F1 value. Euclidean and Manhattan distances have the highest reliability values for true-positive and true-negative class classifications. Mahalanobis distance has the lowest reliability value for false-positive class classification, while Chebyshev distance has the lowest value for false-negative class classification

Prediksi Pemberian Rekomendasi Kenaikan Pangkat PNS Menggunakan Metode Naïve Bayes Desi Irfan; Irwan Daniel; Adam Sagara; Zakarias Situmorang
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

A civil servant or civil servant (English: civil servant, Dutch: ambtenaar) is a person employed by a government agency to provide public services. As a profession, civil servants are positions that are pursued through career paths and not based on general elections involving the people's vote. Quoted from the Regulation of the Head of BKN No. 35 of 2011 concerning Guidelines for the Preparation of PNS Careers, the career pattern of civil servants is arranged based on the principles of certainty, professionalism, and transparency. One of the requirements to achieve the desired career is through the promotion process. The promotion or class of a civil servant cannot be separated from the recommendation of the leadership. A leader in providing recommendations must look at several important points that must be possessed by employees who will be given recommendations such as Attendance, Integrity, Cooperation and Insight or Knowledge. In the process, there are still problems in terms of technical and effectiveness because manual assessments sometimes still assess subjectively. Therefore, a study was carried out for the classification of the determination of the status of giving recommendations using the Naïve Bayes method. Naive Bayes is one method of probabilistic reasoning. The Naive Bayes algorithm aims to classify data in certain classes, then the pattern can be used to estimate the employee who will be given a recommendation, so that the leader can make a decision to give recommendation or not to the employee

Co-Authors Adam Sagara Ade Clinton Sitepu Ade Clinton Sitepu Adelina, Mimi Chintya Aditia Rangga Agus Fahmi Limas Putra Alkhairi, Putrama Asrizal Asrizal Asyahri Hadi Nasyuha B. Herawan Hayadi Budi K. Hutasuhut Daim Azhari Parinduri Desi Irfan Doughlas Pardede Efendi, Syahril Ela Roza Batubara Erna Budhiarti Nababan Fazli Nugraha Tambunan Ginting, Emnita Boru Handayani, Meli Hartono Hartono Herman Mawengkang Husein, Alice Erni Ichsan Firmansyah Irwan Daniel Irwan Daniel Ita Juwita Saragih Jaka Tirta Samudra Jaka Tirta Samudra Jaka Tirta Samudra Jaka Tirta Samudra Jazi Eko Istiyanto Jinan, Abwabul Jinan, Abwabul Junaidi Junaidi Karina Andriyani Kelvin Leonardi Kohsasih Khairul Fadhli Margolang Khoirunsyah Dalimunthe Kusuma, Jaka Lestari, Valencya Lewis, Andreas Lubis, Cindy Paramitha Lusi Herlina Siagian M Anggi Rivai Nst Manungkalit, Jupri Maria Claudia Purba Masri Wahyuni Mawaddah Harahap Mawaddah Harahap, Mawaddah Melda Pita Uli Sitompul Muhadi M. Ilyas Gultom Muhammad Mizan Siregar Muhammad Zarlis Muhammad Zarlis, Muhammad Nababan, Junerdi Novendra Adisaputra Sinaga Opim Salim Sitompul P.P.P.A.N.W. Fikrul Ilmi R.H. Zer Pradipta, Muhammad Iqbal Pratiwi, Mariska Putri Puji Sari Ramadhan Purba, Andry Hery Putrama Alkhairi Raden Aris Sugianto Rahmad, Sofyan Retantyo Wardoyo Riandini, Maisarah Ridha Maya Faza Lubis Ridha Maya Faza Lubis Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly, Rika Rimbun Siringoringo, Rimbun Romanus Damanik Roslina, Roslina Rubianto Rubianto Sartika Mandasari Sembiring, Rahmat Widya Sri Hartati Sugeng Riyadi Tarigan, Dede Ardian Tulus Tulus Wanayumini Yoppi, Edunal Yuni Franciska Yusfrizal Yusfrizal Yusniar Lubis Yusniar Lubis Yusniar Lubis

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