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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Mantik Penusa JIPN (Journal of Informatics Pelita Nusantara) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer ComTech: Computer, Mathematics and Engineering Applications Jurnal Mantik Jurnal Sains dan Teknologi TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) INFOKUM Journal of Computer Networks, Architecture and High Performance Computing International Journal of Basic and Applied Science Jurnal Media Informatika Journal Basic Science and Technology Jurnal Mandiri IT CEBONG Journal INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH LEBAH Indonesia Accounting Research Journal Journal of Computer Science and Research International Journal of Enterprise Modelling Journal of Defense Technology and Engineering
Hengki Tamando Sihotang
Universitas Putra Abadi Langkat
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MODEL TATA KELOLA DAN ARSITEKTUR TEKNOLOGI INFORMASI DAN KOMUNIKASI DI PERGURUAN TINGGI DALAM MENDUKUNG REVOLUSI INDUSTRI TAHAP 4.0 Hengki Tamando Sihotang; Harapan Lumbantoruan
Jurnal Mantik Penusa Vol. 3 No. 3 (19): COmputer Science
Publisher : Lembaga Penelitian dan Pengabdian (LPPM) STMIK Pelita Nusantara Medan

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Abstract

Implementation of Information Technology (IT Governance) in tertiary institutions has an important role in developing the Quality of Lecturers and Education Staff, especially Graduates and application of Information and Communication Technology (ICT) that they have in order to have maximum value. The convenience and improvement of services for stakeholders in the tertiary environment can be continuously improved by the application of targeted information technology. In order to maintain information technology as an added value in a tertiary institution, it is necessary to have a Governance Model so that all factors and dimensions related to Information Technology are synergized and able to provide added value and expected return on investment for tertiary institutions. The right IT Governance model for a university must be in line with the goal of IT Governance, which is able to align IT strategy with business strategies that exist in universities to improve the quality of graduates. This research is intended to develop ICT Standard Standards in Indonesian universities by using The Open Group Architecture Framework Architecture Development Method (TOGAF ADM) and Control Objectives for Information and related Technology (COBIT.5). TOGAF provides a detailed method description on how to build and manage and implement Enterprise Architecture (EA), while COBIT provides guidance for ICT management and governance. Both of these Frameworks are arranged in the hope of a comprehensive Management Model proposal so that it becomes a standard standard for every Indonesian tertiary institution.
Decision Support System For Choosing The Best Class Guardian With Simple Additive Weighting Method: Decision Support System For Choosing The Best Class Guardian With Simple Additive Weighting Method Dini Anggraini; Hengki Tamando Sihotang
Jurnal Mantik Vol. 3 No. 3 (2019): November: Manajemen, Teknologi Informatika dan Komunikasi (ManTIK)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Education is one of the most important things that can bring progress in a country. This study aims to design and build a decision system for the selection of the best supervisor class that can help the selection of supervisor class using the Simple Additive Weighting (SAW) method with pedagogic, personality, social, professionalism, education assessments. The SAW method is a method that uses the weighted sum. With this method the optimal solution is sought from alternatives and certain criteria. In this study, the researcher conducted research at SMA 1 Perbaungan so that the selection of the best supervisor class was right on target.
Clustering Of Polri Bintara Placement In North Sumatera Regional Police Using K-Means Algorithm: Clustering Of Polri Bintara Placement In North Sumatera Regional Police Using K-Means Algorithm Ririn Pebrina Br. Marpaung; Hengki Tamando Sihotang
Jurnal Mantik Vol. 3 No. 3 (2019): November: Manajemen, Teknologi Informatika dan Komunikasi (ManTIK)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Data mining on process carried out to obtain information from a database or data that can be used to help solve the latest problems or solutions, data mining that is used in this paper is the process of merging by using K-Means solutions. K-Means is one of the techniques used to group non-hierarchical (bulk) data which is supported to provide existing data partition in the form of two or more groups. This method partitioned the data in groups so that the different characteristic data was grouped into other groups. The purpose of grouping this data is to support the objective functions arranged in the grouping process, which generally support variations between groups and take advantage of variations between groups. The agreed clustering was the grouping of non-commissioned police officers in the North Sumatra regional police, with the data collection used was the placement data within the North Sumater Regional Police HR. The procedure that is carried out in this research is the problem process to the design and testing of the program. The knowledge gained from the grouping of the Bintara Police of the National Police in the North Sumatra Regional Police HR is the 5th data Placement based on data collected related to the position of the Brig Ro Sarpras of the North Sumatra Regional Police, as well as related to the data analysis with the K-Intended Algorithm in the North Sumatra Police Brigade. Based on the analysis of the latest number of changes based on the calculation of the K-mean algorithm ie the value 79-100 Being the range for the First cluster, the range 70-78 becomes the second cluster and 60-69 is categorized as the Third cluster. To produce a new pattern, a data mining process is carried out with different data..
Decision Support System For Prospective Recipients Of The Healthy Indonesia Card (Kis) In The Village Of Bah Sidua Dua With The Analytical Hierarchy Process (AHP) Method: Decision Support System For Prospective Recipients Of The Healthy Indonesia Card (Kis) In The Village Of Bah Sidua Dua With The Analytical Hierarchy Process (AHP) Method Elpridawati Purba; Hengki Tamando Sihotang
Jurnal Mantik Vol. 3 No. 3 (2019): November: Manajemen, Teknologi Informatika dan Komunikasi (ManTIK)
Publisher : Institute of Computer Science (IOCS)

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Abstract

This study discusses how to discuss a support system that is used to assist the village government in negotiations for potential beneficiaries in the village of Bah Sidua dua as serdang bedagai regencies. The method used in this research is Analyticah Hierarchy Process (AHP), because this method is widely used in solving problems involving multi criteria. SPK is a system that can help someone to make decisions of various types that are done accurately and in accordance with the desired goals.
Decision Support Systems Recipient Program Keluarga Harapan (PKH) In Durian Kec.Pantai Labu Kab. Deli Serdang with the Simple Additive Weighting (SAW) Method: Decision Support Systems Recipient Program Keluarga Harapan (PKH) In Durian Kec.Pantai Labu Kab. Deli Serdang with the Simple Additive Weighting (SAW) Method Rosulastri Purba; Hengki Tamando Sihotang
Jurnal Mantik Vol. 3 No. 3 (2019): November: Manajemen, Teknologi Informatika dan Komunikasi (ManTIK)
Publisher : Institute of Computer Science (IOCS)

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Abstract

This research examines how to design an application and build a decision support system in order to facilitate the process of determining beneficiaries of Program Keluarga Harapan (PKH). By using the Simple Additive Weighting (SAW) method, PKH beneficiaries are more targeted. The SAW method certainly uses a more accurate assessment because it is based on a criterion value of a predetermined preference weight. This research produces a system that is able to display the recommendation of prospective beneficiaries in accordance with the ranking of the criteria that have been determined according to the needs of the system
Decision Support Systems Assessment of the best village in Perbaungan sub-district with the Simple Additive Weighting (SAW) Method: Decision Support Systems Assessment of the best village in Perbaungan sub-district with the Simple Additive Weighting (SAW) Method Sri Devi; Hengki Tamando Sihotang
Jurnal Mantik Vol. 3 No. 3 (2019): November: Manajemen, Teknologi Informatika dan Komunikasi (ManTIK)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Information technology is a technology used to process data, including processing, obtaining, compiling storing, manipulating to produce quality information, which is relevant information that is accurate and timely in decision making. In the village assessment is an effort to encourage community efforts based on their own determination and strength as well as researching and assessing the success of community efforts in rural development such as improving the quality of economic, political, social, and cultural life as well as security and order. This research examines how to design an application and build a decision support system to facilitate the process of assessing the best villages. Using the Simple Additive Weighting (SAW) method, assess the best village to be more targeted. The SAW method certainly uses a more accurate assessment because it is based on the value of criteria and weight of predetermined preferences. This research produces a system that can display recommendations for the best village assessment with the results of the criteria that have been determined by the needs of the system.
Implementation Of C4.5 Algorithm To Analyze Library Satisfaction Visitors: Implementation Of C4.5 Algorithm To Analyze Library Satisfaction Visitors Fristi Riandari; Hengki Tamando Sihotang
Jurnal Mantik Vol. 4 No. 2 (2020): Augustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.875.pp1076-1084

Abstract

Measuring visitor satisfaction, especially in the library, is very important to note considering the library is a means intended to help the academic process or add insight to visitors. Measuring library visitor satisfaction is very important to note whether the services expected by visitors are in accordance with what is received, which will greatly assist the university in processing the library so that it can be used properly, so that the books provided can be of maximum use and not only the quality of service provided for the library provided can be an attraction for visitors to become fond of visiting the library reading books that will help academically the average visitor is a student. The system needed is the Data Mining Application in Measuring Satisfaction of library visitors at STMIK Pelita Nusantara. Where library visitors will be objects that provide an assessment / opinion on variables that have characteristics, namely Tangiable, Reability, Responsivnes, Assurance, Empathy. This system was built with the C4.5 algorithm and the Testing system with the application RapidMiner Studio 9.7.
Classification of Book Types Using the Support Vector Machine (SVM) Method Fristi Riandari; Hengki Tamando Sihotang; Tarisa Tarigan; Muhammad Rafli
Jurnal Mantik Vol. 6 No. 1 (2022): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

This study aims to create a model that can classify book types based on several categories and analyze the accuracy results of the Support Vector Machine (SVM) method. This research begins with the stages of data collection, namely the dataset of books obtained from the library. Furthermore, the dataset will be categorized into several types. The next stage, after the data is collected, will be carried out in the pre-process stage. This pre-process stage aims to prepare data so that it is ready to be processed in the feature extraction stage. The pre-processing stage consists of text segmentation, case folding, tokenization, stopword removal, and stemming. Next, the feature extraction stage will be carried out which aims to explore potential information and represent words as feature vectors. The next stage is to separate the training data and test data. Then the classification process is carried out using the SVM multiclass method to get the final result of modeling. The resulting classification results will then be evaluated in order to obtain an accuracy value and then will be analyzed whether the resulting classification model is feasible to implement.
Plant Disease Diagnosis Expert System Cardamom (Ammomum Cardamomum l.) Using The Naive Bayes Method Web-Based Calvin Berkat Iman Hulu; Hengki Tamando Sihotang
Jurnal Mandiri IT Vol. 10 No. 2 (2022): January: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (294.485 KB) | DOI: 10.35335/mandiri.v10i2.94

Abstract

Diseases and pests on cardamom plants is one of the diseases and pests that can seriously attack cardamom plants. Cardamom plant diseases and pests can be diagnosed through the symptoms that are currently being experienced by the cardamom or through its clinical picture, through these symptoms an expert system can be made to make a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The expert system made in carrying out the diagnosis uses the Naïve Bayes method. This method is a simple probabilistic-based prediction technique based on the application of Bayes' rules with the assumption of strong (naive) independence. In other words, in Naïve Bayes the model used is an “independent feature model”. This expert system was built using PHP and MySQL programming as a database. In this expert system the types of cardamom disease diagnosed consisted of aphids, leaf-eating caterpillars, stem borers, fruit and roots, leaf beetles, mosaics, late blight, root rot, and fungus, which consisted of 33 symptoms. While the results of the diagnosis will inform about the results of the diagnosis containing a list of symptoms entered, information on the results of regulations regarding diseases and pests that are attacking cardamom plants and information about possible treatments that can be carried out and treatment solutions.
Klasifikasi Kelayakan Kredit Pada Calon Debitur CS Finance Dengan Metode Naïve Bayes Hengki Tamando Sihotang; Dwiki Rivaldo Naidu; Harpingka Fitria Br. Sibarani
Jurnal Sains dan Teknologi Vol. 1 No. 2.1 (2019): Jurnal Sains dan Teknologi [SAINTEK] SPESIAL ISSUE
Publisher : Sistem Informasi Komputer dan Teknologi (SisfoKomTek)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34013/saintek.v1i2.1.221

Abstract

Kredit merupakan suatu sistem pinjam meminjam atas persetujuan yang telah disepakati diawal dengan phak bank atau institusi lembaga keuangan sejenis dengan nasabahnya. Dengan demikian analisa kelayakan pemberian kredit ini diharapkan dapat menganalisa solusi kesesuaian tingkat akurasi dalam sejumlah data yang sangat besar (big data) dengan melibatkan sebuah dataset yang nantinya akan dilakukan penambangan data dengan menggunakan tools rapid miner. Metode algoritma yang akan digunakan yakni metode data mining berupa Algoritma Naive Bayes Classifier. Klasifikasi data mining dapat membantu para analis kredit dalam hal menentukan signifikansi dan kelayakan pemberian kredit pada nasabah. Sehingga dari proses klasifikasi ini didapatkan berupa atribut penentu berupa kategori kelayakan dalam hal penentuan pemberian kredit kepada salah satu nasabah yang bersangkutan. Pengujian yang dilakukan yakni dengan menggunakan model confusion matrix yang melibatkan data training yang berbeda dalam hal jumlah atribut, dimana ekperimen pertama pengujian dilakukan terhadap 16 atribut data training kemudian ekperimen kedua pengujian dilakukan dengan melibatkan 9 atribut data training. Maka dari kedua eksperimen yang dilakukan akan diperoleh komparasi nilai akurasi, pengujian 16 atribut menghasilkan signifikansi akurasi 59,00% dan pengujian 9 atribut menghasilkan nilai akurasi sebesar 56,00 % sehingga dari kedua pengujian yang dilakukan dapat dipilih alternatif akurasi yang paling baik yakni pengujian dengan 16 atribut. Sehingga hasil dan output yang dihasilkan akan menghasilkan ketepatan pengujian atas suatu rekomendasi keputusan dalam membantu para profesional atau analis kredit di institusi keuangan dalam hal menentukan kelayakan pemberian kredit pada nasabahnya dengan bantuan algoritma yang digunakan untuk menyelesaikan suatu persoalan sehingga didapatkan pengidentifikasi terkait manakah yang layak atau tidak dikatakan sebagai penentuan pemberian kredit dengan mengacu pada penentuan kelas lancar atau bermasala
Co-Authors A, Galih Prakoso Rizky Achiriani, Tri Wahyuningtiyas Agustina Simangunsong Aisyah Alesha Aisyah Alesha Alrasyid, Wildan Anthoni Anggrawan Anthony Anggrawan Bambang Saras Yulistiawan Bosker Sinaga Budi Arif Dermawan Calvin Berkat Iman Hulu Chandra, Suherman Dadang Pyanto Delano, Aldrich Desi Vinsensia Dini Anggraini Dwiki Rivaldo Naidu Efendi, Syahril Elpridawati Purba Endang Mistaorina Laia Erwin Panggabean Fadiel Rahmad Hidayat Firmansyah Firmansyah Fransisco alexander Simbolon Fristi Riandari Galih Prakoso Rizky A Galih Prakoso Rizky A Guntur Syahputra Hapsanto, Henry Eko Harapan Lumbantoruan Harapan Lumbantoruan Harpingka Fitria Br. Sibarani Harpingka Fitriai Br. Sibaran Hasugian , Paska Marto Herlina Zebua Herman Mawengkang Hondor Saragih Husain Husain Hutahaean, Harvei Desmon I Made Aditya Pradhana Putra Jacob, Halburt Jane Irma Sari Jelita Sari Simanungkalit Jijon Raphita Sagala Joan De Mathew Jonhariono Sihotang Jonhariono Sihotang Jonson Manurung Judijanto, Loso Kouvelis Geovany Ortizan Laia, Endang Mistaorina Lemos, Sgarbossa Carlo Manurung, Jonson Maria Santauli Siboro Martinus Ndruru Melda Agustina Nababan Michaud, Patrisius Mochamad Wahyudi Muhammad Rafli Muhammad Zarlis Mulianingtyas, RR Octanty Murni Marbun Normi Verawati Marbun Panjaitan, Firta Sari Patricius Michaud Felix Patrisia Teresa Marsoit Pilisman Buulolo Prakoso Rizky A, Galih Pujiastuti, Lise R. Mahdalena Simanjorang Rasenda, Rasenda Rifka Widyastuti Rifka Widyastuti, Rifka Ririn Pebrina Br. Marpaung Rizky A, Galih Prakoso Rizky, Galih Prakoso Rohit Gautama Roma Sinta Simbolon Rosulastri Purba RR Octanty Mulianingtyas Santiwati Sihotang Santoso, Heroe Sethu Ramen Sihotang , Jonhariono Sihotang, Jonhariono Sim, Lee Choi Simbolon, Agata Putri Handayani Simbolon, Roma Sinta Simbolon, Romasinta Siringoringo, Rimmar Siskawati Amri Sitio, Arjon Samuel Song , Jiang Lou Sri Devi Sulindawaty, Sulindawaty Tarisa Tarigan Teresa, Patrys Vina Winda Sari Vinsensia, Desi Wildan Alrasyid Yulistiawan, Bambang Saras