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All Journal International Journal of Electrical and Computer Engineering 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 Journal of Computer Science and Research International Journal of Enterprise Modelling
Hengki Tamando Sihotang
Universitas Putra Abadi Langkat
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Journal : Jurnal Mantik

 1 
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)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (654.317 KB)

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.
Student Graduation Value Analysis Based On External Factors With C4.5 Algorithm Fristi Riandari; Hengki Tamando Sihotang; Rohit Gautama; Sethu Ramen
Jurnal Mantik Vol. 6 No. 2 (2022): August: 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.v6i2.2784

Abstract

Data mining is the process of extracting data into information that has not previously been conveyed, with the right techniques the data mining process will provide optimal results. Data Mining is divided into several methods. Data classification is a process of finding the same properties in a set of objects in a database and classifying them into different classes according to the defined classification model. The purpose of classification is to find a model from the training set that distinguishes attributes into the appropriate category or class, the model is then used to classify attributes whose class has not been previously known. The classification technique is divided into several techniques, one of which is the Decision Tree. One of the existing approaches in the classification technique is the C4.5 algorithm. The C4.5 algorithm is an approach in data mining classification techniques that can predict students' final grades. The variables used in analyzing the passing grades will be classified based on their attributes. The C4.5 algorithm with the decision tree method can provide predictive rule information to describe the process associated with analyzing student passing grades. The characteristics of the classified data can be obtained clearly, both in the form of a decision tree structure and rules so that in the testing phase the RapidMiner software can help predict student passing grades. With the formation of rules that can become new information that can be used as a tool in analyzing student passing grades.
Co-Authors 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 Guntur Syahputra Harapan Lumbantoruan Harapan Lumbantoruan Harpingka Fitria Br. Sibarani Harpingka Fitriai Br. Sibaran Hasugian , Paska Marto Herlina Zebua Herman Mawengkang Husain Husain Hutahaean, Harvei Desmon Jacob, Halburt Jane Irma Sari Jelita Sari Simanungkalit Jijon Raphita Sagala Joan De Mathew Jonhariono Sihotang Jonhariono Sihotang Judijanto, Loso Kouvelis Geovany Ortizan Laia, Endang Mistaorina Lemos, Sgarbossa Carlo 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 Pujiastuti, Lise R. Mahdalena Simanjorang Rasenda, Rasenda Rifka Widyastuti, Rifka Ririn Pebrina Br. Marpaung Rizky A, Galih Prakoso Rizky, Galih Prakoso Rohit Gautama Roma Sinta Simbolon Rosulastri Purba 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