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All Journal IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Sinkron : Jurnal dan Penelitian Teknik Informatika METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Kesehatan Masyarakat dan Lingkungan Hidup International Journal of Engineering, Science and Information Technology

Sinambela Marzuki

Fakultas Ilmu Komputer, Universitas Methodist Indonesia.

Author-ID : 3759716

Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Articles

Machine Learning for Handoffs Classification Based on Effective Communication History Simbolon, Anita Ira Agustina; Pujiastuti, Maria; Jaya, Indra Kelana; Tarigan, Kerista; Sinambela, Marzuki
Sinkron : jurnal dan penelitian teknik informatika Vol. 3 No. 2 (2019): SinkrOn Volume 3 Number 2, April 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (248.188 KB)

An important step in data effective communication in handoffs process analysis is data exploration and representation. Communication in handoff treatment is crucial to protect the patients and it can lead to patient’s safety, discontinue care of a patient or the cause loss of important information related to the continuum of care. In this case, we use the machine learning technique by using Support Vector Machine for classification the handoffs for twenty weeks to analysis and represented based on the effective communication history. We used handoffs dataset which employed from Arifin Achmad Hospital in Pekanbaru, Indonesia. The result indicated the performance of the designed system was successful and could be used in handoffs analysis based on the effective communication histories in Arifin Achmad Hospital in Pekanbaru, Indonesia.

PEMETAAN MIKROZONASI DALAM MENDUKUNG PERENCANAAN DAN PENGEMBANGAN KELEMBAGAAN LINGKUNGAN HIDUP Teguh Rahayu; R Hamdani Harahap; Marzuki Sinambela
Jurnal Kesehatan Masyarakat dan Lingkungan Hidup Vol 5 No 1 (2020): JURNAL KESEHATAN MASYARAKAT DAN LINGKUNGAN HIDUP
Publisher : UNIVERSITAS SARI MUTIARA INDONESIA

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Pengembangan kelembagaan lingkungan hidup menjadi prioritas dalam pengurangan tingkat resiko kerusakan lingkungan. Perlunya kajian dan kolaborasi antara kelembagaan akan mempengaruhi keberhasilan dalam pembangunan dan kesejehteraan masyarakat. Dalam hal ini, pengurangan resiko kerusakan lingkungan dapat dilakukan dengan melakukan pemetaan terhadap bencana alam. Penelitian ini berfokus pada pengurangan dampak resiko gempabumi terhadap lingkungan. Penelitian ini juga bertujuan untuk melakukan pendekatan terhadap kelembagaan lingkungan hidup yang memegang peranan dalam kebijakan pembangunan dan perencanaan, khususnya kajian mikrozonasi sebagai upaya pemetaan resiko kerusakan lingkungan di kota Medan, Sumatera Utara.

THE TRANSLATION OF CIVIL AVIATION SAFETY REGULATION PART 170 AIR TRAFFIC RULES INTO INDONESIAN Sylvia Tiara; Hutabarat Tommy Liber; Saragih Azhari Nisa; Sinambela Marzuki
IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Vol 7, No 1 (2019): IDEAS: Journal on English Language Teaching and Learning, Linguistics and Litera
Publisher : Institut Agama Islam Negeri Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/ideas.v7i1.719

The background of this research was based on the continued development of international aviation in the world which was a challenge for the translator to find an equivalent sentence. The purpose of this thesis was to find the equivalence type used in translating the source language to the target language and find the dominant equivalence type used. For solving this problem, the writer used Nida and Taber theory that divided equivalence types into two types, namely formal equivalence or formal correspondence and dynamic equivalence. The method used was descriptive qualitative method. The data was obtained through systematic sampling method. Based on the analysis, the equivalence types of 53 of 66 samples (80%) were translated by using formal correspondence; 12 of 66 samples were translated using dynamic equivalence (18%) and only one sample (2%) did not neither involve in formal correspondence nor dynamic equivalence because SL text did not have translation in TL (reserved). The most dominant equivalence type used in the translation was formal correspondence.

TIME SERIES FORECASTING FOR AVERAGE TEMPERATURE IN 96041 STATION USING LONG SHORT-TERM MEMORY MODEL Nancy Lusiana Damanik; Elida Pane; Kartika Dewi; Efrianses F. H. Sinaga; Jamaluddin Jamaluddin; Hiras Sinaga; Marzuki Sinambela
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 5 No. 1 (2021): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

An understanding of patterns and gauge of normal temperature joined of parameter climate and climate information for way better water asset administration and arranging during a bowl is exceptionally vital. Investigate climate patterns utilizing typical and neighborhood annually normal temperatures, compare and make perceptions. during this consider, we'll analyze nearby and ordinary normal temperature information in 96041 Station supported perception station in place. the foremost objective of this considers to seem the execution of the traditional temperature in an exceedingly single station and to foresee the conventional temperature information utilizing the Long memory Demonstrate approach. supported the results of ordinary informatics of investigating temperature with nearby temperature relationship, we got the show of preparing bend, remaining plot, and therefore the diffuse plot is appeared utilizing these codes. the nice execution of 96041 Station had an Mean Squared Error esteem of 0.01 and R squared esteem 0.98, concerning zero will speak to superior quality of the indicator.

CLASSIFICATION OF STUDENT’S AIR TRAFFIC CONTROL SKILL USING LOGISTIC REGRESSION Liber Tommy Hutabarat; Hairul Amren S.; Marzuki Sinambela; Tonni Limbong
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 3 No. 2 (2019): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

The classification of student’s air traffic control skills at Akademi Teknik dan Keselamatan Penerbangan Medan (ATKP) is very interesting to evaluate and look at the performance of the student. In this study, we compute the student’s air traffic control (ATC) skill data to classify and evaluate the model and performance of the dataset. The computation of the dataset using the logistic regression approach based on Sk-learn by training and test data. The data was collected from ATKP for twenty samples. The result of this study indicates the logistic regression classifier is the best algorithm for this classification problem, offering good values in terms of accuracy, true negative rate, and true positive rate.

Supervised models to predict the Stunting in East Aceh Eva Darnila; Maryana Maryana; Khalid Mawardi; Marzuki Sinambela; Iwan Pahendra
International Journal of Engineering, Science and Information Technology Vol 2, No 3 (2022)
Publisher : Master Program of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Nowadays, Undernutrition is the main cause of child death in developing countries. There are many people and organizations try to mitigate or minimize case of child death. Thus, this paper aimed to has excellent method to handle undernutrition case by exploring the efficacy of machine learning (ML) approaches to predict Stunting in East Aceh administrative zones of Indonesia and to identify the most important predictors. The study employed ML techniques using retrospective cross-sectional survey data from East Aceh, a national-representative data is collected from government by using 2019 about stunting data. We explored Random forest commonly used ML algorithms. Random Forest (RF) as an extension of bagging that in addition for taking random sample of data and also uses random subset of features which mitigates over fitting. Our results showed that the considered machine learning classification algorithms by random forest can effectively predict the stunting status in East Aceh administrative zones. Persistent stunting status was found in the east part of Aceh. The identification of high-risk zones can provide more useful information and data to decision-makers for trying to reduce child undernutrition.

Co-Authors Amren S, Hairul Efrianses F. H. Sinaga Elida Pane Eva Darnila Gea, Asaziduhu Hiras Sinaga Indra Kelana Jaya Iwan Pahendra Jamaluddin Jimmy F. Naibaho Kartika Dewi Khalid Mawardi Liber Tommy Hutabarat Maryana Maryana Nancy Lusiana Damanik Pujiastuti, Maria R. Hamdani Harahap Ronaldo Glenn Sinabariba Saragih Azhari Nisa Simbolon, Anita Ira Agustina Siska Narulita Siboro Surianto Sitepu Sylvia, Tiara Tarigan, Kerista Teguh Rahayu TONNI LIMBONG Yohanna, Margaretha

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