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Uncertainty Ontology for Module Rules Formation Waterwheel Control Azmi, Zulfian -; Nasution, Mahyuddin K. M.; Mawengkang, Herman; Zarlis, M
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14188

Implementation of Uncertainty model has not given maximum result in forming rule on an inference of a case. For testing to determine whether water quality is high, medium and low. The input variables used are temperature, pH, salinity and Disolved Oxygen. Testing is done by looking at the water turbidity change in the shrimp pond, to determine the water quality. Its water quality determines in the control module of the waterwheel rotation.Rolling the waterwheel moves quickly if pond water quality is low, moving slowly if water quality is medium and immobile if water quality is good. And the establishment of the rule with the approach of knowledge of Ontology to determine the relation between several variables (temperature, Ph, Disolved Oxygen and salinity). Each variable is set to its certainty value in the form of fuzzy value. Next is determined the relation of the four variables for the formation of rule.

Optimasi Kontrol Motor Induksi Menggunakan Metode Fuzzy Dan Algoritma Genetika Aulia, Rahman; Zarlis, Muhammad; Nasution, Mahyuddin K. M.
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 1 No 2 (2017): SinkrOn Volume 1 Nomor 2 April 2017
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (382.642 KB)

Kinerja conveyor dalam proses produksi suatu industri sangat berpengaruh dalam mengoptimalkan hasil produksi. Penggunaan conveyor tidak terlepas dengan motor penggerak conveyor, sehingga kondisi prima motor juga harus diperhatikan agar proses produksi tidak terhenti yang mengakibatkan kerugian yang relatif besar bagi industri yang memiliki tingkat produksi tinggi. Untuk mengetahui dan menentukan kondisi dari motor â€“ motor yang akandibebani dalam kondisi baik maka digunakan logika fuzzy. Logika fuzzy harus dioptimalkan penggunaanya dengan Algoritma genetika dalam menentukan nomor motor berapa saja yang harus hidup sehingga sesuai dengan beban yang dipikul. Menetukan dan mengetahui kondisi motor dan menentukan nomor motor yang harus beroperasi bertujuan untuk mengoptimalkan berjalannya suatu sistem conveyor. Hasil yang didapat pada penelitian ini yaitu Optimasi yang paling baik dari tiga kali pengujian adalah terjadi pada pengujian ke dua dengan jumlah motor sebanyak 60 buah memakai tegangan 110 V dengan memikul beban 300 kg mendapatkan hasil 11,7 % dengan nomor motor yang hidup adalah 12, 19, 20, 21, 26, 32. dan 40.

Uncertainty Ontology for Module Rules Formation Waterwheel Control Azmi, Zulfian -; Nasution, Mahyuddin K. M.; Mawengkang, Herman; Zarlis, M
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14188

Implementation of Uncertainty model has not given maximum result in forming rule on an inference of a case. For testing to determine whether water quality is high, medium and low. The input variables used are temperature, pH, salinity and Disolved Oxygen. Testing is done by looking at the water turbidity change in the shrimp pond, to determine the water quality. Its water quality determines in the control module of the waterwheel rotation.Rolling the waterwheel moves quickly if pond water quality is low, moving slowly if water quality is medium and immobile if water quality is good. And the establishment of the rule with the approach of knowledge of Ontology to determine the relation between several variables (temperature, Ph, Disolved Oxygen and salinity). Each variable is set to its certainty value in the form of fuzzy value. Next is determined the relation of the four variables for the formation of rule.

Sensitivity of MAPE using detection rate for big data forecasting crude palm oil on k-nearest neighbor Al Khowarizmi; Rahmad Syah; Mahyuddin K. M. Nasution; Marischa Elveny
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2696-2703

Forecasting involves all areas in predicting future events. Many problems can be solved by using a forecasting approach to become a study in the field of data science. Forecasting that learns through data in the light age is able to solve problems with large-scale data or big data. With the big data, the performance of the k-Nearest Neighbor (k-NN) method can be tested with several accuracy measurements. Generally, accuracy measurement uses MAPE so it is necessary to conduct sensitivity on MAPE by combining it with the detection rate which is the difference technique. In addition, the k-NN process has been developed for the sake of running sensitivity by performing normalized distance using normalized Euclidean distance so that in this paper using the crude palm oil (CPO) price dataset, it is able to forecast and become a future model and apply it to Business Intelligence and analysis. In the final stage of this paper, the accuracy value in doing big data forecasting on CPO prices with MAPE is 0.013526% and MAPE sensitivity combined with a detection rate of 0.000361% so that future processes using different methods need to involve detection rates.

FILSAFAT LOGIKA DAN ONTOLOGI ILMU KOMPUTER Verdi Yasin; Muhammad Zarlis; Mahyuddin K.M. Nasution
Journal of Information System, Applied, Management, Accounting and Research Vol 2 No 2 (2018): JISAMAR : Volume 2, Nomor 2, June 2018
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (587.756 KB)

Logika adalah metode atau teknik yang diciptakan untuk meneliti ketepatan penalaran serta mengkaji prinsipprinsip penalaran yang benar dan penarikan kesimpulan yang absah. Ilmu logika berhubungan dengan kalimatkalimat (argumen) dan hubungan yang ada diantara kalimat-kalimat tersebut. Tujuannya adalah memberikan aturan-aturan sehingga orang dapat menentukan apakah suatu kalimat bernilai benar. Kalimat yang dipelajari dalam logika bersifat umum, baik bahasa sehari-hari maupun bukti matematika yang didasarkan atas hipotesahipotesa. Oleh karena itu aturan-aturan yang berlaku di dalamnya haruslah bersifat umum dan tidak tergantung pada kalimat atau disiplin ilmu tertentu. Ilmu logika lebih mengarah dalam bentuk sintaks-sintaks daripada arti dari kalimat itu sendiri. Secara umum logika dibedakan menjadi dua yaitu Logika Pasti dan Logika Tidak Pasti. Logika pasti meliputi Logika Pernyataan (Propotitional Logic), Logika Predikat (Predicate Logic), Logika Hubungan (Relation Logic) dan Logika Himpunan. Sedangkan logika tidak pasti meliputi Logika Samar atau kabur (Fuzzy Logic). Logika Pernyataan membicarakan tentang pernyataan tunggal dan kata hubungnya sehingga didapat kalimat majemuk yang berupa kalimat deklaratif. Logika Predikat menelaah variabel dalam suatu kalimat, kuantifikasi dan validitas sebuah argumen. Logika Hubungan mempelajari hubungan antara pernyataan, relasi simetri, refleksif, antisimtris, dll. Logika himpunan membicarakan tentang unsur-unsur himpunan dan hukum-hukum yang berlaku di dalamnya.

Relationship Of Parity, Education And Sources Of Information With The Level Of Knowledge Of The Mother About The Provision Of Immunization Basis In Desa Barbaran Jae Kec. Panyabungan Barat Tahun 2019 Helmi Wardah Nasution
Jurnal EduHealth Vol. 10 No. 01 (2019): September, Jurnal EduHealth
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (528.609 KB)

Currently, almost one million children each year do not receive an immunization program. 2007 data shows that only 6 out of 10 children in Indonesia receive a complete immunization program. In fact, 9 out of 100 children do not get vaccinated at all. The percentage of children who received complete vaccination for DPT was only 66.7%. The immunization percentage for hepatitis B was 60.3%; for tuberculosis 85.4%, for Polio 73.5%, and for measles 76.4%. This type of research used an analytic study with a cross sectional design, which aims to explain the relationship between parity, education and sources of information with the level of mother's knowledge about the completeness of basic immunization. Data analysis was done by chi square test. The population in this study were all mothers who had babies aged 0-12 months in Barbaran jae village, kec. West Panyabungan as many as 31 people. The sample in this study was the entire population, namely mothers who have babies aged 0-12 months in Barbaran Jae Village, Kec. Panyabungan Barat as many as 31 people. The highest frequency distribution was found in sufficient knowledge, namely 17 respondents (54.8%), multipara parity, namely 19 respondents (61.3%), academic education/PT, namely 13 respondents (41.9%), and sources of information print media that is 17 respondents (54.8%). There was a correlation between parity (P = 0.045), education (P = 0.001), and sources of information (P = 0.026), with the mother's level of knowledge about the completeness of basic immunization in Barbaran Jae Village, Kec. West Connection.

Mathematical Philosophy Mahyuddin K.M. Nasution
Journal of Research in Mathematics Trends and Technology Vol. 2 No. 2 (2020): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v2i2.4678

Mathematics and philosophy are two words with different meanings and the same thing. With various historical evidence, mathematics as the basis of science is not part of or born from philosophy. In the same position in knowledge, mathematics confirm the answers to intimate problem in philosophy. Often there is confusion in philosophy because of conflicting concepts with one another. Mathematics without philosophy does not move swiftly, because without the meanings that are sometimes driven by philosophy. Logically, truth is not well developed in evidence except when mathematics and philosophy get long. It is to provide an understanding of the need for a foundation of truth thought, which generally reveals in the comprehension of mathematics, namely in meta-mathematics and philosophy.

The feature extraction for classifying words on social media with the Naïve Bayes algorithm Arif Ridho Lubis; Mahyuddin Khairuddin Matyuso Nasution; Opim Salim Sitompul; Elviawaty Muisa Zamzami
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp1041-1048

To classify Naïve Bayes classification (NBC), however, it is necessary to have a previous pre-processing and feature extraction. Generally, pre-processing eliminates unnecessary words while feature extraction processes these words. This paper focuses on feature extraction in which calculations and searches are used by applying word2vec while in frequency using term frequency-Inverse document frequency (TF-IDF). The process of classifying words on Twitter with 1734 tweets which are defined as a document to weight the calculation of frequency with TF-IDF with words that often come out in tweet, the value of TF-IDF decreases and vice versa. Following the achievement of the weight value of the word in the tweet, the classification is carried out using Naïve Bayes with 1734 test data, yielding an accuracy of 88.8% in the Slack word category tweet and while in the tweet category of verb 78.79%. It can be concluded that the data in the form of words available on twitter can be classified and those that refer to slack words and verbs with a fairly good level of accuracy. so that it manifests from the habit of twitter social media user.

Enhancing Performance of Parallel Self-Organizing Map on Large Dataset with Dynamic Parallel and Hyper-Q Alexander F.K. Sibero; Opim Salim Sitompul; Mahyuddin K.M. Nasution
Data Science: Journal of Computing and Applied Informatics Vol. 2 No. 2 (2018): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Self-Organizing Map (SOM) is an unsupervised artificial neural network algorithm. Even though this algorithm is known to be an appealing clustering method,many efforts to improve its performance are still pursued in various research works. In order to gain faster computation time, for instance, running SOM in parallel had been focused in many previous research works. Utilization of the Graphics Processing Unit (GPU) as a parallel calculation engine is also continuously improved. However, total computation time in parallel SOM is still not optimal on processing large dataset. In this research, we propose a combination of Dynamic Parallel and Hyper-Q to further improve the performance of parallel SOM in terms of faster computing time. Dynamic Parallel and Hyper-Q are utilized on the process of calculating distance and searching best-matching unit (BMU), while updating weight and its neighbors are performed using Hyper-Q only. Result of this study indicates an increase in SOM parallel performance up to two times faster compared to those without using Dynamic Parallel and Hyper-Q.

The effect of the TF-IDF algorithm in times series in forecasting word on social media Arif Ridho Lubis; Mahyuddin K. M. Nasution; Opim Salim Sitompul; Elviawaty Muisa Zamzami
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp976-984

Forecasting is one of the main topics in data mining or machine learning in which forecasting, a group of data used, has a label class or target. Thus, many algorithms for solving forecasting problems are categorized as supervised learning with the aim of conducting training. In this case, the things that were supervised were the label or target data playing a role as a 'supervisor' who supervise the training process in achieving a certain level of accuracy or precision. Time series is a method that is generally used to forecast based on time and can forecast words in social media. In this study had conducted the word forecasting on twitter with 1734 tweets which were interpreted as weighted documents using the TF-IDF algorithm with a frequency that often comes out in tweets so the TF-IDF value is getting smaller and vice versa. After getting the word weight value of the tweets, a time series forecast was performed with the test data of 1734 tweets that the results referred to 1203 categories of Slack words and 531 verb tweets as training data resulting in good accuracy. The division of word forecasting was classified into two groups i.e. inactive users and active users. The results obtained were processed with a MAPE calculation process of 50% for inactive users and 0.1980198% for active users.

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