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All Journal ComEngApp : Computer Engineering and Applications Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Teknologi Bahan dan Barang Teknik Jurnal Teknik Informatika C.I.T. Medicom Pelita Masyarakat Madaniya Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Community Empowerment Jurnal Sisfotek Global Jurnal Ilmiah Teknik Informatika & Elektro (JITEK)
Muhathir, Muhathir
Universitas Medan Area
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Physics Public Health Social Sciences

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KLASIFIKASI EKSPRESI WAJAH MENGGUNAKAN BAG OF VISUAL WORDS Muhathir .
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 2, No 2 (2018): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v2i2.181

Abstract

Pada hakikatnya, manusia dapat membedakan pola terhadap suatu objek berdasarkan bentuk visual yang mengandung keadaan emosional. Seperti membedakan ekspresi wajah seseorang pada suatu citra. Manusia dapat membedakan ekspresi pada citra tersebut secara kasat mata. Namun komputer yang tidak dapat mengenali ekspresi wajah tersebut. Bag of visual words merupakan suatu skema untuk mengklasifikasikan citra berdasarkan nilai-nilai pixel pada citra. Dengan menggunakan deteksi interest point dan ekstraksi interest point, bag of visual words mengambil ciri unik pada citra sehingga dapat membedakan pola-pola yang terdapat pada suatu citra. Bag of visual word dengan nilai K 500 mampu mengklasifikasi pola ekspresi wajah dengan tingkat akurasi 69%,Kata kunci: Wajah, Klasifikasi, Speed-up Robust Feature, Bag of visual words, Ekspresi
Pembuatan Aplikasi Sistem Informasi Manajemen Sekolah Untuk Layanan Penerimaan Peserta Didik Baru Zulfikar Sembiring; Susilawati Susilawati; Muhathir Muhathir
Pelita Masyarakat Vol 2, No 1 (2020): Pelita Masyarakat, September
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/pelitamasyarakat.v2i1.4193

Abstract

One of the education problems in this country is the zoning policy in the new student admission system (PPDB). This is in accordance with the policy of the Ministry of Education and Culture (Kemendikbud) in 2016 which began with the use of zoning for the administration of national exams. Then in 2017 the zoning system was implemented for the first time in implementing PPDB, and was refined in 2018 through Permendikbud Number 14 of 2018. The first problem faced is the zoning system organized by State Junior High Schools in Medan and the Education Office which still causes unrest for the community, especially parents, where the implementation has not been carried out in a transparent manner, both the number of prospective students who have registered at the school and the scoring system based on distance, the achievement of prospective students and the transfer of parents' duties. The second problem is the system for announcing the acceptance of prospective students who have passed a certain school is not generally published. The solution offered to deal with problems that occur to partners is by transferring science and technology in the form of management information system-based applications and services to partners in the form of a new student admission information system (PPDB), training related to the use of the PPDB system, and assistance to partners. . The result of this community service program is to increase insight and knowledge of skills for partners in optimizing the use of information systems and information technology to support PPDB operational activities, improving partners' skills and abilities in using school service management applications designed to facilitate the school PPDB process and implementation of PPDB. which is organized by schools and education offices to become more transparent to the public.
Penataan Lingkungan Dusun Batik Sebagai Kawasan Wisata Industri Rumah Tangga Pada Desa Pematang Johar Kecamatan Labuhan Deli Yunita Syafitri Rambe; Neneng Yulia Barky; Muhathir Muhathir
Madaniya Vol. 3 No. 1 (2022)
Publisher : Pusat Studi Bahasa dan Publikasi Ilmiah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53696/27214834.148

Abstract

Salah satu mata pencaharian masyarakat Desa Pematang Johar adalah batik. Kurangnya sarana dan prasarana yang baik, menjadi satu kendala dalam mengembangkannya. Sementara batik sendiri, merupakan sasaran Desa Pematang Johar dalam memperkenalkan ke masyarakat luas yang merupakan salah satu program kerja desa. Perwujudan program ini diperlukan dengan bantuan tenaga arsitek dalam merancang kawasan. Para pengabdi mencoba melihat permasalahan dan potensi dusun. Diperlukan suatu perencanaan desa untuk mengembangkan kawasan. Perencanaan yang dilakukan dengan tujuan mewujudkan desa tersebut menjadi sebuah desa kawasan batik dengan mengangkat para ibu rumah tangga sebagai pelaku utama. Perencanaan ini juga dilakukan untuk menjadikan dusun ini sebagai generator untuk dusun sekitarnya, dan juga untuk memberikan kegiatan-kegiatan untuk menambah mata pencaharian masyarakat. Metode yang dilakukan dalam pengabdian adalah melakukan perencanaan terhadap dusun batik dengan tahapan melakukan observasi, melakukan pendataan, melakukan survey dan pengukuran dan melakukan desain yang bercirikan batik sebagai potensi utama kawasan dengan konsep urban rural regeneration. Konsep ini dengan melihat pengembangan dengan melibatkan partisipasi masyarakat sebagai upaya mewujudkan desa berkelanjutan. Luaran yang diinginkan adalah sebuah perencanaan kawasan batik yang dituangkan dalam masterplan. Diinginkan dengan adanya masterplan ini, menjadi dasar bagi desa untuk melaksanakan dan mewujudkan kawasan tersebut sebagai area wisata bagi masyarakat luas dalam memperkenalkan batik sawah.
Analysis of the Naïve Bayes Method in Classifying Formalized Fish Images Using GLCM Feature Extraction Ayu Pariyandani; Eka Pirdia Wanti; Muhathir Muhathir
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 1, No 2 (2020)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (655.435 KB) | DOI: 10.30596/jcositte.v1i2.5171

Abstract

Fish is one of the foods that are high in protein so that many Indonesians consume fish as protein intake for health. Fish can be found in any waters including Indonesian marine waters, so that some of the Indonesian people work as fishermen. This causes the number of fish catches to increase and the fishermen have to sell the fish quickly in at least one day because the fish will rot easily if not consumed immediately. This has led some traders to cheat by mixing formaldehyde with fish that are not sold out. This action is very detrimental to consumers, so they must be more vigilant in choosing or buying fish on the market. One way for consumers to recognize formaldehyde fish is a technology that can distinguish fresh fish or formalin fish based on the image of the fish, Naive Bayes and GLCM (Gray Level Co-Occurrence Matrix) by using this method the accuracy of this system can reach up to 70%.
Numerical Analysis of Variations Distance Formulas on K Nearest Neighbors In Classifying Malaria Parasite Blood Cells Taufik Ismail Simanjuntak; Juliansyah Putra Tanjung; Mahardika abdi prawira tanjung; Cut Try Utari; Muhathir Muhathir
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.5464

Abstract

Malaria is one of the numerous acute and chronic diseases. Even malaria can pose a threat to a person's safety. The original cause of malaria was an infection with a protozoan of the genus Plasmodium, which was transmitted by the bite of a mosquito. This Anopheles mosquito parasite infects red blood cells throughout the body, resulting in an enlarged spleen. This research aims to make it easier for physicians to classify blood images as malaria-infected or not. If the input is a blood image, then SURF Feature Extraction will be used to extract the blood image. We therefore obtained weight results based on the extraction results. The weighted results generated by the SURF extraction process will be classified using the KNN Algorithm to determine whether or not an individual is infected with malaria. This study's tests compared various distance formulas utilized by the KNN classification method. Comparing the results of malaria blood image classification using the KNN classification method with variations in the distance formula, it is evident in table 7 that correlation is the optimal distance formula for malaria parasite blood cells recognition, followed by cosine. According to the results of KNN's tests, it is not optimal at classifying blood images containing malaria, but these results are categorized as good
Bina Komunikasi Wisata Desa Percut Kecamatan Percut Sei Tuan Kabupaten Deli Serdang Effiati Juliana Hasibuan; Indra Muda; Muhathir Muhathir
Pelita Masyarakat Vol. 4 No. 1 (2022): Pelita Masyarakat, September
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/pelitamasyarakat.v4i1.7246

Abstract

Percut Village is a popular tourist destination in Percut Sei Tuan District, drawing visitors from all over the country, particularly on Saturdays and Sundays. There is a culinary tour in this town that serves several varieties of fish meals that guests can choose according to their preferences. Visitors can enjoy the relaxing sea views until they approach the Malaysian border on their way to the gastronomic destination. Visitors will be transported to the gastronomic destination via free fishing boats provided by the café owner. There is also a Fish Auction Place (TPI) in this village, which attracts inhabitants who want to buy fresh fish at a low price compared to other localities. The other issue is that local folks' ability to communicate in order to entice tourists to return is still restricted. Residents' willingness to take advantage of the possibility to make things for sale is still low. Based on the dedication shown, the communication training provided to partners has proven to be very effective in promoting the various types of tourism available in Percut village, as well as the socializing provided to keep the environment clean. However, the Covid 19 epidemic, which is still rampant, has severely harmed partners' culinary businesses and fish auctions.Percut Village has tourism potential, particularly in the fields of marine tourism, beach tourism, and culinary tourism; socialization about tourism communication is very useful for opening culinary tourism visits in Percut Village; residents' understanding of environmental maintenance procedures and healthy homes is still low; and The development of Covid 19 and the imposition of Community Activity Restrictions (PPKM) had a significant impact on Percut Village's tourism appeal.
Performance Evaluation Of Variations Boosting Algorithms For Classifying Formalin Fish From Photos Fadlisyah Fadlisyah; Muhathir Muhathir
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 6 No. 2 (2023): Issues January 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i2.6614

Abstract

Fish is one of the foods that are often consumed by humans to complete the protein in the body. Indonesia is rich in animal protein so some rogue traders to avoid losses due to rotten fish, sellers process fish to make it look fresh by fishing with formalin liquids so that buyers think the fish is still fresh, this problem is often found in the market so that it takes the right solution. The solution offered is to apply Machine Learning (Boosting Algorithm) to classify fresh fish and fish that have been planned with formalin by utilizing the extraction of GLCM features. The findings of this study indicate a variation of boosting algorithms can provide solutions to this problem. Accuracy, precision, recall, f1-score, f2-score, and Jaccard score in tilapia fish with a value of 0.95, 0.95, 0.95, 0.95, 0.95, 0.95 this result is obtained by extreme gradient boosting variations with the highest achievements compared to variations Other things are also similar to Tamban fish with a value of 0.78, 0.775, 0.78, 0.825, 0.77, 0.632. The effect of boosting algorithm on the measurement of model performance looks very increased in tilapia fish while in tamban fish do not provide maximum results, but these findings are better
Performance Comparison of Boosting Algorithms in Spices Classification Using Histogram of Oriented Gradient Feature Extraction Muhathir Muhathir; Reydo Trisno Pangestu; Ira Safira; Melisah Melisah
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v4i1.13710

Abstract

Spice classification is an important task in the food industry to ensure food safety and quality. This study focuses on the classification of spices using the HoG feature extraction method and boosting algorithms. The objective of this research is to compare the performance of four different models of boosting algorithms, namely Adaboost Classifier, Gradient Boosting Classifier, XGB Classifier, and Light GBM Classifier, in classifying spices. The evaluation metrics used in this research are Precision, Recall, F1-Score, F2-Score, Jaccard Score, and Accuracy. The results show that the XGB Classifier model achieved the best performance, with a precision of 0.811, recall of 0.809, and F1-score of 0.809, while the Adaboost Classifier model had the lowest performance, with a precision of 0.709, recall of 0.689, and F1-score of 0.682. Overall, the results indicate a fairly good success rate in classifying spices using the HoG feature extraction method and boosting algorithms. However, further evaluation is needed to improve the accuracy of the classification results, such as increasing the number of training data or considering the use of other feature extraction methods
Compares the effectiveness of the bagging method in classifying spices using the histogram of oriented gradient feature extraction technique Muhathir Muhathir
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 1 (2023): 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.Vol15.2023.386.pp48-57

Abstract

Spice classification is a crucial task in the food industry to ensure food safety and quality. This study focuses on the classification of spices using the Histogram of Oriented Gradient (HoG) feature extraction method and bagging method. The objective of this research is to compare the performance of three different models of bagging method, including Bootstrap Aggregating (Bagging), Random Forests, and Extra Tree Classifier, in classifying spices. The evaluation metrics used in this research are Precision, Recall, F1-Score, F2-Score, Jaccard Score, and Accuracy. The results show that the Random Forest model achieved the best performance, with precision, recall, F1-score, F2-Score, Jaccard, and Accuracy values of 0.861, 0.8633, 0.8587, 0.8607, 0.7694, and 0.8733 respectively. On the other hand, the Extra Tree Classifier had the lowest performance with precision, recall, F1-score, F2-Score, Jaccard, and Accuracy values of 0.7034, 0.7958, 0.7037, 0.7047, 0.5635, and 0.72 respectively. Overall, the results indicate a fairly good success rate in classifying spices using the HoG feature extraction method and bagging method. However, further evaluation is needed to improve the accuracy of the classification results, such as increasing the number of training data or considering the use of other feature extraction methods. The findings of this research may have significant implications for the food industry in ensuring the quality and safety of food products.
Recognition Of Chicken Species Through Sound Using Weierstrass Transform Cut Lika Mestika Sandy; Reyhan Achmad Rizal; Muhathir Muhathir
JURNAL SISFOTEK GLOBAL Vol 13, No 1 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i1.3442

Abstract

Voice recognition is an applied technique in the field of digital signal processing that has been widely used, such as technology in the field of telecommunications which is now able to provide data transmission services not only text but can also serve data transmission using voice. Speech recognition studies to date have only focused on human speech recognition, so it is important to develop research on speech recognition in animals. In this research a speech recognition system will be developed for balenggek, pelung and bekisar ornamental chickens using the Delphi 7 programming language and the weiertrass transform method. The performance evaluation measurement of the speech recognition system in this study uses two parameters, namely the detection rate and the false positive rate. The results showed that the speech recognition system for ornamental chickens using the weierstrass transform method had an average detection rate of 83.00% and an average false positive rate of 16%.
Co-Authors Al Khowarizmi Amri Ismail Tumanggor Arief Goeritno Aripin Rambe Asmaul Husna Ayu Pariyandani Azmi, Fadhillah Cahyo Hasanudin Cut Lika Mestika Sandy Cut Try Utari Deti Indah Kiranti Diah Ayu Larasati Dian Ifantiska Effiati Juliana Hasibuan Eka Pirdia Wanti Ellis Susmawati FADHILLAH AZMI Fadlisyah Fadlisyah Fadlisyah Fadlisyah FAUZI . Hashina Qiamu Mumtaziah Hayani Wulandari Indra Muda Insidini Fawwaz Ira Safira Ira Safira Juliansyah Putra Tanjung Karynda Natalie Theofilus Leonardi Paris Hasugian M Hamdani Santoso Mahardika Abdi Prawira Tanjung Mahmudah Salwa Gianti Melisah Melisah Merri Hafni Muchammad Takdir Sholehati Muhammad Hamdani Santoso N P Dharshinni Nadzifah Nadzifah Neneng Yulia Barky Nurul Khairina Rambe, Yunita Syafitri Reydo Trisno Pangestu Reyhan Achmad Rizal Rifa Alia Syahidah Rizki Muliono Sri Juwita Subairi Subairi Susilawati Susilawati Susilawati, Susilawati Syahputra, Dinur Syifaul Fuada Taufik Ismail Simanjuntak Theofil Tri Saputra Sibarani Wahyu Hidayah Yuhefizar Yuhefizar Zulfikar Sembiring