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All Journal ComEngApp : Computer Engineering and Applications Journal Scientific Journal of Informatics InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Teknoinfo Jusikom: Jurnal Sistem Informasi Ilmu Komputer JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknologi Bahan dan Barang Teknik JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Jurnal Teknik Informatika C.I.T. Medicom Pelita Masyarakat Madaniya Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Community Empowerment INCODING: Journal of Informatics and Computer Science Engineering J-SAKTI (Jurnal Sains Komputer dan Informatika) Mejuajua Jurnal Sisfotek Global Journal of Renewable Energy, Electrical, and Computer Engineering TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Ilmiah Teknik Informatika & Elektro (JITEK) Jurnal Ilmu Komputer dan Teknologi Informasi Al'Adzkiya International of Computer Science and Information Technology Journal JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Muhathir, Muhathir
Universitas Medan Area
Religion Aerospace Engineering 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 Mechanical Engineering Physics Public Health Social Sciences Other

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PURWARUPA EMBEDDED DEVICE BERBASIS CHIP ATMEGA2560 DAN MODUL RFID UNTUK SISTEM PENGUNCIAN Arief Goeritno; Muhathir Muhathir; Yuhefizar Yuhefizar; Muchammad Takdir Sholehati
Jurnal Teknologi Bahan dan Barang Teknik Vol 11, No 1 (2021)
Publisher : Balai Besar Bahan dan Barang Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37209/jtbbt.v11i1.265

Abstract

Keberadaan sistem minimum berbasis mikrokontroler dapat digunakan untuk sistem penguncian bertingkat melalui pabrikasi dan perakitan untuk keterwujudan sebuah purwarupa perangkat tertanam berbasis chip mikrokontroler AVR ATmega2560 dan modul Radio Frequency Identification (RFID). Penetapan sasaran penelitian dilakukan setelah tahapan perancangan dan pembuatan perangkat tertanam, yaitu membuat motherboard mini dan mengintegrasikan sejumlah perangkat elektronika dan memrogram sistem mikrokontroler. Sasaran penelitian, yaitu melaksanakan uji verifikasi berupa simulasi dan melakukan uji validasi berupa pengukuran kinerja terhadap purwarupa perangkat tertanam. Metode penelitian dilaksanakan dengan pentahapan, yaitu simulasi dilaksanakan dengan bantuan aplikasi Proteus dan pengukuran kinerja dilaksanakan dengan tahapan sesuai urutan pada simulasi. Hasil penelitian berupa simulasi dalam bentuk pemberian 4 (empat) kondisi buatan dan pengukuran kinerja dilakukan juga dalam bentuk pemberian 4 (empat), tetapi dengan kondisi sesungguhnya.  Kesimpulan utama penelitian ini berkaitan dengan saat uji verifikasi dan validasi. Pemaksimalan terhadap uji verifikasi wajib ditindaklanjuti dengan uji validasi. Pertama, ketika kartu tidak terdeteksi modul RFID, ketika kartu terdeteksi modul RFID, ketika sistem penguncian dibuka secara paksa dan buzzer “ON”. Kedua, ketika kartu tidak terdeteksi saat di tag pada antena dan ketika sistem penguncian dibuka secara paksa dan buzzer “ON”, dan kartu terdeteksi saat di tag pada antena.
Hyperparameter Model Architecture Xception in Classifying Zophobas Morio and Tenebrio Molitor Amri Ismail Tumanggor; Muhathir Muhathir
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 4, No 2 (2023)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v4i2.15800

Abstract

Zophobas Morio and Tenebrio Molitor are popular larvae as feed ingredients that are widely used by animal lovers to feed reptiles, birds, and other poultry. However, these two larvae are similar in appearance; their nutritional content is very different. Zophobas Morio is more nutritious and has a higher economic value compared to Tenebrio Molitor. Due to limited knowledge, many animal lovers have difficulty distinguishing between the two. This study aims to build the best configuration of the Xception architecture hyperparameter model that can distinguish between the two. The model is trained using images taken from mobile phones. Training is carried out using the parameters Epoch 15, Batch Size 32, Optimizer Adam, RMSprop, and SGD. The experimental results on the dataset show that the best accuracy for the Xception architecture hyperparameter model is Optimizer Adam with an accuracy rate of 100%, and Optimizer SGD with an accuracy rate of 100%. And of course, it gives very good results
Performance Analysis of Naive Bayes Variation Method in Spice Image Classification Using Histogram of Gradient Oriented (HOG) Feature Extraction Taufik Ismail Simanjuntak; Muhathir Muhathir; Fadlisyah Fadlisyah; Ira Safira
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.7957

Abstract

Indonesia has a lot of natural wealth of spices. The diversity of spices is an inseparable aspect of Indonesian history. Spices and seasonings are biological resources that have long played an important role in human life. Indonesian spices have almost the same color and shape. The purpose of this study was to analyze the performance of the Naïve Bayes variation method in classifying spices using a Histogram Of Oriented Gradient (HOG) feature extraction. Based on 3 tests, the performance of the four Naïve Bayes variation methods carried out in this study, it can be seen that testing 5 types of spices using the Gaussian Naïve Bayes method obtained the best performance with an accuracy of 0.946, a precision of 0.95, a recall of 0.945, f1 score of 0.947, f beta score of 0.946, and Jaccard score of 0.90. Where as using the Complement Naïve Bayes method gets the lowest performance. From the results of this study it can be concluded that by utilizing HOG feature extraction and the Naïve Bayes variation method, maximum classification results are obtained in classifying spices. To obtain more accurate classification results, consider using other methods and other feature extraction
Implementasi Algoritma C4.5 Untuk Klasifikasi Penentuan Penerima Bantuan Langsung Tunai Di Desa Tanjung Rejo Sri Juwita; Muhathir Muhathir; Rizki Muliono
Jurnal Ilmiah Teknik Informatika & Elektro (JITEK) Vol 1, No 2 (2022): Jurnal Ilmiah Teknik Informatika & Elektro (JITEK)
Publisher : Jurnal Ilmiah Teknik Informatika & Elektro (JITEK)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jitek.v1i2.1474

Abstract

Direct Cash Assistance (BLT) provides money to the poor. This cash assis-tance program was made to help the underprivileged deal with the corona-virus (Covid 19) pandemic. The implementation of the C4.5 algorithm in determining the recipients of Direct Cash Assistance (BLT) was conducted by making classifications or rules according to the data of the old benefi-ciaries, then classifying based on the variables of the husband's and wife's work, home status, and the number of dependents. The results of these classifications or rules were used as a basis if there were future Direct Cash Assistance (BLT) recipients. Through the application of the C4.5 algorithm in determining the exact target of Direct Cash Assistance (BLT), beneficiar-ies could receive assistance quickly and then would be shown in a report that could be downloaded.
Improve children’s literacy with the reading aloud method Hashina Qiamu Mumtaziah; Syifaul Fuada; Leonardi Paris Hasugian; Ellis Susmawati; Nadzifah Nadzifah; Deti Indah Kiranti; Rifa Alia Syahidah; Karynda Natalie Theofilus; Cahyo Hasanudin; Subairi Subairi; Muhathir Muhathir; Hayani Wulandari; Mahmudah Salwa Gianti
Community Empowerment Vol 8 No 9 (2023)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ce.9119

Abstract

Children who lack motivation and interest in learning and reading often demonstrate apathy and are easily discouraged, leading to a lack of concentration on their educational pursuits. As a result, these students face challenges in their academic journey. Therefore, it is crucial to make concerted efforts to enhance children's literacy by implementing the reading aloud approach, which can positively influence their overall growth and development in the Rusunawa Ciseureuh Purwakarta community. The primary objective of this program is achieved through the utilization of the reading-aloud technique. The anticipated outcomes of this program encompass increased children's motivation and interest in literacy, which will be supported by supplementary elements such as incorporating enjoyable learning techniques, engaging in gardening activities, decorating pots, and providing incentives for participating children.
REAL TIME DETECTION OF CHICKEN EGG QUANTITY USING GLCM AND SVM CLASSIFICATION METHOD Cut Lika Mestika Sandy; Asmaul Husna; Reyhan Achmad Rizal; Muhathir Muhathir
Jurnal Techno Nusa Mandiri Vol 20 No 2 (2023): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v20i2.4735

Abstract

A common problem currently being faced in the chicken egg production home industry is difficulty in counting the number of eggs. Currently, calculating the number of eggs is still done manually, which is less than optimal and prone to errors, so many entrepreneurs often experience losses. The manual system currently used also has the potential for this to happen. The use of technology on an MSME scale among laying hen breeders has not been widely adopted, this is due to limited access and understanding of technology. One alternative solution to deal with this problem is to build a real-time computerized system. The system that will currently be built in this research uses GLCM feature extraction and the SVM classification method. This system will detect egg production via CCTV cameras and will be stored in a database to be displayed on the website. The advantage of this system is that egg entrepreneurs can monitor chicken egg yields in real time. The results of trials that have been carried out using GLCM feature extraction and the SVM classification method in calculating the number of eggs using the SVM method with a polynomial kernel are highly recommended for use in this research because it can achieve 95% accuracy.
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.
KLASIFIKASI DAUN TEH SIAP PANEN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK ARSITEKTUR MOBILENETV2 Marpaung, Febriady; Khairina, Nurul; Muliono, Rizki; Muhathir, Muhathir; Susilawati, Susilawati
Jurnal Teknoinfo Vol 18, No 1 (2024): Januari
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v18i1.3435

Abstract

Penentuan waktu panen daun teh adalah faktor penting dalam industri teh yang secara signifikan mempengaruhi kualitas dan nilai jual produk. Maka dari itu, para petani teh dan produsen perlu memahami waktu yang tepat untuk memetik daun teh untuk menghasilkan teh berkualitas tinggi. Klasifikasi daun teh siap panen dapat menjadi solusi efektif untuk membantu dalam menentukan waktu panen yang optimal. Dalam rangka mencapai tujuan ini, pendekatan digital menjadi semakin penting, di mana pengenalan otomatis daun teh dapat dilakukan dengan cepat dan akurat. Salah satu metode yang digunakan dalam penelitian ini adalah Convolutional Neural Network (CNN) dengan arsitektur MobileNetV2. Convolutional Neural Network (CNN), khusus dirancang untuk mengolah data dua dimensi seperti gambar. Keunggulan CNN terletak pada kemampuannya memahami dan mengklasifikasi aspek dan objek dalam citra. Salah satu arsitektur model Deep Learning menggunakan CNN yang populer adalah MobileNet. MobileNetV2, sebagai modifikasi MobileNet, memperkenalkan inverted residual blocks dan linear bottleneck. Perbedaan utama dengan MobileNetV1 terletak pada penggunaan bottleneck, yang memungkinkan model mengubah input dari tingkat rendah ke deskriptor tingkat tinggi. MobileNetV2 mampu ekstraksi fitur otomatis dan efisien melalui inverted residual blocks, dan linear bottleneck meningkatkan kapabilitas model dalam mengolah informasi. Dengan pendekatan ini, MobileNetV2 menggunakan CNN sebagai alat efektif untuk tugas-tugas klasifikasi citra, menawarkan kemampuan ekstraksi fitur otomatis dan pengolahan informasi yang efisien dalam pengembangan Deep Learning. CNN telah terbukti efektif dalam tugas klasifikasi gambar, dan MobileNetV2 dikenal karena ringan dan efisien dalam penggunaan sumber daya. Dengan menggunakan metode ini, penelitian ini bertujuan untuk mengklasifikasikan tingkat kematangan daun teh. Hasil training dari enam skenario model yang diuji menunjukkan bahwa tingkat akurasi tertinggi tercapai pada pengujian skenario model 2, yaitu sebesar 100%. Pada pengujian ini, hyperparameter yang optimal termasuk epoch sebanyak 50, input shape RGB Channel sebesar 224x224x3, batch size sejumlah 32, dan optimizer yang digunakan adalah Adam. Pentingnya akurasi terlihat dari hasil pengujian menggunakan data testing, di mana model berhasil mencapai akurasi sebesar 100%. Selain itu, nilai presisi, recall, dan f1-score juga mencapai 100%. Hal ini menunjukkan bahwa model yang dikembangkan mampu mengenali dan mengklasifikasikan daun teh siap panen dengan sangat baik
ANALISIS PERBANDINGAN MENGGUNKAN METODE TOPSIS DAN WASPAS DALAM PENENTUAN KARYAWAN TELADAN Sri Wahyuni; Rizki Muliono; Nurul Khairina; Muhathir
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 7 No. 1 (2023): JATI Vol. 7 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v7i1.6295

Abstract

CV. Multisindo Karya selaku industri konsultan teknologi data pada cara penentuan karyawan teladan saat ini masih menggunakan cara pemantauan langsung. Namun, proses ini dinilai belum efektif dan belum bisa mengakomodir terhadap hal-hal lain yang harusnya mendukung penilaian karyawan sehingga memungkinkan terjadinya kesalahan dalam penilaian dan memperlambat proses penentuan karyawan teladan acuan sedang memakai cara kalkulasi sebagai buku petunjuk, cara ini pastinya menghabiskan durasi cukup lama. Proses penilaian dengan menggunakan beberapa kriteria yang digunakan yaitu , kriteria dalam penilaian karyawan seperti disiplin kerja, tanggung jawab, komunikasi dan kerjasama, pemahaman dan penguasaan pekerjaan, dan inisiatif. Dengan memakai metode Technique for order Performance by Similarity to Ideal Solution, serta metode Weighted Aggregated Sum Product Assesment penulis merancang suatu aplikasi yang dapat melaksanakan cara penentuan karyawan teladan dengan hasil yang dapat dibanding antara kedua tata cara. Bersumber pada hasil kalkulasi dari tata cara TOPSIS memberikan hasil Ira Astriani Saragih dengan angka TOPSIS 0, 748, Serta menggunakan tata cara WASPAS memberikan hasil Ira Astriani Saragih dengan angka WASPAS 0,960. Dan tingkat akurasi yang didapat metode TOPSIS ialah 49,67% dan WASPAS ialah 50,33%.
Perancangan Sistem Informasi Pendataan Swab Pegawai Pada PT. Perkebunan Nusantara III Nasution, Annisa; Muhathir, Muhathir
Jurnal Ilmiah Teknik Informatika & Elektro (JITEK) Vol 3, No 2 (2024): Jurnal Ilmiah Teknik Informatika & Elektro (JITEK)
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jitek.v3i2.1897

Abstract

PT. Perkebunan Nusantara III is an Indonesian state-owned enterprise engaged in the plantation sector. However, since the Covid-19 pandemic, the company has required all PTPN employees to carry out swabs to prevent transmission of Covid-19. Prior to conducting employee swabs, there is data collection first. Currently, swab data collection at PTPN III still uses the manual method, namely using paper as a document. Therefore the purpose of this research is to design an Information System for Employee Swab Data Collection at PT. Perkebunan Nusantara III to replace the use of paper in processing employee swab data. By designing a swab data collection information system, it is hoped that it can reduce the use of paper and make it easier to collect employee swab data at PTPN III.
Co-Authors Al Khowarizmi Albar, Rizka Amri Ismail Tumanggor Andre Hasudungan Lubis Arief Goeritno Aripin Rambe Ayu Pariyandani Azmi, Fadhillah Cahyo Hasanudin Cut Lika Mestika Sandy Cut Try Utari Deti Indah Kiranti Diah Ayu Larasati Dian Ifantiska Dina Maizana Dinur Syahputra Dwipayana, Mahendar Effiati Juliana Hasibuan Eka Pirdia Wanti Ellis Susmawati Esrayanti Simanjuntak Essay Puspita Sitopu FADHILLAH AZMI Fadli, MHD. Fajar Alry Fadlisyah Fadlisyah Fadlisyah Fadlisyah Fadlisyah Fauzi FAUZI . Fitra , Akbario Gultom, William Habib Satria Hashina Qiamu Mumtaziah Hayani Wulandari Idrus, Syed Zulkarnain Syed Indra Muda Insidini Fawwaz Ira Safira Ira Safira Juliansyah Putra Tanjung Karynda Natalie Theofilus Leonardi Paris Hasugian M. Hamdani Santoso Maghfirah Maghfirah Mahardika Abdi Prawira Tanjung Mahmudah Salwa Gianti Marpaung, Febriady Melisah Melisah Merri Hafni Moulando Tampubolon Muchammad Takdir Sholehati Muhammad Fadlan Siregar Muhammad Fauzy Mungkin, Moranaim N P Dharshinni Nadzifah Nadzifah Napisah, Napisah Nasution, Annisa Neneng Yulia Barky Noor, Fredy Nugraha Rahmadan Diyanto Nurul Khairina Pariyandani, Ayu Purba, Sentia Ovania Rambe, Yunita Syafitri Reydo Trisno Pangestu Reyhan Achmad Rizal Rifa Alia Syahidah Rizki Muliono Saufa Yardha Moerni Sibarani, Theofil Tri Saputra Simangunsong, Roy Candra Simanjuntak, Juan Siregar, Erlina Sri Juwita Sri Wahyuni Subairi Subairi Susilawati Susilawati Syahputra, Dinur Syahputra, Dinur Syifaul Fuada Syuhada, Rahmad Taufik Ismail Simanjuntak Taufik Ismail Simanjuntak Theofil Tri Saputra Sibarani Tika Ermita Wulandari Wahyu Hidayah Wanti, Eka Pirdia Wibawa, M. Bayu Yahya, Yanawati Binti Yanawati Yahya Yopan Rahmad Aldori Yuhefizar Yuhefizar Zebua, Meniati Zuhar Musliyana, Zuhar Zulfikar Sembiring Zulfikar Sembirirng