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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Computer Networks, Architecture and High Performance Computing Djtechno: Jurnal Teknologi Informasi Jurnal Sains Teknologi dan Sistem Informasi Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Digital Transformation Technology (Digitech) CSRID
Abdul Muis
Universitas Satya Terra Bhinneka
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Library & Information Science

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Implementation of the ORESTE Method in Determining the Selection of Service Ambassador Events Akbar Idaman; Hamjah Arahman; Abdul Muis; Tar Muhammad Raja Gunung; Handry Eldo
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3225

Abstract

The selection of candidates to become Service Ambassadors is an important and complex process. Assessors need to consider many factors and the relative weight of each factor to ensure the best candidate is selected for the position. One method that can be used in candidate selection is the ORESTE method. The ORESTE method is a multi-criteria decision-making method developed by J.P. Brans and B. Mareschal in 1994. This method allows assessors to aggregate multiple criteria and consider the relative weight of each criterion to compare alternatives and produce a ranking of candidates based on the highest relative value. In the context of Service Ambassador selection, the ORESTE method can assist assessors in solving complex decision-making problems and ensuring the best candidate is selected for the position. The method allows raters to consider multiple criteria and consider the relative weight of each criterion, resulting in a ranking of candidates based on the highest relative value. Thus, the use of the ORESTE method in determining the selection of Tourism Ambassadors can simplify and speed up the candidate selection process, as well as increase accuracy and satisfaction in decision making. By using the ORESTE method, the results of the decision to select the winner of the Service Ambassador event are obtained with a preference value of 4.42
Identification of Nervosa Disease using Case-Based Reasoning Tar Muhammad Raja Gunung; Riko Muhammad Suri; Nopi Purnomo; Akbar Idaman; Abdul Muis
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3227

Abstract

Among teenagers or adults, body shape greatly affects a person's confidence. Most people will be very confident if their body shape is ideal, where the person will be very confident speaking in public. Different things with people who have a body shape that is too thin/fat, so their confidence is less to appear in public. To get the ideal body shape they will do everything possible, one of which is dieting, taking weight loss capsules, and so on. They do not know the dangers of dieting too strictly and taking weight loss capsules carelessly which can make them contract Nervosa disease. To get the results of the expert system, the case-based reasoning method will be used. After this application is built, the result obtained is the type of nervosa disease based on the symptoms felt by the user.
Comparing Neural Networks, Support Vector Machines, and Naïve Bayes Algorhythms for Classifying Banana Types Abwabul Jinan; Manutur Siregar; Vicky Rolanda; Dede Fika Suryani; Abdul Muis
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3381

Abstract

One of the most significant fruits for human consumption is the banana. Fruit consumption not only promotes health but also lowers the risk of heart disease, stroke, digestive issues, hypertension, some cancers, cataracts in the eyes, skin ailments, cholesterol reduction, and, perhaps most importantly, boosts immunity.The study included secondary data, which is information gathered from online resources like Kaggle. Ten categories of bananas will be identified from the 531 total varieties of bananas used as a train dataset: Ambon bananas, Stone bananas, Cavendish bananas, Kepok bananas, Mas bananas, Red bananas, plantains, Milk bananas, Horn bananas, and Varigata bananas. The development of information technology for image object recognition has become a very intriguing topic along with the rapid advancement of society, and it is undoubtedly directly tied to information data. In order to examine Naive Bayes, Support Vector Machine, and Neural Network techniques for classifying banana types, researchers will use the SqueezeNet Deep Learning model to extract features from photos. The study's findings will provide empirical evidence for the distinctions between each algorithm's accuracy, recall, and precision. Based on the collected results, the Neural Network (NN) method is the best in terms of classification, with accuracy of 72.3%, precision of 72.1%, and recall of 72.3%.
Diagnosis and Prediction of Chronic Kidney Disease Using a Stacked Generalization Approach Agung Prabowo; Sumita Wardani; Abdul Muis; Radiman Gea; Nathanael Atan Baskita Tarigan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3611

Abstract

Chronic Kidney Disease (CKD) is. In the past, several learners have been applied for prediction of CKD but there is still enough space to develop classi?ers with higher accuracy. The study utilizes chronic kidney disease dataset from UCI Machine Learning Repository. In this paper, individual approaches, viz., linear-SVM, kernel methods including polynomial, radial basis function, and sigmoid have been used while among ensembles majority voting and stacking strategies have been applied. Stacked Ensemble is based on various types of meta-learners such as C4.5, NB, k-NN, SMO, and logit-boost. The stacking approach with meta-learner Logit-Boost (ST-LB) achieves accuracy 98,50%, sensitivity 98,50%, false positive rate 20,00%, precision 98,50%, and F-measure 98,50% demonstrating that it is the best classi?er as compared to any of the individual and ensemble approaches
Rancang Bangun Sistem Informasi Pemasaran Barang Antik Berbasis Mobile Web Rofiqoh Dewi; Abdul Muis
Computer Science Research and Its Development Journal Vol. 15 No. 3 (2023): October 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In this era of digitalization, the use of technology in developing a product is very commonly used to introduce products, sell products and other things related to recognizing product needs such as product information, product functionality, price, or uniqueness that a product has but is not found in other products. like antiques. Currently, it is very rare to find the marketing of antiques in modern and traditional markets. The need to buy antiques is also very rare, but that doesn't mean it has disappeared with time because there are still some people who are interested in antiques if they appear displayed in a window at the market. Based on this, to make it easier for people to access antiques, technology is needed to be able to process data well to make it more efficient and effective. Based on this, the direction of the research carried out by the researcher aims to introduce antiques to all levels of society and build a mobile website to market these antiques so that people can get to know the types and benefits of antiques, the history of antiques and the prices of these antiques.
Convolutional Neural Network Activation Function Performance on Image Recognition of The Batak Script Muis, Abdul; Zamzami, Elviawaty Muisa; Erna Budhiarti Nababan
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13192

Abstract

Deep Learning is a sub-set of Machine learning, Deep Learning is widely used to solve problems in various fields. One of the popular deep learning architectures is The Convolutional Neural Network (CNN), CNN has a layer that transforms feature extraction automatically so it is widely used in image recognition. However, CNN's performance using the tanh function is still relatively low, therefore it is necessary to select the right activation function to improve accuracy performance. This study analyzes the use of the activation function in image recognition of the Batak script. The result of this study is that the CNN model using the ReLU and eLU functions produces the highest accuracy compared to the CNN model using the tanh function. The CNN model using eLU produces the best accuracy performance in the training process, which is 99.71% with an error value of 0.0108. Meanwhile, in the testing process, the highest accuracy value is generated by the CNN Model using the ReLU function with an accuracy of 94.11%, an error value of 0.3282, a precision value of 0.9411, a recall of 0.9411, and an f1-score of 0.9416.
Development of Android-Based Smart System for Gingivitis Diagnosis Using Certainty Factor Hadistio, Ryan Rinaldi; Simamora, Windi Saputri; Muis, Abdul
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13361

Abstract

Gingivitis is a gum disease that causes bleeding, swelling, redness, discharge, changes in normal contours, and although health authorities take this seriously, sometimes some patients consider it normal. This study aims to educate the public about the importance of understanding the condition of their bodies, especially the most vulnerable teeth. Lack of time to consult an expert leads to this disease being neglected. Therefore, it is necessary to develop a consultation application in the form of an expert system. The built system adopts the deterministic factor method. The certainty factor works by reading the entire data submitted by the expert and giving the result as a percentage of confidence that the patient has gingivitis. The experts used in this system are dental experts. Data obtained from direct experts and consultations resulted in new knowledge in the form of the percentage of trust patients suffering from gingivitis. The data collected are symptoms and solutions obtained from experts. This research provides a new service for patients suffering from gingivitis without the need to see a specialist directly. Based on the testing data provided to the patient and based on the patient's condition at that time, the test results of the system reached a confidence level of 98.74%. So that the results of consultation are obtained in the form of information about the disease and the solutions needed.
Analisis Metode WASPAS dalam Menentukan Pengangkatan Pegawai Kontrak Menjadi Pegawai Tetap Abdul Muis; Abdul Muis; Akbar Idaman; Handry Eldo; Agung Prabowo; Ryan Rinaldi Hadistio
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 4 No. 1 (2024): April 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v4i1.3034

Abstract

Human Resources (HR) is a valuable asset for every company, and good management greatly affects operational success. PT XYZ faces challenges in the process of appointing contract employees to permanent employees which is currently done manually, causing a slow and less accurate process. This research aims to develop a method that simplifies and accelerates the process using Weight Aggregated Sum Product Assessment (WASPAS) to simplify and speed up the decision-making process in appointing contract employees to become permanent employees at PT. XYZ, so that decisions taken can be faster, more precise and accurate. This method was chosen for its ability to reduce errors and optimize the assessment with various criteria. The results showed that Alternative 9 was ranked first with a Qi value of 0.9685, showing the best performance among other candidates. The implementation of the WASPAS method is expected to help PT XYZ in making faster, more precise, and accurate decisions, thereby increasing efficiency and objectivity in employee hiring, as well as improving the performance and stability of the company's human resources.
Analisis Kepribadian berdasarkan Konteks Acara dengan Pendekatan Klasifikasi Teorema Bayes Idaman, Akbar; Vicky Rolanda, Vicky; Abdul Muis
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 4 No. 4 (2025): EDISI JULI 2025
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v4i4.11666

Abstract

Dalam era digital yang ditandai oleh kompleksitas interaksi sosial daring, analisis kepribadian menjadi semakin penting untuk berbagai aplikasi, mulai dari sistem rekomendasi hingga pengembangan antarmuka adaptif. Penelitian ini mengangkat permasalahan bagaimana mengidentifikasi kepribadian individu secara otomatis berdasarkan konteks acara, baik formal maupun informal, yang memengaruhi ekspresi perilaku dan gaya komunikasi. Untuk menjawab tantangan ini, diterapkan pendekatan klasifikasi menggunakan Teorema Bayes yang mampu mengakomodasi ketidakpastian serta memberikan inferensi probabilistik atas fitur-fitur observasional. Penelitian ini bertujuan membangun model klasifikasi kepribadian kontekstual dengan memperhitungkan aspek gaya bahasa, tema pembicaraan, serta dinamika emosional dalam suatu acara. Hasil sementara dari penerapan metode ini menunjukkan bahwa pada rule K3, kategori kepribadian Agreeableness Tinggi memiliki nilai probabilitas tertinggi sebesar 0,9 atau 90%. Berdasarkan hasil tersebut, solusi gaya yang disarankan adalah Gaya Formal Klasik dan Kasual Santai yang selaras dengan preferensi kepribadian tersebut dalam situasi sosial tertentu. Penelitian ini berkontribusi pada pengembangan sistem cerdas yang bersifat user-aware dan context-sensitive, serta membuka peluang untuk eksplorasi lanjutan dalam bidang psikologi komputasional dan klasifikasi perilaku berbasis data.
SISTEM PAKAR PEMILIHAN SMARTPHONE BERDASARKAN KEBUTUHAN DAN PREFERENSI USER MENGGUNAKAN METODE CASE BASED REASONING Gunung, Tar Muhammad Raja; Egani Sitepu, Sengli; Pandapotan Siregar, Manutur; Muis, Abdul; Rolanda, Vicky
Djtechno: Jurnal Teknologi Informasi Vol 6, No 2 (2025): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i2.7167

Abstract

Pemilihan smartphone yang sesuai dengan kebutuhan pengguna sering kali menjadi permasalahan tersendiri, terutama karena banyaknya pilihan produk dengan spesifikasi yang bervariasi. Penelitian ini bertujuan untuk menerapkan metode Case Based Reasoning (CBR) dalam proses rekomendasi smartphone berdasarkan preferensi pengguna. CBR bekerja dengan membandingkan kasus baru, yaitu kebutuhan dan kriteria pengguna, dengan kasus-kasus sebelumnya yang telah tersimpan dalam basis data untuk menentukan tingkat kemiripan. Pada penelitian ini, digunakan empat tahapan utama dalam metode CBR yaitu: Retrieve, Reuse, Revise, dan Retain.Hasil pengujian menunjukkan bahwa dari 13 alternatif smartphone yang dianalisis, Xiaomi Poco X5 Pro mendapatkan nilai kemiripan sebesar 100%, sedangkan perangkat lainnya seperti Realme Narzo 60x, Infinix Smart 8, Vivo V27, Samsung Galaxy A54, dan lainnya memperoleh nilai kemiripan 0%. Hal ini menunjukkan bahwa Xiaomi Poco X5 Pro merupakan pilihan paling sesuai dengan kebutuhan pengguna dalam studi kasus ini. Dengan demikian, metode CBR terbukti mampu memberikan rekomendasi yang tepat dan terukur, serta dapat menjadi dasar pengembangan sistem pakar atau sistem pendukung keputusan di masa mendatang.
Co-Authors ABDUL MUIS Agung Prabowo Agung Prabowo Akbar Idaman Dede Fika Suryani Egani Sitepu, Sengli Elviawaty Muisa Zamzami Erna Budhiarti Nababan Gunung, Tar Muhammad Raja Hadistio, Ryan Rinaldi Hamjah Arahman Handry Eldo Handry Eldo Jinan, Abwabul Jinan, Abwabul Manutur Siregar Nathanael Atan Baskita Tarigan Pandapotan Siregar, Manutur Purnomo, Nopi Radiman Gea Riko Muhammad Suri Rofiqoh Dewi Rolanda, Vicky Ryan Rinaldi Hadistio Simamora, Windi Saputri Siregar, Manutur Pandapotan SUMITA WARDANI Suryani, Dede Fika Tar Muhammad Raja Gunung Vicky Rolanda Vicky Rolanda, Vicky