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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science ARSY : Jurnal Aplikasi Riset kepada Masyarakat
Lubis, Arif Ridho
Politeknik Negeri Medan
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Prediction analysis of the happiness ranking of countries based on macro level factors Dini Oktarina Dwi Handayani; Muharman Lubis; Arif Ridho Lubis
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp666-678

Abstract

Happiness is an essential universal human goal in their life that can improve the quality of life. Since the introduction of positive psychology, the primary consideration has been pointed out to the study of the role from certain factors in predicting the happiness, especially the advancement of technology that allows computer-mediated to be part of human interaction. It provides a multidimensional approach and indirect influence to the human expression and communication. The project investigates what it takes to build a happy country by analysing on the relationship between the happiness ranking of countries and their macro level factors. The World Happiness Report 2019 is used coupled with Python programming for visualizing and extracting information from the dataset to better understand the bigger picture.
Automatic face recording system based on quick response code using multicam Julham Julham; Muharman Lubis; Arif Ridho Lubis; Al-Khowarizmi Al-Khowarizmi; Idham Kamil
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i1.pp327-335

Abstract

This research mainly talks about the use of quick response (QR) code reader in automating of recording the users' face. The applied QR code reader system is a dynamic type, which can be modified as required, such as adding a database, functioning to store or retrieve information in the QR code image. Since the QR code image is randomly based on its information, a QR code generator is required to display the image and store the information. While the face recorder uses a dataset available in the OpenCV library. Thus, only the registered QR code image can be used to record the user's face. To be able to work, the QR code reader should be 10 to 55 cm from the QR code image.
Information technology based smart farming model development in agriculture land Al-Khowarizmi Al-Khowarizmi; Arif Ridho Lubis; Muharman Lubis; Romi Fadillah Rahmat
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp564-571

Abstract

Smart farming in various worlds is not just about applying technology in terms of storing data on agricultural land. However, having a concept of measurable data based on available computational techniques trained and then generating knowledge. As an application, the agri drone sprayer can be used for the process of applying pesticides and liquid fertilizers on each side. In addition, drone surveillance is also useful in implementing smart farming such as mapping land so that farmers will know the condition of their agricultural land. However, the soil and weather sensor will also help the farmers to monitor the farmland as well. Devices with sensors can only obtain data in the form of air and soil humidity, temperature, soil pH, water content and forecasting the harvest period. So that the smart farming model can help farmers to get recommendations, in preventing the predicted damage to their land and crops. However, according to its geographical location, the application of smart farming can be a smart solution to agricultural problems in Indonesia and make the future of Indonesian Agriculture a technology-based smart agriculture.
Optimization of distance formula in K-Nearest Neighbor method Arif Ridho Lubis; Muharman Lubis; Al- Khowarizmi
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (610.331 KB) | DOI: 10.11591/eei.v9i1.1464

Abstract

K-Nearest Neighbor (KNN) is a method applied in classifying objects based on learning data that is closest to the object based on comparison between previous and current data. In the learning process, KNN calculates the distance of the nearest neighbor by applying the euclidean distance formula, while in other methods, optimization has been done on the distance formula by comparing it with the other similar in order to get optimal results. This study will discuss the calculation of the euclidean distance formula in KNN compared with the normalized euclidean distance, manhattan and normalized manhattan to achieve optimization results or optimal value in finding the distance of the nearest neighbor.
Analysis of Educator Readiness in the Online Teaching Learning Process Using Naïve Bayes Yuyun Yusnida Lase; Yulia Fatmi; Haryadi Haryadi; Arif Ridho Lubis; Santi Prayudani
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 2 (2022): Issues January 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i2.5964

Abstract

This study discusses the readiness of educators in the online teaching and learning process. Samples of data were taken randomly as many as 100 (one hundred) people who were carried out using a questionnaire for educators at the junior high school level in the city of Medan. The variables used in the research are human resources, facilities and infrastructure, skills in applying technology, time management in online learning, the assessment process. Data processing and data analysis using nave Bayes algorithm. This algorithm is very well used for the process of classifying large amounts of data. The reason for using the nave Bayes algorithm in processing and analyzing data is because the way this algorithm works uses statistical and probability methods in predicting future results. The results of calculations using the nave Bayes algorithm based on the specified training data show that educators at the junior high school level are ready for the online learning process.
The effect of a SECoS in crude palm oil forecasting to improve business intelligence Al-Khowarizmi Al-Khowarizmi; Ilham Ramadhan Nasution; Muharman Lubis; Arif Ridho Lubis
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (561.401 KB) | DOI: 10.11591/eei.v9i4.2388

Abstract

Crude palm oil is a crop that has a harvest period of ± 2 weeks and is in dire need of dissemination of information using e-commerce in order to be able to predict the price of the yield of companies or individual gardens within the next 2 weeks in order to improve studies on business intelligence. The disadvantage of not implementing e-commerce is certainly detrimental to the garden owner because they have to go through an agent so prices are set based on the agent. So with the application of e-commerce, buyers of crude palm oil can predict prices in conducting business processes to the future. So the need to forecasting the price of crude palm oil heads in order to improve the application of business intelligence using the evolution-based artificial neural network (ANN) method which in this paper is tested with SECoS get a MAPE value of 0.035% and by applying business intelligence can protect transaction costs by 33.3%.
Astrocytoma, ependymoma, and oligodendroglioma classification with deep convolutional neural network Romi Fadillah Rahmat; Mhd Faris Pratama; Sarah Purnamawati; Sharfina Faza; Arif Ridho Lubis; Al-Khowarizmi Al-Khowarizmi; Muharman Lubis
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i4.pp%p

Abstract

Glioma as one of the most common types of brain tumor in the world has three different classes based on its cell types. They are astrocytoma, ependymoma, oligodendroglioma, each has different characteristics depending on the location and malignance level. Radiological examination by medical personnel is still carried out manually using magnetic resonance imaging (MRI) medical imaging. Brain structure, size, and various forms of tumors increase the level of difficulty in classifying gliomas. It is advisable to apply a method that can conduct gliomas classification through medical images. The proposed methods were proposed for this study using deep convolutional neural network (DCNN) for classification with k-means segmentation and contrast enhancement. The results show the effectiveness of the proposed methods with an accuracy of 95.5%.
Development of soil moisture measurement with wireless sensor web-based concept Julham Julham; Hikmah Adwin Adam; Arif Ridho Lubis; Muharman Lubis
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp514-520

Abstract

Measurement of soil moisture commonly by applying the soil moisture sensors is to measure the condition of the ground around which is relatively not wide. Therefore if applied for the large-scale, repeated measurements are required in accordance with the determined point. As a result it takes time to get the whole results. With the existence of wireless sensor technology then this problem can be overcome. This wireless sensor system will create a network consisting of nodes and server. In this study the server part is a server computer that requires a web server application together with its script to display and store data, while the node part is the data reader system. In the data system reader module, the sensor device is required as the input that is SEN0114, the processor is a microcontroller, while the wireless uses Wi-Fi module that is ESP8266. Wi-Fi topology used later is infrastructure (using access points). In this research, it begins by testing the sensor and then testing the data validation between the node and the server. SEN0114 sensor has different value from the American Standard Method (ASM) that is 0.922%. While the data validation test of the measurement result is Wi-Fi ESP8266 module which has a maximum distance of 14 meters toward the access points.
Dealing with Voters’ Privacy Preferences and Readiness in Electronic Voting Muharman Lubis; Arif Ridho Lubis
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp994-1003

Abstract

Various countries have been encouraged to adopt electronic voting because it can reduce operational cost and time spent for tabulation process. In the current research, it has been mentioned several problem arised in term of technical aspects, voters’ trust, machine vulnerabilities and privacy right in which experts argued the election system have been compromised. In short term, the certain faction will try to exploit the system weaknesses for their own benefit, while in the long term, it can create public distrust to the government, which decrease the voters turn out, break the participation willingness and downgrade the quality of voting. Thus, the government should deal with previous issues in the election before adopting electronic approach while at the same time align with voters’ expectation to provide better election in serve citizen through comprehensive analysis. This study provide initial step to analyse the readiness of electronic voting from the social perspective in response to how Indonesia view the initiative to adopt new tech in voting system.
Decision Making in the Tea Leaves Diseases Detection Using Mamdani Fuzzy Inference Method Arif Ridho Lubis; Santi Prayudani; Muharman Lubis; Al Khowarizmi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp1273-1281

Abstract

The tea plants (Camellia Sinensis) are small tree species that use leaves and leaf buds to produce tea harvested through a monoculture system. It is an agriculture practice to cultivate one types of crop or livestock, variety or breed on a farm annually. Moreover, the emergence of pests, pathogens and diseases cause serious damages to tea plants significantly to its productivity and quality to optimum worst. All parts of the tea plant such as leaves, stems, roots, flowers and fruits are exposed to these harm lead to loss of yield 7 until 10% per year. The intensity of these attacks vary greatly on particular climate, the degree slope and the plant material used. Therefore, this study analyzes tea leaves as a common part used in recipes to create unique taste and flavor in tea production, especially in agro-industry. The decision making method used is Fuzzy Mamdani Inference as one of model with functional hierarchy with initial input based on established criteria. Fuzzy logic will provide tolerance to the set of value, so that small changes will not result in significant category differences, only affect the membership level on the variable value. Previous method using probabilities have shown 78% tea leaves have been attacked by category C (Gray Blight) while using Mamdani indicated 86% of tea leaves have been infected. In this case, this result pointed out that Fuzzy Mamdani Inferences have more optimal result compare to the previous method.
Co-Authors Al Khowarizmi Dini Oktarina Dwi Handayani Habibi Ramdani Safitri Hikmah Adwin Adam Idham Kamil Ilham Ramadhan Nasution Irvan, Irvan Julham Julham Mahyuddin K M Nasution Mhd Faris Pratama Muharman Lubis Prayudani, Santi Romi Fadillah Rahmat Sarah Purnamawati Sharfina Faza Yulia Fatmi Yulia Fatmi Yuyun Yusnida Lase