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JOMLAI: Journal of Machine Learning and Artificial Intelligence

jomlai
Website

Published by Yayasan Literasi Sains Indonesia

ISSN : 28289102 EISSN : 28289099 DOI : 10.55123/jomlai

Core Subject : Science, Engineering,

Computer Science & IT Engineering

Focus and Scope JOMLAI: Journal of Machine Learning and Artificial Intelligence is a scientific journal related to machine learning and artificial intelligence that contains scientific writings on pure research and applied research in the field of machine learning and artificial intelligence as well as an overview of the development of theories, methods, and related applied sciences. Topics cover the following areas (but are not limited to): Software engineering Hardware Engineering Information Security System Engineering Expert system Decision Support System Data Mining Artificial Intelligence System Computer network Computer Engineering Image processing Genetic Algorithm Information Systems Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Other relevant study topics Noted: Articles have primary citations and have never been published online or printed before

Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan

Articles 77 Documents

1 2 3 4 5

Prototype of Automatic Water Sprayer Based on Humidity Sensor and ATmega8 AVR Microcontroller in Oil Palm Nurseries Marcelo Salas Sihombing; Suhada Suhada; Ika Purnama Sari
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Oil palm nurseries are currently experiencing very rapid development, but the watering process at the oil palm nursery stage itself is still done manually so that it is less efficient in the watering process. To overcome these problems, in this study an automatic system was created using the AVRATmega8 microcontroller as the main controller of the system. With the variable humidity of the planting media as a timer for watering, a prototype water sprayer is made that can do watering automatically. The prototype of this automatic water sprayer is equipped with a soil moisture sensor which is used to read the moisture value of the oil palm growing media as well as functioning as a system input, LCD as a medium for monitoring system performance, and a relay that functions to turn on and off the water pump connected to the installation of the planting media watering pipe. . Watering of oil palm seedlings is carried out when the soil moisture sensor detects that the moisture value in the planting media has been below the lower limit of the working system and stops watering when the sensor readings indicate that the humidity value of the planting medium is above the upper limit of the working system.

Implementation of Genetic Algorithm for Subject Scheduling at SD Taman Cahya Pematangsiantar Muhammad Irfan; Muhammad Ridwan Lubis; Zulaini Masruro Nasution
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

The teaching schedule in schools is essential in teaching and learning activities; this schedule aims to support, facilitate, and improve the quality of education. With a teaching schedule, teaching and learning activities will run smoothly and efficiently. Until now, the scheduling of lessons in several schools is still done conventionally by the curriculum department, with previously held meetings for the division of tasks with the supervising teacher. The conventional teaching scheduling system for school teachers will be deemed less effective. In addition to requiring very high accuracy and relatively few estimates, this method also allows for errors. Therefore, this study aims to implement a genetic algorithm to optimize subject scheduling and apply the teacher scheduling model generated by the genetic algorithm in a web application. The data of this study were collected from observations at SD Taman Cahya Pematangsiantar. As a result, scheduling using genetic algorithms can generate schedules automatically, displaying the plan on the day and hour of each teacher's teaching schedule, thus creating an optimal solution for scheduling. In addition, applying the Genetic Algorithm is faster and easier in the process of making a schedule for setting teacher teaching hours so that it does not take a long time.

Implementation of One-step Secant Algorithm for Forecasting Open Unemployment by Highest Educational Graduate Ismi Azhami; Eka Irawan; Dedi Suhendro
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

Based on data, the open unemployment rate according to the highest education graduate in Indonesia shows the number of semester unemployment which has an unstable value, sometimes up and sometimes down. This study aims to implement the ability and performance of one of the training functions on the backpropagation algorithm, namely one-step secant, which can later be used as a reference in terms of data forecasting. The one-step secant algorithm is an algorithm that is able to train any network as long as the input, weight and transfer functions have derivative functions and this algorithm is able to make training more efficient because it does not require a very long time. The data used in this study is open unemployment data according to the highest education completed in Indonesia in 2006-2021 based on semester, which is sourced from the Indonesian Central Statistics Agency. Based on this data, a network architecture model will be formed and determined using the One-step secant method, including 14-13-2, 14-16-2, 14-19-2, 14-55-2, and 14-77- 2. From these 5 models, after training and testing, the results show that the best architectural model is 14-19-2 (14 is the input layer, 19 is the number of neurons in the hidden layer and 2 is the output layer). The accuracy level of the architectural model for semester 1 and semester 2 is 75% with MSE values of 0.00130797 and 0.00388535.

Analysis of Community Service Satisfaction Levels at the Pematangsiantar Environmental Service Using the Fuzzy Mamdani Method Joel Tindaon; Muhammad Ridwan Lubis; Ika Okta Kirana
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Currently, there are still many weaknesses and shortcomings in public services carried out by government officials, so that they have not been able to meet the quality expected by the community. This is indicated by the lack of good public services delivered through the mass media. Given that the main function of the government is to serve the community, the government must strive to improve the quality of service for the better. In this study, an analysis of the level of community service satisfaction at the Pematangsiantar environmental service will be carried out using the Fuzzy Mamdani method. Data was collected by means of observation, literature study and interviews with the Pematangsiantar Environmental Service Office. The data used consists of several variables: Number of Respondents (Variable 1), Total Response Results (Variable 2) and Output Results (Variable 3). Based on 45 respondents with a total of 43 responses, the satisfaction output obtained is 560. Based on 50 respondents, 49 responses are obtained, so the service satisfaction output is 578. The conclusion is based on the calculation of the Mamdani Fuzzy model in 2021, the community is satisfied for the services provided by the Pematangsiantar environmental service based on the range of values that have been generated.

Mobile-based Assignment Reminder Application for Students and Lecturers Kukuh Yulian Santoso; Taufiq Abidin; Slamet Wiyono
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

This research is motivated by the large number of student activities that sometimes make students forget or overlook the activities they have to do on time. One of the activities that sometimes forget or even get overlooked is assignments. Assignments are activities carried out by a group of people in carrying out learning activities. The purpose of this study is to design an android-based task reminder application that can remind students about lecture assignments, be able to remember students about the deadline for assignment collection, and other information regarding lecture activities. The application design method used is the waterfall method. Research This study was tested using white-box and black-box methods. The test results show that the application is correct, has no errors in terms of logic and function, and can functionally produce the expected output.

Classification Techniques in Predicting New Student Admission Using the Naïve Bayes Method Suwayudhi Suwayudhi; Eka Irawan; Bahrudi Efendi Damanik
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

Admission of new students is the registration process for new students entering school and the initial gate through which students enter the object of Education; this activity is the starting point for determining the smoothness of the tasks of a school, assisted by teaching staff and equipped with optimal facilities and infrastructure in teaching and learning activities, producing skilled and broad-minded students. However, the uncertainty of the number of registrants also influences the policies that will be taken in the future. Therefore, it is necessary to forecast or predict to estimate the number of students who are likely to register so that the school can prepare everything. In this study, the prediction process for new students will use a classification technique using the Naïve Bayes method. This study aims to predict the rise and fall of the number of students who register using the Naïve Bayes method. The research data was obtained by distributing questionnaires randomly to 200 respondents (students) who were about to enter high school. The data is accumulated using the help of Microsoft excel. The results obtained are that the prediction of high-class precision is 100%, while the prediction of low-class precision is 94.23%. The conclusion is that the extracurricular, cost and distance criteria need attention and improvement. This is because disinterest and low prediction are higher than interest with high prediction results.

Selection Analysis of Pre-Employment Card Recipients Using the Simple Additive Weighting (SAW) Method Tri Ayu Lestari; Harly Okprana; Rizky Khairunnisa Sormin
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

The Pre-Employment Card Program is a work and business capability development program that focuses on job seekers, laborers or workers who have finished their working period, and workers or workers who need to improve their skills, including those who have macro and micro businesses. One of these government programs aims to reduce unemployment due to the economic impact of the Covid-19 virus outbreak. Decision Support System is an effective system used to produce calculations with the output in the form of ranking. And the purpose of this research is to build a decision support system by analyzing the selection of Pre-Recipients of Pre-Employment Cards with the Simple Additive Weighting (SAW) Method. The data source of this study was obtained from the distribution of questionnaires/questionnaires which were distributed randomly to the people of Tempel Village, Kerasaan Rejo Village, Pematang Bandar. This study uses 50 alternatives and 7 criteria.

Classification of Internet Addiction Levels in Students Using the Naïve Bayes Algorithm Fakhriyah Zulfah Parinduri; Rafika Dewi; Susiani Susiani
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

The presence of the internet on students has a big influence on science and technology which makes the internet as an additional insight to find the information needed, apart from being a source of information, students also access the internet as a means of entertainment. So that it makes students last longer in front of gadgets or computers continuously. The purpose of this study is to determine whether students are indicated by internet addiction and provide input to STIKOM Tunas Bangsa to make policies that use the internet as a learning process so that internet addiction does not occur excessively. Because it is very influential in the learning process to add insight about science and technology to students. The subjects carried out by this study were students who were studying at STIKOM Tunas Bangsa. Therefore, the research was conducted using the Naïve Bayes algorithm classification, in which the data was obtained using a questionnaire distributed to students. The subjects carried out by this study were students who were studying at STIKOM Tunas Bangsa. Therefore, the research was conducted using the Naïve Bayes algorithm classification, in which the data was obtained using a questionnaire distributed to students. It is hoped that this research can be information for students to be able to maintain self-control in utilizing various entertainments on the internet.

Movidius Neural Compute Stick for Real Time Detection of Human Objects with the Mobilenet-SSD Method Maulia Rahman; Dedi Leman
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

The presence of surveillance cameras plays an important role in helping the process of monitoring and evaluating human activities in the monitored area. This ability can prevent or trace undesirable events such as criminal acts or some accidents that related to human activities. However, most of the surveillance camera that used nowadays only held a passive role in security that can lead to an increased potential risk of negligence by the guards (users) in the process of monitoring the activities that are happening. This study aims to design a system that is able to improve the performance of surveillance cameras in detecting and calculating numbers of human based on Movidius NCS on a Raspberry Pi device so that the camera can be active and be able to provide optimal results and reduce the use of excess space on the storage. The human object detection system that is used in this research applies Deep Learning technique with Mobilenet-SSD as its network architecture model. The research trials were carried out under various conditions of light intensity starting from 50-550 lux and distance to objects in range of 1-10 meters. The results showed that the accuracy obtained by the system was able to reach 91.67% with 49.24% of storage efficiency.

Comparison of Borda and NRF (Normalized Rating Frequency) in Recommender System Taufiq Abidin; Slamet Wiyono
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

The Collaborative Filtering method is a popular method in making recommender systems. Although CF is a popular method, it has major problems, namely cold start and sparsity . Several studies have been conducted to treat cold starts and sparsity. One way to overcome cold start and sparsity is the Borda calculation method. Research using the Borda method has been carried out a lot but has not utilized the rating optimally. The NRF method is a new method offered to maximize the use of ratings. By using dummy test data, the NRF method is more effective than Borda in calculating recommendation scores.

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Anjar Wanto

Contact Email
anjarwanto@ieee.org

Phone
+6282294365929

Journal Mail Official
jomlai.journal@gmail.com

Editorial Address
Jl. Bunga Cempaka No. 51D. Medan. Indonesia Phone: +62 822-9436-5929 | +62 812-7551-8124

Location
Kota medan,

Sumatera utara

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Anjar Wanto

Contact Email anjarwanto@ieee.org

Phone +6282294365929

Journal Mail Official jomlai.journal@gmail.com

Editorial Address Jl. Bunga Cempaka No. 51D. Medan. Indonesia Phone: +62 822-9436-5929 | +62 812-7551-8124

Location Kota medan, Sumatera utara INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Anjar Wanto

Contact Email
anjarwanto@ieee.org

Phone
+6282294365929

Journal Mail Official
jomlai.journal@gmail.com

Editorial Address
Jl. Bunga Cempaka No. 51D. Medan. Indonesia Phone: +62 822-9436-5929 | +62 812-7551-8124

Location
Kota medan,

Sumatera utara

INDONESIA