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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 10 Documents

Search results for , issue "Vol. 1 No. 2 (2022): June" : 10 Documents clear

Diabetes Risk Prediction using Logistic Regression Algorithm Qatrunnada Refa Cahyani; Mochammad Januar Finandi; Jathu Rianti; Devi Lestari Arianti; Arya Dwi Pratama Putra
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Many factors affect people suffering from diabetes, some of which are high blood pressure, excess sugar levels, weight, genetic history of diabetes, age, number of pregnancies, skin fold thickness, and the amount of insulin levels in the body. Logistic regression is a statistical tool that can be used in classification modeling about the presence or absence of diabetes. The aim of this study is to predict diagnostically whether a patient has diabetes or not. The results obtained are relatively low predictions because the ranges of values of several factors that cause it are very far apart so normalization is carried out so that the ranges of values are close together. The result is that diabetes risk prediction using a logistic regression algorithm with normalization resulted in a recall of 55% while without normalization it was 43%. Thus, normalization can improve the performance of diabetes risk prediction using a logistic regression algorithm. This model is expected to be a reference for the treatment of diabetics for doctors in hospitals and in the community to find out how to maintain a lifestyle and how to avoid diabetes in terms of the variables that affect the occurrence of the disease.

Implementation of K-Means Algorithm for Clustering Books Borrowing in School Libraries Daud Siburian; Sundari Retno Andani; Ika Purnama Sari
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

The school library is an important resource in an effort to support the process of improving the quality of education in schools. Through the library a lot of information can be extracted and used for educational purposes. The library is expected to play its function as a vehicle for education, research, preservation, information, and recreation to improve the nation's intelligence. This study aims to cluster the borrowing of library books at SMA Assisi Pematangsiantar. The research data was obtained from the school library. The algorithm used for the clustering process is K-Means Clustering which is one of the data mining algorithms. The data was processed using Microsoft Excel and Rapid Miner 5.3 to determine the value of the centroid in 2 clusters, namely the highest and lowest clusters. Based on manual calculations with Microsoft Excel and testing with Rapid Miner, this study resulted in the same value, namely the highest cluster produced 6 types of books including Mathematics,. Geography, Chemistry, Civics, Physical Education and Computers. As for the lowest cluster, there are 6 types of books, namely Indonesian, English, Biology, Physics, Religion and Cultural Arts. So it can be concluded that the K-Means method in this study can cluster school library book borrowing well, referring to manual calculations and testing which have the same results

Application of Artificial Bee Colony Algorithm to Optimize The Shortest Route to Distribute Clean Water Pipes Mhd Furqan; Yusuf Ramadhan Nasution; Khairunnisa Khairunnisa
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Regional Water Company Tirtanadi is a company engaged in clean water treatment and distributing clean water into the customers’ houses. The pipelines used are long and branched which causes the water volume to be divided. So, the alternative solution offered, to make sure the water distribution to each customers’ houses are efficient, is to search the shortest route using the Artificial Bee Colony algorithm. Artificial Bee Colony algorithm is a metaheuristic algorithm which has a strong global search ability and is able to solve continuous problems on determining the optimal clean water pipe route. This research’s goal is to facilitate Tirtanadi company on deciding the best installation point for the clean water distribution pipe. This research uses a dataset in the form of 8 installation points and one water treatment plant point. According to the calculation result on determining the best water pipe route using the Artificial Bee Colony algorithm obtained an optimal route which is V1→V7→V4→V9→V8→V2→V6→V3→V5. So it can be concluded that Artificial Bee Colony Algorithm is able to decided the search for clean water distribution pipes route on PDAM Tirtanadi and is able to give a good solution for searching for the shortest route.

Optimization of Computer Network Security System Against Malware Attacks Using Firewall Filtering with Port Blocking Method Andri Andri; Indra Gunawan; Ika Okta Kirana
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Computer networks have an important role in teaching and learning activities in schools, but there are also negative impacts. One of them is prone to attack by malware such as viruses and so on, as is the case at the Satria Mandiri Private Vocational School in Bandar Huluan. So far, the computer network at the school is very easy to attack by malware. The negative impact of malware on the network is bandwidth traffic overload, causing bandwidth constraints to run out quickly or data transfer traffic to be slower than usual. The reliability of a network can be determined from the security factor of the network itself. Some routers have firewall settings that are quite capable but need to be managed more specifically based on the needs of the 1500 Kbps network scale and available bandwidth. Creating good rules in the firewall will make it easier to filter network traffic and bandwidth so that it can create security and convenience for network and bandwidth users. Port blocking allows users or users to interact with the proxy server on the local network, where the connected user has gone through verification that can filter malware activity with embedded rules

Identification of Rice Plant Diseases Through Leaf Image Using DenseNet 201: Identifikasi Penyakit Tanaman Padi Melalui Citra Daun Menggunakan DenseNet 201 Primatua Sitompul; Harly Okprana; Annas Prasetio
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Indonesia as an agrarian country with the largest population uses rice as a staple food is depending on rice production. The lack of quantity and quality of production that often occurs is caused by disease attacks on plants that are detected too late. This is due to the lack of agricultural extension workers who help farmers in dealing with plant diseases. This study conducted an experiment on rice plant diseases based on leaf imagery using a dataset that has four classifications of leaf conditions of rice plants, namely healthy, brown spot, hispa, and leaf blast. The results obtained are quite good, namely, the accuracy value of the training data is 88.4% and 82.99% in data testing using the Densely Connected Convolutional Networks (DenseNet)-201 architecture as. From the results of the key research, DenseNet201 is quite suitable to be used to carry out diseases in rice plants so that the types of diseases that attack can be identified and given early. Thus food security can be maintained and not cause losses due to crop failures that harm farmers.

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.

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.

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.

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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