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Anjar Wanto
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JOMLAI: Journal of Machine Learning and Artificial Intelligence
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 82 Documents
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Application of Data Mining Classification C4.5 Patient Satisfaction with Tuan Rondahaim Simalungun Hospital Service Nadrah Fauziah; Muhammad Ridwan Lubis; Bahrudi Efendi Damanik
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 4 (2022): December
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.312 KB) | DOI: 10.55123/jomlai.v1i4.1678

Abstract

The purpose of this study was to produce a measuring instrument for patient satisfaction with hospital services. In order to further improve patient care. The method used in this study is the C4.5 Algorithm, where the data source used is a questionnaire/questionnaire technique which is given a questionnaire to the general public who visit the hospital. The results of this study are expected to provide input to the Tuan Rondahaim Hospital in Simalungun by using the C4.5 Algorithm. This can be done by using a decision tree model or decision tree in the C4.5 algorithm. In this study, the researchers used data from the patients of RSUD Tuan Rondahaim, totaling 105 patients through a questionnaire that the researchers distributed. The variables are Hospital Place (C1), Empathy (C2) and Responsiveness (C3). The testing process of this study uses Rapid Miner software to generate rules and a decision tree model or decision tree that will be used in determining the patient satisfaction factor for Tuan Rondahaim Hospital. The results of this study obtained 14 rules with an accuracy rate of 93.55%.
Application of Associations Using the Apriori Algorithm to Analyze Consumer Purchase Patterns at Grocery Stores Oka Ristawaty Sirait; Sumarno Sumarno; Nani Hidayati
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 4 (2022): December
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (578.322 KB) | DOI: 10.55123/jomlai.v1i4.1679

Abstract

The grocery store sells various types of ingredients for everyday life. Every day many customers shop at the grocery store. Every item sold at the Grocery Store will generate sales data, but this data cannot be utilized optimally. So we need a data analysis to help the Grocery Store gain knowledge of sales patterns in a certain period. The algorithm used as the primary process of analyzing the sale of ingredients in grocery stores is an a priori algorithm using the application of a minimum support value of 50% and a minimum confidence value of 70%, which meets the minimum support value and minimum confidence value, and sales transactions to find association rules. The Apriori algorithm test results will show results that have met the needs and determine the pattern of purchasing materials at the Grocery Store based on the items that customers most frequently purchase.
Analysis of the Fletcher-Reeves Algorithm in Determining the Best Model for Predicting School Life Expectancy in North Sumatra Jaya Tata Hardinata; Christa Voni Roulina Sinaga; Ferri Ojak Immanuel Pardede; Juli Antasari Sinaga
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1819

Abstract

Expected Length of School is the length of school (in years) that is expected to be felt by children at a certain age in the future. It is assumed that the probability that the child will remain in school at the following ages is the same as the probability of the population attending school per total population for the current age. Length of School is also a benchmark for evaluating government programs in improving Human Resources who excel in the competition of technological advances. This writing is done to implement and prove that the Fletcher-Reeves Algorithm can be used to predict Old School Expectations in North Sumatra. The research data is School Expectancy in North Sumatra which consists of 10 districts/cities, which was obtained from the Central Statistics Agency of North Sumatra from 2010 to 2020. This study uses 5 architectural models, namely 9-10-1, 9-15-1, 9-20-1, 9-25-1 and 9-30-1. From the five architectural models used, the best architectural model is 9-10-1 with an MSE of 0.0130650400. Based on this best architectural model, it will be used to predict the Expectation of Long Schools in North Sumatra for the next 5 years, from 2021 to 2025.
DSS Approach with the AHP Method in the Selection of Quiz Participants at SDIT Permata Cendekia Ahmad Fadhli Hasibuan; Rahmat W. Sembiring; Muhammad Ridwan Lubis
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1866

Abstract

This study aims to develop a decision support system for the selection of intelligent candidates using the Analytical Hierarchy Process (AHP) method. The case study was conducted at SDIT Permata Cendekia, an educational institution in Indonesia. The AHP method is used as a framework for making decisions based on hierarchically determined criteria and sub-criteria. The data needed in this study were obtained through interviews and observations at SDIT Permata Cendekia. After that, the steps in the AHP method, namely making a pairwise comparison matrix, calculating the weight of criteria and sub-criteria, and calculating alternative scores, are carried out in developing a decision support system. Based on the research, it was found that alternative A3 was the best alternative out of 12 alternatives assessed based on 4 (four) assessment criteria. This research is expected to be able to provide effective and efficient solutions in the process of selecting candidate quizzes at SDIT Permata Cendekia, as well as being the basis for developing a similar decision support system in selecting candidate quizzes at other educational institutions.
Determining Product Suitability using Rule-Based Model with C4.5 Algorithm Chintya Carolina Situmorang; Dedy Hartama; Irfan Sudahri Damanik; Jaya Tata Hardinata
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1923

Abstract

A hotel warehouse must have orderly, good, safe, comfortable, and usable procurement of goods. The common issue that occurs in a warehouse is damaged and unusable goods. The fluctuating production demand for goods sometimes leads to neglecting the quality of the goods in the warehouse. To determine usable goods, appropriate recommendations are needed. The C4.5 algorithm with data mining techniques is an appropriate recommendation for analyzing a large amount of data for classification. The data used in this study is the inventory data of Hotel Sapadia Pematangsiantar's warehouse. Implementing the C4.5 algorithm that produces a Decision Tree can assist the warehouse in determining which goods are still usable for hotel activities. This study resulted in the best variable from the rule model used to determine the feasibility of goods being the physical condition of the goods. The accuracy of the rule model generated from the C4.5 Algorithm modeling is 99.02% against the feasibility of goods.
Utilization of the ELECTRE and SMART Algorithms for Determining the Head of Administration for the Gunung Maligas Sub-District Office Fajar Ramadan; Rahmat W. Sembiring; Anjar Wanto
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1932

Abstract

This study aims to apply the ELECTRE (Elimination and Choice Expressing Reality) and SMART (Simple Multi-Attribute Rating Technique) algorithms in determining the administrative head of the Gunung Maligas sub-district office. The head of administration is an important position in a government organization responsible for managing various administrative and coordinating activities. The ELECTRE method produces an alternative ranking of administrative head candidates based on multiple relevant attributes. Work experience, communication skills, organizational knowledge, and leadership skills are considered. The SMART method assigns weights to each point and combines attribute values to produce an overall score for each candidate. The data in this study were obtained through surveys and interviews with related parties. After the data is collected, an analysis process is carried out using the ELECTRE and SMART algorithms to produce a ranking of candidates that best suit the needs of the Gunung Maligas sub-district office. The results of this study are expected to provide objective and accurate recommendations for selecting qualified administrative heads. By using the ELECTRE and SMART algorithm approaches, the process of determining the executive authority can be more efficient and effective and help improve managerial performance and coordination at the Gunung Maligas sub-district office.
The Best Village Selection Decision Support System in Simalungun Regency Using the SAW Method Ina Kusanti Purba; Rahmat Widia Sembiring; Saifullah Saifullah
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1933

Abstract

This study aims to develop a decision support system to select the best village in Simalungun District. The SAW (Simple Additive Weighting) method is used for decision-making. This system is designed to assist local governments and related stakeholders in selecting the best villages based on relevant criteria. The criteria covered aspects such as community education, public health, community economy, security and order, community participation, governance, social institutions, and family empowerment and welfare. Consideration of each criterion's weight or level of importance is carried out by involving experts and relevant stakeholders. The SAW method calculates the performance scores of existing villages based on predetermined criteria. The score is then used in the ranking process to determine the best village. Based on the research results, alternative villages that deserve the title of the best village are Marubun Bayu village as rank 1, Dolok Maraja as rank 2 and Naga Jaya II as rank 3. This research is expected to provide significant benefits for decision-makers in selecting the best village in Simalungun Regency to increase efficiency and objectivity in the decision-making process, as well as encourage more sustainable and equitable development in all the villages of Simalungun Regency.
Implementation of the SMART Algorithm in Determining Patient Satisfaction Levels with Outpatient Services Patar Simbolon; Muhammad Zarlis; Sundari Retno Andani; Fitri Anggraini
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.159

Abstract

This study aims to implement the SMART algorithm in determining the level of patient satisfaction with outpatient services at Vita Insani Hospital Pematangsiantar. This study uses four evaluation criteria, namely speed of service, friendliness of staff, clarity of information, and comfort of the room. There are nine alternatives evaluated, namely registration, polyclinic, doctor, cashier, laboratory, radiology, pharmacy, emergency room, and security guard. This study uses the SMART method (Simple Multi-Attribute Rating Technique) in determining the level of patient satisfaction with outpatient services. Calculations are performed either manually or computerized. The results showed that the two calculation methods yielded the same results, namely alternative A9 (Security Guard) was selected as an alternative that needed to improve its services in improving outpatient services at Vita Insani Hospital. By using the SMART algorithm, it is hoped that the hospital can identify service areas that need to be improved to increase patient satisfaction in outpatient services. This research provides valuable information for hospital management in making strategic decisions to improve service quality and meet patient expectations.
Decision Support System for Giving PDAM Tirtauli Pematangsiantar Employee Bonuses Using the Weighted Product (WP) Method Mira Ariffiani; Irfan Sudahri Damanik; Zulia Almaida Siregar
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.346

Abstract

Employee Bonuses at PDAM Tirtauli Pematangsiantar are given to employees who are selected as employees of the workforce who perform their work in accordance with the profession through the selection process. The process of judgment and decision-making in selection is usually subjective when there are some recipients of employee bonuses who have not much different abilities. Applications created in this research in the form of Decision Support System Employee Bonus Employee PDAM Tirtauli Pematangsiantar Using Weighted Product Method. This application is used to assist the selection in conducting assessments of the competency of the recipients of employee bonus giving and recommendation in decision making. The assessment criteria used include other Attendance, Number of Children, Length of Work, Responsibility, and Loyalty. Weighted Product method is a method of completion by using multiplication to associate attribute values, where the value must be raised first with the attribute weights in question. The system is built using WEB and MySQL programming language for data processing. The result of the research is the application of the recipient of the employee bonus giving to facilitate the process of selecting the recipients of the employee bonus giving according to the need.
Community Temporary Direct Assistance (BLSM) Decision Support System with the Profile Matching Method Mita Ariffiani; Irfan Sudahri Damanik; Ika Okta Kirana; Primatua Sitompul
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1033

Abstract

Community Temporary Direct Assistance (BLSM) is a Government Program. The process of assessing and making decisions in BLSM is usually subjective, especially if there are prospective BLSM recipients who have criteria that are not much different. The application made in this study is a Decision Support System for Community Temporary Direct Assistance (BLSM) in the Panguluh Nagori Gunung Bayu Office with the Profile Matching method. This application is used to assist in assessing the competence of prospective BLSM recipients and providing recommendations in decision making. The assessment criteria used include aspects of the condition of the house and economic aspects. This Profile Matching method will compare participant profiles with the ideal profile of prospective BLSM recipients. The smaller the gap, the greater the chance to pass the assessment. This system was built using the WEB programming language and MySQL as the database. It is hoped that the decision support system for receiving community temporary direct assistance (BLSM) at the Panguluh Nagori Gunung Bayu Office can assist the Village Head in determining potential beneficiaries who are entitled to be recommended for BLSM with a process of multi-criteria weighting and assessment that is faster, more accurate and more effective.

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