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Gedung Universitas Prima Indonesia, Medan Fakultas Teknologi dan Ilmu Komputer Jurusan Sistem Informasi Jl. Sekip Simpang Sikambing
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Jusikom: Jurnal Sistem Informasi Ilmu Komputer
Published by Universitas Prima Indonesia
ISSN : -     EISSN : 25802879     DOI : 10.34012
Core Subject : Science,
Decision Sciences, Operations Research & Management
This journal is about information systems and computer science.
Arjuna Subject : -
Articles 222 Documents
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APPLICATION OF THE ARIMA MODEL FOR PREDICTION OF MONTHLY DIVORCE RATE IN THE RELIGIOUS COURTS IN SOUTH SUMATRA Fitriati, Sri; Rini, Dian Palupi; -, Firdaus
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4649

Abstract

This research discusses predictions of divorce rates in Religious Courts in South Sumatra. This is important to do because the divorce rate has a changing trend. Sometimes high and sometimes low but always at a high trend number, so soCourt officials or social scientists in developing effective strategies for overcoming marriage problems, allocating resources, or supporting families who need counseling can be prepared in advance, especially at the Religious Courts in South Sumatra to reduce the divorce rate because the purpose of marriage is not to divorce. This research discusses the divorce rate in terms of predicting/forecasting because much research has been done on the divorce rate by examining the causes of divorce. This research uses the ARIMA (Autoregressive Integrated Moving Average) model to predict. The ARIMA model is a method that has been widely used in forecasting research to get good results. The research results are that the ARIMA model used is (1,0,2) and (2,0,2), with an error rate of only 0.48% using the MAPE method. Keywords: predictions, numbers, divorce, arima, mape.
IMPLEMENTATION OF THE AHP METHOD ON DECISION SUPPORT SYSTEM FOR SELECTING THE BEST RICE SEEDLINGS IN MADANG SUKU 1 SUB-DISTRICT Utami, Putri Ela Citra; Ruskan, Endang Lestari
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4743

Abstract

Rice is one of the most widely grown staples in most rural areas in Indonesia. East OKU Regency is the Regency with the second largest rice production in South Sumatra Province, Madang Suku 1 District is one of the Districts in East OKU Regency and is the center of rice production. However, many farmers in Madang Suku 1 do not know the quality of rice seeds that are by the criteria that are suitable for the village where the farm is, resulting in unsatisfactory yields for farmers, which has an impact on the welfare of rice farmers. Therefore, to help overcome the problems that occur, a system is needed that can help farmers in choosing the best rice seeds that suit the conditions of the area. This decision support system uses the AHP method, this method can make decisions effectively with complex and then simplified in a hierarchical arrangement. In addition, this method can also take into account the level of consistency and inconsistency in the assessment carried out by comparing existing factors or criteria. This research resulted in the ranking of rice recommendations for Madang Sub-district Tribe 1 which is 1.855 obtained by MR, Inpari 42 = 1.470, Ciherang = 1.119, Inpari 32 = 1.000, and Ciliwung with a value of 0.558. Keywords: Decision Support Systems; Analytical Hierarchy Process; Rice Seedlings;  
IMPLEMENTATION OF SUPPLY CHAIN MANAGEMENT AT CV.TINGGAR JAYA FOR WEB-BASED STOCK MONITORING Ramadan, Mohamad Rizqulloh; Hilabi, Shofa Shofiah; Nurapriani, Fitria; Priatna, Bayu
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4764

Abstract

Implementation of Supply Chain Management at CV. Tinggar Jaya is a company warehouse system designed for company needs to coordinate company resources. The problem that occurs at CV. Tinggar Jaya still uses manual methods, from ordering to checking or monitoring stock in the warehouse. Therefore, the solution to this problem is implementing supply chain management at CV. Tinggar Jaya will organize and monitor the warehouse's stock amount using the waterfall system design method with the expected goal of implementing supply chain management to monitor the stock of goods to be more efficient in carrying out this process. Keywords: Warehouse, Supply Chain Management, Goods, Monitoring, Stock, Website
PREDICTION OF POPULATION GROWTH IN KARAWANG CITY USING MULTIPLE LINEAR REGRESSION ALGORITHM METHOD Desfianthy, Fatiya Hanifah; Hilabi, Shofa Shofiah; Priyatna, Bayu; Novalia, Elfina
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

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

Abstract

Currently, Indonesia is experiencing population growth. The factors influencing this growth are the rates of births and deaths. Every year, the population in an area keeps growing. This growth can have various negative impacts on the region. That's why taking action and making predictions about population growth is crucial. The objective of this study is to use a regression algorithm to estimate how fast the population will grow in Karawang City. The data used for this research comes from population records collected by the Karawang City Statistics Agency between 2017 and 2022. To clean, transform, and analyze this data, we employ the Knowledge Discovery in Database (KDD) approach to data mining. By applying linear regression methods with assistance from RapidMiner tools, we have successfully generated predictions based on data that reveal patterns and relationships between variables that influence population growth rates. According to our predictions, there will increase of 338,011 people from 2022 to 2027. This research will assist the Karawang City government in developing plans to minimize negative impacts while optimizing resource utilization such as energy, food, water, and services. Keywords: Multiple Linear Regression, Data Mining, BPS, Rapid Miner
IMAGE PROCESSING FOR DETECTION OF DENGUE VIRUS Panjaitan, Christin; Panjaitan, Yoel; Sitanggang, Delima Sitanggang; Tarigan, Sri Wahyuni
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4799

Abstract

Dengue is a major health problem in tropical and Asia-Pacific regions which typically spreads rapidly in number of infection patients. Knowing that most of the world's population living in risk areas, in order to diagnose and treat the disease, high skilled experts and human resources are needed. However, in some cases human error potentially may occur. Therefore, in this research we developed a model which can diagnose dengue fever disease. This study used blood smear images that were taken under a digital microscope with 400 x magnification specifications by means of image processing techniques such as color transformation, image segmentation, edge detection feature extraction and white blood cells classification. In this study we used white blood cell counting of the role of cell differentiation as a new feature that can classify dengue viral infections of patientsvia decision tree methods. The results showed that, the white blood cells classification modeling technique of 167 cell images resulted in 92.2% accuracy while dengue classification modeling technique of 264 blood cell images resulted in 72.3% accuracy.
APPLICATION OF DATA MINING USING THE RANDOM FOREST METHOD TO PREDICT HEART DISEASE Felix, Felix; Sitanggang, Delima; Laia, Yonata; -, Amalia; Radhi, Muhammad; Barus, Ertina Sabarita
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4801

Abstract

A heart attack is when fatty deposits block the arteries. This causes symptoms such as shortness of breath and chest pain. In addition, obstructed blood flow to the heart can cause damage to the heart muscle. Heart attacks are still the highest cause of death in Indonesia to date. The problem today is that it is tough to predict and identify heart disease. The appropriate method needed to predict heart disease is the Random Forest method. This research aims to calculate the level of accuracy in predicting heart attacks. Based on research and data processing carried out by previous study by comparing two K-Neighbor algorithms, which produced an accuracy value of 83% and the Logistic Regression algorithm produced an accuracy value of 88% and it was found that the Random Forest algorithm had an accuracy of 86.88%. Thus, other algorithms are better at predicting heart attacks than the Random Forest algorithm. Keywords: Heart Attack, Random Forest, Prediction.
ANALYSIS OF THE C4.5 ALGORITHM IN PREDICTING FERTILIZER AND PESTICIDE SALES AT UD. MR ZEN AGRO Sagala, Jijon Raphita; Hasugian, Penda Sudarto; Breukelen, Melisa Van; Nantheni, W.S.Usha
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4816

Abstract

ABSTRACT Fertilizer and Pesticide sales prediction is a process for finding, assessing, and predicting fertilizer and pesticide sales for the future based on sales results in the past few months. The increasing demand from customers for Fertilizers and Pesticides means UD. Mr Zen Agro, which operates in supplying and selling necessities, needs to record sales transactions so that stock shortages and excess stock of goods do not occur. Using data mining techniques and applying the C4.5 Algorithm can help UD. Mr Zen Agro predicts sales of Fertilizers and Pesticides as a reference or guideline in making decision trees, which are able to predict sales data with a high level of accuracy by calculating the entropy value, information gain, split info, and gain ratio until the matter can no longer be calculated or is zero. An application system exists to predict sales of fertilizers and pesticides, which applies the C4.5 algorithm to UD. Mr Zen Agro, it can be seen how big the sales prediction results obtained can be implemented in a decision tree where from the decision tree, it can be seen which fertilizers and pesticides are in demand and which are not for sale. This system was built using the PHP programming language and MySQL as the database. Keywords: Data Mining, Sales Prediction, Fertilizer and Pesticide, Algorithm C4.5.   Keywords: Data Mining, Sales Prediction, Fertilizer and Pesticide, Algorithm C4.5.
THINKING UI/UX DESIGN ONLINE DESCOVERY EVENT TICKETS Ihsan, Mohammad Maftuh; Hananto, April Lia; Tukino; Huda, Baenil
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4841

Abstract

This research discusses designing the UI/UX appearance of an online ticket-purchasing application called Discovery Event to solve problems such as the absence of a group chat feature, late withdrawals of funds, and location points in the application. In implementing UI/UX Design Thinking in online ticket purchasing applications, several stages must be carried out: Empathize, Define, Ideate, Prototype, and Test. The Design Thinking method is used to create solutions to solve problems felt by users. The research results show that Discovery Event can solve problems by improving the group chat feature, efficient fund withdrawals, and adding location point features. Tests involved 20 respondents, which showed user satisfaction with the application interface design. Discovery Event offers an attractive and user-friendly interface and provides a foundation for better application development in the future. Keywords: Online ticket purchasing, Discovery Event, Design Thinking, UI, UX.
IMPLEMENTATION OF DATA MINING ROUGHT SET IN ANALYZING LECTURER PERFORMANCE Hadiyanto, Tegas; Sari, Fitri Permata; Budiarti, Lela; Syahputra, Afriadi; Wirahmadayanti, Isna
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4842

Abstract

Lecturers are professional educators or scientists with the main task of transforming, developing, and disseminating science, technology, and art through education, research, and community service by the Tridharma of Higher Education. The main task of lecturers is to implement the tri dharma of higher education with the scope of activities in the form of teaching, research, and community service. Based on this, the Payakumbuh College of Technology assesses lecturers' performance to maintain the educational institution's quality. A method is needed to identify the quality of lecturers' performance. Lecturer performance can be determined using a rough set approach with several stages. Rough set is a data mining technique applied in several fields, including selecting study programs and predicting mobile phone sales income. Based on the results of using the rough set method, lecturer performance information is produced in a certain period, which aims to help leaders understand the possible performance of lecturers in a certain period. The benefit that can be obtained is that the knowledge obtained through the rough set method can determine the possibility of achieving lecturer performance.
ANALYSIS OF FORWARD CHAINING METHOD ON LAPTOP DAMAGE DIAGNOSIS EXPERT SYSTEM Jufri, Fikri Ramadhan; Akbar, Muhamad Rafi; Auriga, Wira; Syaputra, Eka Benny
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4847

Abstract

The forward chaining method is used in expert systems to reach conclusions by starting from known facts and moving forward to find a solution or diagnosis. In diagnosing damage to student laptops, this method will begin with information about the symptoms or problems experienced by the computer laptop. The system will evaluate these symptoms and match them with pre-programmed rules to identify possible causes of damage. This process continues by adding new information and making decisions based on sequentially applied rules until reaching a final diagnosis. In diagnosing damage to student laptops, the forward chaining method can help systematically identify problems based on observed symptoms, guiding users through the diagnosis process efficiently. Keywords: forward chaining, expert systems, laptop damage.

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