http://ejurnal.setiabudi.ac.id/ojs/index.php/tekinfo/issue/feed Tekinfo: Jurnal Ilmiah Teknik Industri dan Informasi 2021-09-03T06:00:33+00:00 Ida Giyanti jurnaltekinfo@gmail.com Open Journal Systems <p style="text-align: justify;"><span lang="en"><strong>Tekinfo ( Jurnal Ilmiah Teknik Industri dan Informasi )</strong> merupakan jurnal yang dikelola oleh program studi S1 Teknik Industri, Fakultas Teknik, Universitas Setia Budi yang terbit setiap enam bulan sekali yaitu Bulan Mei dan Bulan November pada setiap tahunnya. Naskah yang kami terbitkan mencakup bidang ilmu Teknik Industri dan Teknologi Informasi. Kami terbuka bagi para pembaca dan peneliti untuk berkontribusi mengirimkan naskah penelitian yang mencakup bidang ilmu tersebut.<br></span></p> http://ejurnal.setiabudi.ac.id/ojs/index.php/tekinfo/article/view/904 Implementation of Decision Tree Algorithm (J.48) to Predict Risk of Credit in BMT 2021-09-03T06:00:33+00:00 Atik Febriani atik@ittelkom-pwt.ac.id Violita Anggraini 18106060@ittelkom-pwt.ac.id <p><em>Credit is crucial in financial institutions that affects the growth and development of these institutions. Weak supervision and management in the process of extending credit to customers can lead to high non-performing loans. This problem occured in one of the financial institutions that provides credit to customers, namely BMT X. Data for 2019 showed that there were 600 applications for multipurpose loans. Of these, only about 76% showed good collectability. The condition of credit collectability that is not optimal causes BMT X to spend more to collect installments that must be paid by the debtor directly. This bad credit causes losses to the financial institution. Thus, in providing credit, BMT X must be smart in assessing customer’ feasibility. The purpose of this research is to design credit policies in order to minimize the prediction errors of customers with bad credit category. The technique used in this research is classification data mining with the J.48 algorithm. To measure the effectiveness of an attribute in classifying a data sample set, it is necessary to select the attribute that has the greatest information gain which will be placed at the root node. This research produces six rules with an accuracy level of 80,2% so as it can be used by BMT X to search customer’s feasibility to gain credit.</em></p> <p><strong><em>Keywords</em></strong><strong>: </strong><em>Algorithm J.48, data mining, decision tree, credit risk</em></p> 2021-04-30T04:29:51+00:00 ##submission.copyrightStatement## http://ejurnal.setiabudi.ac.id/ojs/index.php/tekinfo/article/view/1090 Application of C4.5 Algorithm for Late Payment Classification of Insurance Premiums 2021-09-03T06:00:30+00:00 Jefry Antonius Karlia jefryantonius87@gmail.com Wawan Nurmansyah w_nurmansyah@ukmc.ac.id <p><em>The problem that often arises in insurance companies is the number of customers who do not smoothly pay premiums. The procedure that applies to the insurance during the grace period is 30 days. The insured customer must follow the premium payment procedure, if the customer does not pay the premium, the insurance policy will be canceled, this is part of the company's loss. An insurance company has a lot of data and this data can be processed to produce information on how to find out potential customer delays from a pattern formed using the C4.5 method. This research was conducted by applying the C4.5 algorithm using insurance customer data. The results of this study are a classification system for late payment of insurance premiums that can classify insurance customer premium payment status as a consideration for accepting insurance customers. The system test results show that the system can classify the status of insurance customer premium payments with a classification accuracy of 88%.</em></p> <p><em><strong>Keywords: </strong>Algorithm C 4.5, Insurance, Classification, Premium<br></em></p> 2021-05-29T00:00:00+00:00 ##submission.copyrightStatement## http://ejurnal.setiabudi.ac.id/ojs/index.php/tekinfo/article/view/1182 Rice Production Forecasting in Central Java Province 2021-09-03T06:00:28+00:00 Muhammad Ridwan muh.ridwan26@gmail.com Hari Purnomo haripurnomo@uii.ac.id Nancy Oktyajati oktyajati_nancy@gmail.com <p><em>The availability of local rice needs to be predicted to meet the demand for rice supply in Indonesia</em><em>.</em><em>&nbsp;Central Java, as the third largest rice producer in Indonesia, is one of the pillars of national rice demand</em><em>.</em><em>&nbsp;The amount of food production in Indonesia is an important factor in determining the right food supply</em><em>.</em><em>&nbsp;Forecasting rice production in Central Java is necessary to determine future food conditions</em><em>.</em><em>&nbsp;The purpose of this research is to develop a forecast model for rice production in Central Java province and to find out the estimated rice production in Central Java Province in the next </em><em>5</em><em>&nbsp;years</em><em>.</em><em>&nbsp;The time series forecasting method was used in this study</em><em>.</em><em>&nbsp;The data used in this study are data on rice production from 1993 to 2020</em><em>.</em><em>&nbsp;From the results of the </em><em>A</em><em>uto </em><em>C</em><em>orrelation </em><em>F</em><em>unction (ACF) test, it is known that the production data has a trend data pattern</em><em>.</em><em>&nbsp;The method used in this study is the double exponential smoothing method with two parameters (Holt's Methods)</em><em>.</em><em>&nbsp;The optimal forecasting model is obtained with the help of solver software in Microsoft Excel</em><em>.</em><em>&nbsp;By using the help of the Microsoft Excel solver, the optimal constant value α is 0,767 and β is 0,412 with a Mean Absolute Precentage Error value of 4,82%</em><em>.</em><em>&nbsp;Forecasting results from 2021 to 2025 are known to decline every year</em><em>.</em><em>&nbsp;The average decline in rice production in the next </em><em>5</em><em>&nbsp;years is estimated at 4,4% per year</em><em>.</em></p> <p><strong><em>Keywords</em></strong><strong>: </strong><em>rice, exponential smoothin</em><em>g</em><em>, Central Java, forecastin</em><em>g</em></p> 2021-06-14T04:00:06+00:00 ##submission.copyrightStatement## http://ejurnal.setiabudi.ac.id/ojs/index.php/tekinfo/article/view/1089 Analysis of The Effect of Knowledge Sharing Behaviors on Employee Performance in The Garment Industry 2021-09-03T06:00:26+00:00 Bramantiyo Eko Putro bramantiyo@unsur.ac.id Rahmat Ramdani rahmatramdani747@gmail.com <p>Eastern Modern Apparel (EMA) is a <em>textile company located</em><em> in Cipeuyeum, Cianjur Regency. This research was conducted to determine the impact of knowledge sharing on the performance of employees of PT. EMA. </em><em>S</em><em>everal divisions in PT. EMA makes knowledge sharing among individuals still lacking so that knowledge of employee performance improvement is not fully evenly distributed. The model used is a development of the Theory of Planned Behavior with the addition of several factors. These factors are expected relationships, expected contributions, pleasure in helping others, self-competence, availability of resources, technology, trust, attitudes toward sharing, intention to share and by adding some factors to sharing explicit knowledge and sharing implicit knowledge. Data collection was carried out by distributing questionnaires directly or online. The data obtained is used to test the conceptual model emipirically using structural equation modeling. The conceptual model was tested with 220 samples. The results showed that the availability of resources, attitudes towards sharing, intention to share knowledge had a positive impact on explicit knowledge sharing activities. Sharing explicit and </em><em>tacit</em><em> knowledge has a positive impact on employee performance with a coefficient value of 0,001 but not significant.</em></p> <p><strong><em>Keywords</em>: </strong><em>knowledge sharing, employee performance, SEM, textile industry</em></p> 2021-06-17T06:57:11+00:00 ##submission.copyrightStatement## http://ejurnal.setiabudi.ac.id/ojs/index.php/tekinfo/article/view/848 Lamp Selection in the Library Lighting System using the Fuzzy AHP Method 2021-09-03T06:00:24+00:00 Frisheila Sely Apriliana freesela@gmail.com Bambang Suhardi bambangsuhardi@staff.uns.ac.id <p><em>Library is an important aspect that must exist in an educational institution because it is one source of knowledge and learning. Reading activities are the main activities carried out in the library, so the lighting aspect is one aspect that must be considered to create a good library environment. The selection of lamps as artificial light sources must be adjusted to the needs. The selection of lights can be done using the Multi Attribute Decission Making (MADM) method. One of the MADM methods used to analyze parameters and decision making criteria is Fuzzy Analytical Hierarchy Process (Fuzzy AHP). Fuzzy AHP method is the development of the AHP (Analytical Hierarchy Process) method which consists of matrix elements that are represented by fuzzy numbers. Although AHP can be used to handle quantitative and qualitative criteria in MADM, fuzzy AHP is considered able to describe vague decisions better than AHP. Besides that, Fuzzy AHP is also able to cover the subjectivity problem in AHP. In this study, the respondents are some people who are considered experts in providing judgments and decisions related to the process of selecting lights in the library. The party is the staff of the Household Section as the party in charge of administration regarding the procurement of goods in the Library, the BMN Managing staff of the electricity section as the party responsible technically about the electrical equipment in the Library and the Procurement Services Unit staff as the party responsible for procurement of goods. There are three alternative lighting brands used in this study, namely Philips, Hannoch and OSRAM. Three alternative lighting brands are used because they have a product with a lumen value that matches the lumen needs of each lamp in the Library. Based on the results of ranking using the fuzzy AHP method, it was found that the lamp chosen at priority one was Philips with a weight of 43%, priority two was OSRAM with a weight of 38%, and priority three was Hannoch with a weight of 18%.</em></p> 2021-07-26T07:27:19+00:00 ##submission.copyrightStatement## http://ejurnal.setiabudi.ac.id/ojs/index.php/tekinfo/article/view/1161 Value Engineering Analysis of Decorative Lightning in Product Development 2021-09-03T06:00:22+00:00 Muhammad Yusuf yusuf@akprind.ac.id Cyrilla Indri Parwati cindriparwati@akprind.ac.id Amelia Rachmi Nasution ameliarn07@gmail.com <p><em>Currently, the sales of decorative lighting products are very low because the design of decorative lights are less attractive to consumers. Therefore, the company must develop the product to produce quality products that are updated and attractive to consumers. This research aims to develop the decorative light products using value engineering. Value engineering was used to increase benefits withoutt increasing costs, reducing costs without reducing benefits, or a combination of both. This research was conducted to find out the level of efficiency that can be achieved from several recommended alternatives. Research results showed that the value of the initial design (Product A) was 3,48 x 10</em><em><sup>-7</sup></em><em>; product B was 3,16 x 10</em><em><sup>-7</sup></em><em>; and product C was 8,83 x 10</em><em><sup>-7</sup></em><em>. The use of raw materials has also changed from its initial design which was using a mixture of copper and brass with a thickness of 0,8 mm to an alternative design by using a mixture of copper and brass with a thickness of 0,5 mm. In addition, the study showed that product C are more preferable for consumers.</em></p> <p><strong><em>Keywords:</em></strong><em>&nbsp;decorative lighting, product development, pairwise comparison, value engineering</em></p> 2021-08-10T03:37:58+00:00 ##submission.copyrightStatement## http://ejurnal.setiabudi.ac.id/ojs/index.php/tekinfo/article/view/1064 The Effect of Job Satisfaction on Organizational Commitment 2021-09-03T06:00:20+00:00 Maria Puspita Sari puspitamaria20@gmail.com Mathilda Sri Lestari mathilda3015@gmail.com Suprapto Suprapto supraptodd@yahoo.co.id <p><em>Company employees as human resources are important capital that must receive high attention by companies, including construction companies. Along with the rapid growth of the construction sector, construction activities are carried out evenly in various regions in Indonesia, one of which is in the Sukoharjo district. Employees will tend to leave the organization if they are not satisfied with the work climate and job characteristics. Employees will have a high organizational commitment when they are satisfied with their work, supervision, salary, promotion and co-workers. This study aims to identify the effect of employee job satisfaction on organizational commitment by taking a case study on a construction company in the Baki sub-district, Sukoharjo. Data was collected by distributing questionnaires to 30 construction company employees. The data processing method used was linear regression. The results showed that there was a positive and significant relationship between job satisfaction and organizational commitment.</em>&nbsp;</p> <p><strong><em>Keywords</em></strong>:<strong>&nbsp;</strong><em>job satisfaction, organizational commitment,</em><strong><em>&nbsp;</em></strong><em>construction employees, linear regression</em></p> 2021-08-31T00:00:00+00:00 ##submission.copyrightStatement##