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Jurnal Teknik Informatika C.I.T. Medicom
Published by Institute Of Computer Science
ISSN : 23378646     EISSN : 2721561X     DOI : -
Core Subject : Science,
Computer Science & IT
The Jurnal Teknik Informatika C.I.T a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 55 Documents
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A Decision Support System on Employee Assessment Using Analytical Network Process (ANP) and BARS Methods I Made Dwi Putra Asana; I Gede Iwan Sudipa; Kadek Ari Prayoga Putra
Jurnal Teknik Informatika C.I.T Medicom Vol 13 No 1 (2021): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol13.2021.38.pp1-12

Abstract

Employee assessment is needed in evaluating performance and granting rewards to employees. PT. Kupu-Kupu Taman Lestari conducts an employee performance appraisal using Microsoft Excel. The growth of employee data and assessment variables resulted in the calculation method that was carried out could not provide employee ranking information quickly. The application of Microsoft Excel in processing employee valuation data has weaknesses in data documentation. The purpose of this study is the company has a website-based decision support system that makes it easy for companies to get employee performance appraisal information. The employee performance data ranking method used is the Analytical Network Process (ANP) and the performance evaluation criteria are prepared based on the Behaviorally Anchor Rating Scale (BARS) approach. BARS is used in determining criteria along with a scale of behavior that represents the performance of each criterion. ANP is used to process data of importance between criteria so that it can produce criteria weights based on a comparison between criteria. The results of this study are website-based decision support systems that can be accessed by company management via a web browser. System testing is built based on testing manual calculations with the system and testing the user's system according to the McCall model. The system calculation test shows that the system has produced the same calculation value as the manual calculation. System user testing shows that the system built meets user needs, displays information according to user input correctly, is safe from unauthorized parties, and the system is easy to use.
Development of The Application for Car Audio Parts Detection Damage Using Case Based Reasoning Method and Nearest Neighbor Algorithm Andika Saputra; Ali Khumaidi
Jurnal Teknik Informatika C.I.T Medicom Vol 13 No 1 (2021): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol13.2021.45.pp42-50

Abstract

PT. Denso Ten often receives car audio spare parts that are damaged due to shocks during the trip or sender's error. Damaged parts are collected and repaired by maintenance who has special skills manually. The limited number of maintenance operators and the frequent transfer of experts resulted in work delays due to insufficient spare parts. Spare parts repair work cannot be done by all employees because it requires special skills. The Case-based Reasoning approach and Nearest Neighbor algorithm are used to be developed for expert systems to support the detection of audio part damage so that it will speed up work and can be done by employees without special knowledge. The system can run and be used by users properly as needed and the results have good accuracy. The Case Base Reasoning method and the nearest neighbor algorithm work according to the rules and the calculation results are according to the expert's results.
Penerapan Metode AHP-SAW dalam Sistem Pendukung Keputusan Pemilihan Desa Wisata Terbaik Ni Ketut Ayu Purnama Sari
Jurnal Teknik Informatika C.I.T Medicom Vol 13 No 1 (2021): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol13.2021.51.pp23-32

Abstract

From the perspective of advanced tourism growth, Indonesia's economy is expected to enter the top ten in the world by 2025 before the 2020 COVID-19 pandemic. Balinese workforce absorbs nearly a third of the total population and Balinese are involved in tourism. Garbage and congestion are problems the government must solve in building a better Bali tourism industry in the future. One way to solve this problem is to develop rural ecotourism, which can choose to use a decision support system. In this study, the method used was a combination of AHP-SAW. This manual DSS calculation process can be implemented in web-based software. DSS employs 3 tourists as decision maker. There are 10 alternative tourism villages tested using AHP-SAW, and the tourist villages produced by Pemuteran are the most popular tourist villages. Pemuteran Tourism Village obtained a score of 0.9241. Jatiluwih Tourism Village obtained a score of 0.9117 in second place; Plaga Tourism Village obtained a score of 0.9115 in third place.
Penerapan Metode AHP-MAUT dan AHP-Profile Matching pada SPK Penempatan Siswa OJT Gede Surya Mahendra; Eddy Hartono
Jurnal Teknik Informatika C.I.T Medicom Vol 13 No 1 (2021): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol13.2021.56.pp13-22

Abstract

To improve the quality and quality of employment, OJT is very much needed by Monarch Bali students, but the process, which is still manual, makes decisions that are taken less fast, accurate, effective and efficient. In line with the roadmap of Monarch Bali, it is necessary to develop an automation system to be able to improve the performance of decision making for OJT student placement by making a DSS. The method used in this research is AHP-MAUT and AHP-PM. The decision makers in this study were 3 people, and out of a total of 500 OJT students, 8 OJT students for F&B class, 12 OJT students for Housekeeping class, 13 OJT students for Catering class, and 17 OJT students for Food Management class with a total of 50 OJT students. In this study, AHP-MAUT and AHP-PM can be used properly and can be implemented into a web-based software which is quite user-friendly to users. Implementation of AHP-MAUT, OJT students from the Food Processing class with the code StudentD04 have the highest preference value of 0.5724, and OJT students from the F&B class with the code StudentA02 have a preference value of 4.1155 calculated using AHP-PM, each being ranked first.
Accuracy in Identifying Rice Plant Diseases UsingMethod Fuzzy Sri Handayani; Gunadi Widi Nurcahyo; Sumijan Sumijan
Jurnal Teknik Informatika C.I.T Medicom Vol 13 No 1 (2021): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol13.2021.59.pp33-41

Abstract

Rice is one of the most favored crops by the Indonesian people, because of its many benefits, especially as a staple food for Indonesians, and is also used as a raw material for the feed and food industry. In particular, rice is processed to produce rice which contains high carbohydrates, so that rice is widely used and used as a human staple food. Some things that often happen at this time by rice farmers, many losses caused by rice plant diseases that are too late to be identified, causing crop failure. In this case, this rice plant disease is still in a mild stage, but many farmers ignore it, so that a bigger and wider problem arises and it is too late to control. The purpose of this study is to assist rice farmers in identifying rice plant diseases, which will use the Tsukamoto fuzzy method and implement it into the system, so that farmers do not feel overwhelmed again in identifying rice plant diseases. In general, Fuzzy can be referred to as uncertain logic but its advantage is that it is capable of the punishment process so that its design does not require complex mathematical equations. There are various fields that can be used by fuzzy logic, one of which is to identify rice plant diseases
Optimization Of Determination Against K-Means Cluster Algorithm Using Elbow Creation Melda Pita Uli Sitompul; Opim Salim Sitompul; Zakarias Situmorang
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.176.pp1-9

Abstract

Clustering is a data mining method for grouping data that have similar or different characters in each section. One of the methods is using K-Means by measuring the distance between clusters using the shortest distance or Euclidean Distance. K-means entails weakness, which is the determination of clusters in k-means clustering, resulting in the different data grouping and affecting the results of the data cluster distribution. To overcome this issue, the elbow creation method is employed to determine the similarity level in the cluster by observing the comparison between Root Means Square and R Square to measure the homogeneity and heterogeneity of the cluster where this method is applied by considering the changes in the comparison between the RMSSTD (Root Means Square Standard Deviation) and RS (R Squared) values which have the intersection of the RMSSTD and RSquared values. The difference between RMSSTD cluster 1 and RMSSTD cluster 2 was 0.066 and RS cluster 1 and RS cluster 2 was -0.304. Based on those figures, the highest difference was found in cluster 2. All considered, tourist destinations in East Asia frequently visited or interested to visitors are grouped into cluster 2, comprising criteria 6, 7, 8, and 10, or in other words, resort destination, picnic area, beaches, and religious institutions
PERAMALAN JUMLAH MAHASISWA BARU DENGAN PENDEKATAN REGRESI LINIER Yulia Utami; Desi Vinsensia; Aura Nissa; Sulastri Sulastri
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.231.pp10-15

Abstract

Forecasting models are the result of developments in the field of science and technology that provide convenience in predicting future events. This paper aims to develop a linear regression model to predict the number of new students in the next year. The data to be used in this study is the total of students majoring in informatics engineering and information management during the last 5 years. Based on result obtained the number of student for department of Informatics Engineering is 198 people with a MAPE (Mean Absolute Percentage Error) score of 16.5%, and for the new students department of Informatic Management is 8 people with a MAPE score of 16.1%.
Implementation of The Naïve Bayes Method in the COVID-19 Self-Assessment of Cianjur Regency Government Officials Muhammad Nasir; Andy Ramadhany Rahayu; I Putu Robin Sunjaya; Mey Sri Widialestari; Agus Prayitno
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.239.pp16-26

Abstract

The impact of Covid-19 in Indonesia has penetrated into all fields of human activity including in the government sector, efforts to implement work from home for government agencies, especially in the Cianjur district to suppress the positive number of COVID-19 have been carried out. However, in practice the determination of employees to work from home is not appropriate, resulting in a decrease in the performance of government employees in Cianjur Regency, and an increase in positive numbers in the government environment. The method used in this research is an expert system approach with Naive Bayes which is the fastest and most accurate classification method for determining the problem. Based on the classification of the Naive Bayes method, samples were taken from Cianjur Regency government employees with symptoms of fever, cough, muscle aches, and loss of sense of smell, they had the highest probability of being classified as unhealthy and eligible for a swab test compared to other classifications, which was 80% percent. An expert system with a naive Bayes approach can be implemented to determine the health status of Cianjur Regency employees related to Covid-19, the suitability of the swab test, and the determination to work from home. For further research, it is suggested that it can be integrated with the existing institution's attendance system, and if necessary it can be tested with other methods.
Implementasi Gain Ratio Pada Metode KNN Dalam Memprediksi Penjualan Sparepart Elektronik Pada Service Center Panasonic Lhokseumawe Samsul Bahri Siagian; Samsudin Samsudin; Muhammad Dedi Irawan
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.242.pp36-47

Abstract

K-Nearest Neighbor is a good classification technique, but judging by previous studies, the accuracy of the KNN performance obtained is still inferior to other methods. in the classification process, if some characteristics are not good it can cause errors in the new classifier. As for this study, the researcher uses the gain ratio method as a parameter to see the correlation between each attribute in the dataset, and the gain ratio serves as a weighting for each attribute so as to produce a dataset. the correct way of classifying data using the KNN method, this study is very suitable for predicting sales of spare parts at the Panasonic Service Center company, where the company experienced a decline in sales, this research is very useful for predicting sales for the following month. The results of this study produce very precise predictions of distance with an accuracy value of 13%, where the comparison of the highest accuracy value is found in the total attribute with an accuracy distance of 13%, while the lowest accuracy difference is obtained in the month and type of sales dataset with 0.08%. the overall accuracy of all datasets increases by 100% with K=3, and K=5 gets 80% accuracy. so this method can be used to make sales predictions to make it easier for the company.
Completion of Multi-Criteria Decision Making Using the Weighted Product Method on the Server Maintenance Vendor Selection System Rini Nuraini; Dedy Alamsyah; Ri Sabti Septarini; Alfry Aristo J Sinlae
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.247.pp27-35

Abstract

For companies that use information systems or websites in their business activities, server maintenance is an important thing. For this reason, the selection of a server maintenance vendor is crucial. Vendor determination usually begins with gathering information and holding a leadership meeting based on the assumptions of the decision maker. But this method is time consuming and less objective. Vendor selection is a multi-criteria problem where each criterion has a different importance. This can be solved by using the Multi-Criteria Decision Making (MCDM) approach. Weighthet Product (WP) is one of the methods of solving MCDM. The purpose of this research is to develop a decision support system to determine the best maintenance vendor using the Weighted Product (WP) method. The system is built using a waterfall system development approach that starts from analysis, design, coding and testing. The developed system has the ability to manage alternatives, criteria, alternative assessments, calculations with WP, and displays the best alternative results with WP. From the results of black-box testing, it shows that the developed system can function and run well. In addition, the results of manual calculations with the system show the same results.

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