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COMPARISON OF MAUT METHOD WITH MABAC IN GIVING EMPLOYEES SALARY BONUS AT PT. ARTA JAYA ELECTRIC
Full text linkTujuan: PT. Arta Jaya Elektrik memiliki karyawan yang setiap bulan diberikan gaji dan setiap 6 bulan diberikan bonus gaji. Dalam proses penentuan bonus karyawan masih menggunakan Microsoft Excel sehingga terkadang terjadi kesalahan dalam proses penginputan data yang akan digunakan untuk penilaian karyawan. Selain itu, dikarenakan harus membuat rekapan data penunjang pemberian bonus karyawan.Perancangan/metode/pendekatan: Perancangan sistem dibuat untuk dapat mengelola data karyawan, data kriteria, data sub-kriteria, data penilaian, data perhitungan, dan data hasil akhir. Pendekatan Metode MAUT dan MABAC digunakan karena ingin melakukan perbandingan untuk memilih metode yang paling tepat dan mudah dalam menentukan bonus gaji karyawan. Hasil: Pengujian perhitungan menggunakan MAUT dan MABAC menghasilkan urutan hasil peringkat yang sama. Namun hasil total perhitungan menunjukan jumlah yang berbeda. Keaslian/ state of the art: Berdasarkan penelitian terdahulu, dalam penelitian ini menggunakan kriteria absensi, keterlambatan, lembur, dan kinerja karyawan dalam melakukan perhitungan metode MAUT dan MABAC untuk mencari hasil akhir perangkingan alternatif
STMIK PalComTech Customer Service Questionnaire Processing Application Design
Full text linkPurpose: The focus of this research is to create a Consumer Service Questionnaire Dashboard application that can perform questionnaire data processing, service satisfaction analysis and reporting the results of service improvement recommendations at STMIK PalComTech.Design/methodology/approach: This study uses the Prototype method, where this method can interact with the user during user creation. This method consists of five stages, namely communication, planning quickly, modeling the design quickly, making prototypes, and submitting the system or software to the user or users to be tested using the black box testing method.Findings/result: The results of this study resulted in an application for processing customer service questionnaires from STMIK PalComTech, to simplify and shorten UPT-PM staff in preparing reports on the results of the questionnaire recap, reporting and distributing the results of the questionnaire recap of the Head of UPT-PM.Originality/value/state of the art: The system testing technique used in this study is black box testing, this testing technique focuses on the functional specifications of the software, this test is also used to find errors in the system, for example interface errors, performance errors, incorrect or missing functions
Classification of Damaged Road Images Using the Convolutional Neural Network Method
Full text linkObjective: Automatic identification is carried out with the help of a tool that can take an image of road conditions and automatically distinguish the types of road damage, the location of road damage in the image and calculate the level of road damage according to the type of road damage.Design/method/approach: Identification of damaged roads usually uses manual RCI system which requires high cost. In this study, a comparison framework is proposed to determine the performance of the image pre-processing model on the image classification algorithm.Results: Based on 733 image data classified using the CNN method from 4 models of pre-processing stages, it can be concluded that training from grayscale images produces the best level of accuracy with a training accuracy value of 88% and validation accuracy reaching 99%.Authenticity/state of the art: Testing of 4 pre-processing models against the classification algorithm used as a comparison resulted in the best algorithm/method for managing road images
Group Decision Support System Using SMART-COPELAND SCORE Model In Choosing The Best Alternative Pair
Full text linkPurpose: Adjust the Group Decision Support System (GDSS) model in completing case studies of selecting the best alternative candidate pairs for the OSIS core board with many decision-makers and problems in the differences in the preferences of decision-makers as well as modeling in decision making with multi-criteria and multi-attributes and combining preferences decision-makers to choose the best alternative partner candidate.Design/methodology/approach: The Group Decision Support System (GDSS) model combines the SMART method for modeling multi-criteria and multi-attribute assessments and the Copeland Score model for aggregating the judgments of five decision-makers against the selected pair of OSIS core board candidates using a voting mechanism.Findings/result: The comparison test for the manual calculation of the SMART- Copeland Score Model method with the results of the system calculation is the same. From the ten alternative data in the first stage of the test through the SMART method calculation, it then passes into four alternatives divided into two alternative candidate pairs, namely alternative candidate pairs (A1, A3) and alternative candidate pairs (A2, A4). The second stage test uses calculations Copeland Score voting, which produces the best alternative candidate pair, namely alternative (A1, A3) with a final point score = 4.Originality/value/state of the art: Based on a review of previous research, this study uses line-up criteria, written tests, and interview tests with the SMART method to calculate alternative scores on each criteria, and the Copeland Score model to aggregate decision makers\u27 preferences to produce the best alternative candidate pairs. In calculating the final value of the alternative ranking
Implementation of ERP in AKIP Evaluation System: A Case Study at The Ministry of Maritime Affairs And Fisheries
Full text linkEvaluasi kinerja pada instansi pemerintah merupakan aktivitas analisis yang sistematis, pemberian nilai, atribut, dan pengenalan permasalahan, serta mempersembahkan solusi atas masalah yang ditemukan guna meningkatkan akuntabilitas dan peningkatan kinerja instansi pemerintah. Untuk pemerintahan di Indonesia, penilaian atas akuntabilitas kinerja merupakan sebuah cerminan organisasi dalam merepresentasikan kinerjanya, sehingga tidak mengherankan jika setiap instansi pemerintah berupaya semaksimal mungkin untuk meningkatkan kinerjanya sesuai dengan kriteria yang ditetapkan oleh tim evaluator. Baru-baru ini, MENPAN RB merevisi evaluasi AKIP ke dalam Peraturan MENPAN RB Nomor 88 Tahun 2021 dengan banyak perubahan yang cukup fundamental. Hal ini berdampak pada perubahan strategi organisasi untuk mengembangkan evaluasi evaluasi guna dapat memprediksi nilai akuntabilitas kinerja dengan bantuan teknologi informasi berbasis ERP, seperti contoh kasus yang terjadi pada Kementerian Kelautan dan Perikanan. Penelitian ini merupakan studi kasus bertujuan untuk mengetahui bagaimana penerapan ERP pada pelaksanaan evaluasi AKIP yang dijalankan oleh Inspektorat Jenderal Kementerian Kelautan dan Perikanan mulai dari dukungan infrastruktur dan jaringan teknologi informasi yang digunakan, tahap perancangan dan pengembangan perangkat lunak, serta implementasinya dapat digunakan pada pelaksanaannya AKIP pada Tahun 2022. seperti contoh kasus yang terjadi pada Kementerian Kelautan dan Perikanan. Penelitian ini merupakan studi kasus bertujuan untuk mengetahui bagaimana penerapan ERP pada pelaksanaan evaluasi AKIP yang dijalankan oleh Inspektorat Jenderal Kementerian Kelautan dan Perikanan mulai dari dukungan infrastruktur dan jaringan teknologi informasi yang digunakan, tahap perancangan dan pengembangan perangkat lunak, serta implementasinya dapat digunakan pada pelaksanaannya AKIP pada Tahun 2022. seperti contoh kasus yang terjadi pada Kementerian Kelautan dan Perikanan. Penelitian ini merupakan studi kasus bertujuan untuk mengetahui bagaimana penerapan ERP pada pelaksanaan evaluasi AKIP yang dijalankan oleh Inspektorat Jenderal Kementerian Kelautan dan Perikanan mulai dari dukungan infrastruktur dan jaringan teknologi informasi yang digunakan, tahap perancangan dan pengembangan perangkat lunak, serta implementasinya dapat digunakan pada pelaksanaannya AKIP pada Tahun 2022
Capability Level Analysis of IT Governance Using COBIT 5 on Continuity and Availability Of Services (Case Study: LMS Spada Wimaya)
Full text linkPurpose: This study aims to assess the capability level to determine the condition of the capability level as-is, to-be, gap analysis and provide recommendations for improving IT governance in the continuity and availability process of LMS Spada Wimaya service. Design/methodology/approach: The capability level assessment refers to the COBIT 5 Process Assessment Model (PAM) assessment criteria with the research stages adopting the COBIT 5 Assessment Process Activities. Findings/result: Based on the urgency and problems that occur in LMS Spada Wimaya related to the continuity of service availability, the appropriate COBIT 5 enterprise goals are chosen, namely Business Service Continuity and Availability which describes in achieving the vision and mission goals of UPN "Veteran" Yogyakarta related to the procurement of LMS Spada Wimaya. The process of mapping results is prioritized based on impact and importance. The results of the assessment of the current capability level (as-is) in the BAI06, DSS03, DSS05, and MEA01 processes are at level 2 with the expected target capability level (to-be) at level 3 with a gap level of 1. DSS01, DSS02, and DSS04 are at level 1 with a target capability level (to-be) expected at level 3 with a gap level of 2. output criteria, setting performance goals and targets, making Standard Operating Procedures (SOP), conducting performance assessments to ensure compliance. Originality/value/state of the art: This study has the same focus as previous research, which is measuring the ability of the IT governance level with the criteria for the COBIT 5 Model Assessment Criteria (PAM), but is implemented in a different case study and the focus of the process is in accordance with the results of mapping the alignment of organizational goals with COBIT 5 IT goals according to urgency and problems that describe in achieving the vision and mission of the object of research
Success Measurement of E-Learning Spada Wimaya at Universitas Pembangunan Nasional “Veteran” Yogyakarta Using Delone and Mclean Model Approach
Full text linkPurpose: This study aims to measure success and determine the factors that support or hinder the success of the e-learning SPADA Wimaya.Method: This study adapts the development of the DeLone and McLean Model 2003. The data used are primary data obtained from the answers of 387 users of the e-learning SPADA Wimaya Pembangunan Nasional “Veteran” Yogyakarta University as respondents in the distributed questionnaire. The results of the questionnaire were processed using SPSS to test descriptive of the data. After that, the data is processed using Structural Equation Modeling (SEM) for testing the inner model and outer model which includes hypothesis testing through SmartPLS software.Result: Of the nine proposed hypotheses, six were accepted and the other three were rejected. Because not all variables affect each other significantly, the e-learning SPADA Wimaya is declared to have not been successful. The factors that hinder the success of the e-learning SPADA Wimaya are the security indicator on the system quality variable, responsive indicator on the service quality variable and communication effectiveness on the net benefit variable
Mask Detection System Using Convolutional Neural Network Method on Surveillance Camera
Full text linkThe Covid-19 has been an epidemic that has taken the world by storm since the beginning of 2020. This Covid-19 outbreak can spread easily through the air. Because Covid-19 can transmit easily, the government implements new behavior based on an adaption to develop a clean and healthy lifestyle which is often called the new normal. One way to live the new normal is to wear a mask when leaving the house. To help increase public awareness in using masks, numerous technology- based studies have been carried out. This article explain an application using the python programming language that applies digital image processing in terms of detecting the use of masks using Deep Learning with the Convolutional Neural Network (CNN) method to classify data that has been labeled using the supervised learning method. In designing this CNN architectural model, a total of 2110 images of people wearing and without wearing masks will be used, this dataset will be divided into 2 parts, with a rate of 8020, where 80 of the dataset will be used as training data, 20 is used as validation data. In testing the model by taking a total of 100 images with a 5050 ratio between face images using masks and not using masks tested using a confusion matrix, it produces 97% of an accuracy rate, 100% of precision rate, and 94% of recall in recognizing facial images that use masks and don\u27t use masks
Customer Loyalty Analysis On Online Travel Agent (OTA) Using American Customer Satisfaction Index (ACSI) And Structural Equation Modelling (SEM)
Full text linkPurpose: Knowing what affects customer loyalty in Online Travel Agent (OTA) Services. Which will help OTA Services to understand about customer satisfaction and customer loyalty so that they can develop their business in the future in order to get greater customer satisfaction and loyalty.Design/methodology/approach: Using the American Customer Satisfaction Index (ACSI) Model which explains the antecedents and consequences of customer satisfaction. In Antecedent there are variables of User Expectations, Perceived Quality, and Value benefits that have an impact on customer satisfaction variables then from causing customer complaints and customer loyalty. So that 9 research hypotheses are obtained based on the model used and tested using Structural Equation Modeling (SEM). Research requires data on respondents\u27 answers distributed through digital media with a total need for 385 respondent data.Findings/result: After testing using SEM.The 9 hypotheses proposed show that 2 hypotheses are rejected and 7 hypotheses are accepted.Originality/value/state of the art: Previous research has been done but with different models and different methods
Detection of Student Drowsiness Using Ensemble Regression Trees in Online Learning During a COVID-19 Pandemic
Full text linkOnline lectures are mandatory to deal with the implementation of education during the COVID-19 pandemic. This significant change certainly creates a different experience for students. Regarding online learning, several public health experts and ophthalmologists say that residual radiation from electronic screens is causing an epidemic of eye fatigue. Research on smart classrooms actually appeared several years ago, but in reality it has not been implemented according to the planned concept. The current smart classroom research environment only uses outdated methods, which make the computer system incongruent (such as decision trees in video feeds) or only to the level of empirical studies or blueprints, which are not much help for other academic footing or reference materials. to students. This study aims to build an intelligent system that can evaluate students\u27 attention during online classes, use teaching videos as learning feeds and input for predictions and also use advanced algorithms in several computational domains, namely face segmentation, landmarking, PERCLOS observations, Yawning and decision analysis using Ensemble Regression Trees to detect students\u27 sleepiness, which is expected to patch up the shortcomings of the PERCLOS algorithm and the problems found in the single regression tree-based implementation. Based on the results of the tests that have been carried out, the system developed has been able to observe sleepy objects in learning videos with an accuracy of 80% so that later it can be a lesson for teachers why there are students who are sleepy during online classes either because of uninteresting material or other reasons