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METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Published by Universitas Methodist Indonesia
ISSN : 25988565     EISSN : 26204339     DOI : 10.46880
Core Subject : Economy, Science,
Computer Science & IT Economics, Econometrics & Finance
Sistem Informasi Sistem Informasi Manajemen Sistem Informasi Akuntansi Manajemen Basis Data Pengembangan Aplikasi Web dan Mobile Sistem Pendukung Keputusan Desain Grafis dan Multimedia Audit Sistem Informasi Topik-topik lain yang Relevan dengan bidang ilmu Manajemen Informatika Topik-topik lain yang Relevan dengan bidang ilmu Kompuerisasi Akuntansi
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 350 Documents
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DETERMINAN KEPUASAN DAN KINERJA PENGGUNA MODUL GLP SAKTI Hari Sugiyanto; Miftahul Hadi; Ria Dewi Ambarwati; Anjahul Khuluq
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 6 No. 2 (2022): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.074 KB) | DOI: 10.46880/jmika.Vol6No2.pp205-214

Abstract

This study aims to analyze the factors that influence user satisfaction and net benefit (user performance) of user GLP module of SAKTI which come from system quality, information quality and service quality. Respondents are from 10 ministries/agencies that have used module GLP of SAKTI web version. Sampling is non-probability sampling (voluntary sampling). The data used came from the questionnaires filled by the respondents and obtained 49 samples. Data analysis used SEM-PLS or Structural Equation Model-Partial Least Square using SmartPLS software. The results showed that system quality, service quality have significant and positive effect on user satisfaction, but information quality has no effect on user satisfaction and user satisfaction has significant and positive effect on net benefit. Keywords: AIS, Govermental Accounting, Modul GLP
PEGELOLAAN DATA DAN HISTORI PENGGUNA UNTUK PENGEMBANGAN SISTEM INFORMASI BERKAH BERSAMA BERBASIS WEBISTE Sefhia Febriana Budiarti; Billy Sabella; Khairul Anwar Hafizd
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 6 No. 2 (2022): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (980.722 KB) | DOI: 10.46880/jmika.Vol6No2.pp226-233

Abstract

The Berkah Bersama Information System is an information system for manage various data of division general and finance, logistics, also production and marketing used in the Berkah Bersama Company. However, there are still some data management that are not yet included in the system and are still carried out computerized but not integrated through Microsoft Excel. Some of these data include data recording, RHPP (Daily Recapitulation of Farmer Maintenance), drug programs, chick in profit and loss, and user history. So, it is necessary to develop so that data management in the system becomes more complex. This research uses an incremental model, ERD (Entity Relationship Diagram), UML (Unified Modelling Language), and uses the CodeIgniter framework. The results of this research are in the form of Data Management and User History for the Development of a Website-Based Berkah Bersama Information System which useful for managing user data and history. System testing is carried out using the Black-Box Testing method, and the system run according to its functions.
TEXT MINING DAN KLASIFIKASI MULTI LABEL MENGGUNAKAN XGBOOST Rimbun Siringoringo; Jamaluddin Jamaluddin; Resianta Perangin-angin
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 6 No. 2 (2022): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (601.925 KB) | DOI: 10.46880/jmika.Vol6No2.pp234-238

Abstract

The conventional classification process is applied to find a single criterion or label. The multi-label classification process is more complex because a large number of labels results in more classes. Another aspect that must be considered in multi-label classification is the existence of mutual dependencies between data labels. In traditional binary classification, classification analysis only aims to determine the label in the text, whether positive or negative. This method is sub-optimal because the relationship between labels cannot be determined. To overcome the weaknesses of these traditional methods, multi-label classification is one of the solutions in data labeling. With multi-label text classification, it allows the existence of many labels in a document and there is a semantic correlation between these labels. This research performs multi-label classification on research article texts using the ensemble classifier approach, namely XGBoost. Classification performance evaluation is based on several metrics criteria of confusion matrix, accuracy, and f1 score. Model evaluation is also carried out by comparing the performance of XGBoost with Logistic Regression. The results of the study using the train test split and cross-validation obtained an average accuracy of training and testing for Regression Logistics of 0.81, and an average f1 score of 0.47. The average accuracy for XGBoost is 0.88, and the average f1 score is 0.78. The results show that the XGBoost classifier model can be applied to produce a good classification performance.
SISTEM PENDUKUNG KEPUTUSAN EVALUASI HASIL BELAJAR SISWA DI SMK PGRI 3 SIDOARJO MENGGUNAKAN METODE FUZZY AHP (ANALYTICAL HIERARCHY PROCESS) Ahmad Husain Abiyyu; Lilis Widayanti
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp158-174

Abstract

Evaluation of student learning outcomes have an important role for teachers in knowing students abilities and in determining how to guide students. However, in its application to vocational high school PGRI 3 Sidoarjo, the teachers have difficulty regarding the assessment system to evaluate students learning outcomes, the difficulty is in the ranking process. Vocational high school 3 Sidoarjo still used the old and manual systems so the result is that the time needed is inefficient time and made the teachers difficult in processing data. The decision support system of students learning result evaluation at vocational high school 3 Sidoarjo using AHP fuzzy method. The goal is to facilitate the teacher in the student ranking process. The process in this system is the admin inputing students data, classes and scores after that the admin determines the value of each criterion and sub-criterion, then the ranking process is based on class. This decision support system's output is the ranking of students' classes. Using the test results from 20 students, the old system and the new system will be compared. As the result, based on 20 students score data, there were incompatible data, the amount of data were 4 data, with a system accuracy rate of 80%. Unsuitable data due to the old system using 2 criterion while the new system using 5 criterion in ranking.
PENGGUNAAN CLOUD COMPUTING DALAM PERANCANGAN APLIKASI MOBILE BERKONSEP GAMIFIKASI BERKEBUN Korbafo, Adrianus Ragil Indrajaya; Nababan, Darsono; Risald, Risald
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp181-187

Abstract

Climate change causes an increase in global temperature, which results in rising sea levels and threatens many cities in the future, including Jakarta. Carbon emissions are the primary cause of climate change, which is difficult to reduce. Forests can act as a natural filter for carbon emissions, but deforestation still occurs for various reasons. The author and their team propose a solution by creating an application called "Eden" that uses gamification to encourage users to develop a habit of planting trees. This application encourages the public to participate in saving the earth from global warming and climate change by planting trees around their homes, which can filter some of the carbon emissions in their environment.
PENGEMBANGAN SISTEM INFORMASI UNTUK ADMINISTRASI LAYANAN SURAT DI KELURAHAN BUMIAJI Suci Cahya Amalia; Yusuf Sulistyo Nugroho
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp188-200

Abstract

One of the various types of written communication tools is a letter, which is divided into official letters and non-official letters. Official letters are used for formal purposes. However, the process of letter administration in Kelurahan Bumiaji, Kabupaten Sragen is still done conventionally, where people who need a letter have to come to the Kelurahan office and queue, which makes the process ineffective. The letter archiving process carried out by the Kelurahan office is also poorly organized. To overcome this problem, in this study, an information system for letter service administration based on a website was created for the Kelurahan Bumiaji office. The method used to develop the system is the software development life cycle (SDLC), with a waterfall process model. The result of this research is the creation of an information system that can assist the community in obtaining the letters needed and assisting in mail services by the Kelurahan Bumiaji. In addition, this information system also displays information such as announcements from Kelurahan and assets owned by the Kelurahan to the public. Black box testing shows that the system can function as it should, and SUS testing obtained an average score of 77.4 and a grade scale B+.
ANALISIS PERBANDINGAN PERFORMA VIRTUALISASI SERVER MENGGUNAKAN VMWARE ESXI, ORACLE VIRTUAL BOX, VMWARE WORKSTATION 16 DAN PROXMOX Ridho Akbar Nuryadin; Ramadhani, Tarisa A.; Karaman, Jamilah; Reza, Muhammad
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp175-180

Abstract

In the era of advancing digitization, server infrastructure plays a key role in the development of applications and web services. To effectively and efficiently manage and develop virtualized servers, server virtualization techniques can be employed. There are several virtualization platforms available, such as VMware Workstation 16, VMware vSphere (ESXi), Oracle VirtualBox, and Proxmox, each with their own strengths and weaknesses. The objective of this research is to analyze the performance of these four virtualization platforms in developing and managing virtualized servers used for web services, taking into consideration response time, throughput, CPU performance, storage performance, and RAM performance. Experimental methods were used to test these four platforms and measure CPU performance, RAM performance, disk performance, throughput, and response time using Moodle benchmark. The data was then analyzed to draw conclusions about the performance of each platform. The research results show that VMware vSphere ESXi and Proxmox have better CPU performance and response time when handling multiple virtual machines, and are more efficient in disk and memory usage compared to VMware Workstation 16 and Oracle VirtualBox. Significant differences in data transfer speed were found among the four platforms. Overall, VMware vSphere ESXi and Proxmox can be considered better choices for running web servers.
PENERAPAN DATA MINING MENGGUNAKAN METODE K-MEANS UNTUK PENENTUAN REWARD PELANGGAN: Studi Kasus: UD. Penyubur Tani Indah, Sari; Larosa, Fati Gratianus Nafiri; Rumapea, Yolanda Y. P.
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp201-207

Abstract

UD. Penyubur Tani is a trading business that sells various kinds of needs for farmers in running their business in agriculture such as fertilizers, pesticides, seeds, and others. UD. Penyubur Tani wants to increase customer loyalty by giving rewards in the form of discounts so that its business is increasingly trusted and increasing, but in giving rewards to customers is still not effective, because UD. Penyubur Tani has difficulty in calculating one by one which customers whose frequency of purchases and total purchase price are most in the category of very loyal and loyal. Therefore, an application is needed to classify customers so that in determining strategies in building loyalty on target. By using the concept of CRM and the K-Means method, the results obtained from data processing are able to group customers who must be prioritized and can determine which customers deserve a reward. From 100 customer data, the K-Means Clustering method succeeded in grouping very loyal criteria by 8%, loyal 34% and potential by 58%.
MODEL BIDIRECTIONAL LSTM UNTUK PEMROSESAN SEKUENSIAL DATA TEKS SPAM Siringoringo, Rimbun; Jamaluddin, Jamaluddin; Perangin-angin, Resianta; Harianja, Eva Julia Gunawati; Lumbantoruan, Gortap; Purba, Eviyanti Novita
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp265-271

Abstract

This study examines the LSTM-based model for processing spam in text data. Spam poses several dangers and risks, both for individuals and organizations. Spam can be a nuisance that hampers both individual and organizational productivity. Much spam contains fraudulent or phishing attempts to obtain sensitive information. Spam detection using deep learning involves the utilization of algorithms and deep neural network models to accurately classify messages as either spam or not spam. Typically, spam detection systems use a combination of these methods to improve the accuracy of identifying spam messages. This study applies the Bi-LSTM deep learning model to sequentially process text (sequencing). The performance of the model is determined based on the loss and accuracy. The data used are the Spam SMS and Spam Email datasets. The test results show that the Bi-LSTM model demonstrates better performance on all tested datasets. Bi-LSTM is able to capture textual patterns from both the context and the text itself, as it can combine information from both directions. The test results prove that the Bi-LSTM model is more effective in text comprehension. So we need to use Snort to maintain network security. Snort is a useful software for observing activity in a computer network. Snort can be used as a lightweight Network Intrusion Detection System (NIDS). Detection is carried out based on the rules that have been described by the administrator in the directory rules contained in the configuration file. Snort can analyze real time alerts, where the mechanism for entering alerts can be in the form of a user syslog, file or through a database. So we can detect attacks on computer networks early.
PENERAPAN METODE NAÏVE BAYES CLASSIFIER PADA SENTIMEN ANALISIS APLIKASI INVESTASI KEUANGAN DIGITAL: Studi Kasus: Bareksa Dan Bibit Girsang, Jhon Vebrianto; Jaya, Indra Kelana; Simanullang, Harlen Gilbert
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp225-230

Abstract

Investing online is a very promising opportunity. There are many online investment enthusiasts who do not understand how to invest online correctly and be able to minimize risk. Lack of public understanding of the investment implementation process can lead to fraud by irresponsible parties. So understanding investing online is very necessary. There are many online investment applications on the Google Play Store, but these investment applications have their own advantages and disadvantages. The objects of research are the applications of Bareksa and Seeds because the news media often report on these applications at the top and selecting an application requires a collection of information obtained from previous user reviews. The method used is the Naïve Bayes Classifier. Based on the results, the classification is divided into 3 (three) sentiments, namely positive, negative and neutral. With a comparison of training data and testing data 70%:30% accuracy in the Bareksa application was obtained 54% and 44% in the seed application.

Page 13 of 35 | Total Record : 350

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