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Jurnal Manajemen Informatika
Published by Universitas Komputer Indonesia
ISSN : 20884125     EISSN : 26556960     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Manajemen Informatika, merupakan kumpulan dari jurnal, artikel, gagasan, ide, konsep, teori maupun hasil penelitian dari berbagai bidang yang berkaitan dengan teknologi informasi yang merupakan karya dari para staf pengajar di lingkungan Universitas Komputer Indonesia dan Perguruan Tinggi Lainnya. Buku ini dapat dijadikan media informasi atau referensi ilmu yang ada kaitannya dengan teknologi informasi.
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Articles 192 Documents
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Implementasi Bidirectional LSTM untuk Analisis Sentimen Terhadap Layanan Grab Indonesia Dloifur Rohman Alghifari; Mohammad Edi; Lutfi Firmansyah
Jurnal Manajemen Informatika (JAMIKA) Vol 12 No 2 (2022): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v12i2.7764

Abstract

Grab Indonesia is one of the leading online motorcycle taxi companies in Indonesia and has a large number of customers in Indonesia. The level of customer satisfaction varies with the services provided, so there must be suggestions and complaints from customers. Sentiment analysis can be used as a solution to determine the level of service satisfaction in order to improve the system and service. This study aims to determine the level of satisfaction of Grab Indonesia users through the Grab application in the Playstore. One of the approaches that can be used is LSTM. LSTM is an RNN algorithm development to solve the vanishing gradient problem. LSTM has the disadvantage of only running can only capture information from one direction. Bidirectional LSTM (BiLSTM) is an LSTM method that has been developed, where BiLSTM can capture information from two directions. In this BiLSTM method, the more data, the better the algorithm's performance. The test results show that BiLSTM is more reliable than LSTM in the case of sentiment analysis on the Indonesian Grab service. BiLSTM produces the best accuracy of 91% and training loss of 28%. Suggestions for future research can produce more and varied word representations by considering the word embedding combinations.
Digital Transformation Planning Based on Big Data Technology (Case Study: XYZ Bank) Raya Agung Astri Wardhani; Gunawan Wang
Jurnal Manajemen Informatika (JAMIKA) Vol 12 No 2 (2022): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v12i2.7876

Abstract

Bank XYZ is one of the regional government-owned banks which as of August 16, 2021 has a total percentage of customers who have dormant accounts reached 50.43%. This happens because currently the development of the marketing strategy used by Bank XYZ is still based on the products and services owned by Bank XYZ, not referring to customer needs. For this reason, the purpose of this research is to make a digital transformation plan that can be used by Bank XYZ in order to become a customer-centric bank using Big Data technology. The method used to carry out this research is to use the Big Data Framework for Agile Business (BDFAB). The results of this study includes mapping data requirements and Big Data technology for Bank XYZ, the impact to business processes, proposals for changes in information system architecture, planning for quality control mechanisms, to changes in organizational structure so that the benefits obtained by Bank XYZ are a more personalized marketing approach to customers, increased accuracy in offering bank products and services based on customer profiles, needs, behavior, and interests, as well as increased customer engagement and customer satisfaction.
Peningkatan Ketersediaan Darah Sesuai Segmentasi Umur Menggunakan K-Means Clustering Titania Dwi Andini; Lia Farokhah
Jurnal Manajemen Informatika (JAMIKA) Vol 12 No 2 (2022): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v12i2.7897

Abstract

Availability of blood at blood banks in Malang city fluctuates unevenly every month and every year. This greatly affects the demand for blood which is very high every day, especially during the current pandemic. To meet the high demand for blood, a program is needed that aims to attract Malang city residents, especially the productive age segment to donate blood so that the availability of blood every month can be met. This study aims to look at blood stock data from BPS (Central Statistics Agency) Malang City every month for three years (2018-2020) which will be clustered / grouped using K-Means method according to the productive age segmentation (17, 18-24, 25-44, 45-59 years) so that it will produce information when there will be an increase in blood donor raising program according to age segmentation by maximizing the month that is the favorite month of the age segmentation and the month that is quiet for donors. This research resulted in cluster groups based on months with analysis on the best number of clusters so that the evaluation resulted in knowledge that the highest month with many donors was October, while the lowest month with few donors was June and December. The government of Malang and related parties can make a program to increase and maximize the blood donor program in that month.
Analisis Kualitas Layanan My Pertamina Menggunakan Pendekatan e-GovQual pada Beberapa Kota Percobaan Nina Kurnia Hikmawati
Jurnal Manajemen Informatika (JAMIKA) Vol 12 No 2 (2022): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v12i2.7977

Abstract

My Pertamina is an e-government application, launched as a loyalty and e-payment program that is expected to implement cashless transactions. In addition, My Pertamina is used to sell subsidized fuel so that it is right on target. Apparently this is still being discussed by various parties. The quality of this application, needs to be analyzed from the responses of users in the 11 cities of the trial district phase 1. The dataset used is responses from 100 users who were collected through a questionnaire. The method used to analyze service quality and determine the influencing variables is e-GovQual then validity and reliability testing is carried out with each result being 100% and 94.6%, which means that the questionnaire formed is valid and reliable to be used in this study. The analysis carried out on the results of filling out the questionnaire using multiple linear analysis with the results of the coefficient of determination shows that the dependent variable (Y) can be influenced by the independent variable (X) by 97.7%, while the remaining 2.3%. As for the correlation value of 0.989 or 98.9%, this means that there is a very strong influence between the quality of My Pertamina's services on user satisfaction. In addition, the results of hypothesis testing show that all hypotheses can be accepted because they have a positive and significant effect. Thus, the quality of Mypertamina's services can be maintained to support the government's program.
Prediksi Kualitas Air Menggunakan Metode Seasonal Autoregressive Integrated Moving Average (SARIMA) Ayunita Agustin; Faisal Fajri Rahani; Fitri Indra Indikawati
Jurnal Manajemen Informatika (JAMIKA) Vol 12 No 2 (2022): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v12i2.8022

Abstract

Water conservation is very necessary to support the creation of clean water quality that is free from harmful substances that can disturb the environment. So a system is needed to monitor water quality to determine the level of pollution that occurs. This system will work to see water quality in real time with several quality parameters such as pH, temperature, and water turbidity. The purpose of this research is to produce a predictive model and find out the prediction results of a data mining-based system. The method used to predict water quality uses the Seasonal Autoregressive Integrated Moving Average (SARIMA) method, because the water quality data is thought to contain seasonal patterns. The results of this study indicate that the SARIMA model can be applied to the dataset used and obtain the accuracy of the forecasting results on each of the tested parameter data. The results of water quality forecasting with this parameter are the result data for testing at a dataset of a depth of 30 cm and a depth of 60 cm for temperature parameters, namely MSE<0.1, and RMSE<0.02. For pH parameters, MSE<0.1, and RMSE<0.1. As well as the turbidity parameter, the results of MSE<0.02, and RMSE<0.13. From these results indicate that this system can predict water quality with past data.
Survei Penilaian Mahasiswa pada Penentuan Sistem Pembelajaran Terbaik Setelah Pembelajaran Online Selama Covid 19 Nailis Sa'adah; Taufik Hidayat
Jurnal Manajemen Informatika (JAMIKA) Vol 12 No 2 (2022): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v12i2.8093

Abstract

The Covid-19 pandemic began to hit Indonesia since 2020. As a result of the pandemic, almost all aspects and areas of life have been affected. One of them is in the field of education. The government enforces online learning for all levels of education, including universities. There are many differences that are felt by students when participating in online learning. This study aims to determine student assessments in deciding the best learning system after online learning was implemented during the COVID-19 pandemic based on learning quality criteria and learning outcomes. The survey involved 43 student respondents. The research was conducted by applying the descriptive method. Data analysis of survey results was carried out using the Analytic Hierarchy Process (AHP) method. The results showed that the learning outcomes criteria had a higher weight, namely 36.92% compared to the learning quality criteria of 33.86% with a consistency ratio of <10% so that they had a good consistent level. The best alternative learning system is the offline learning system which has a weight of 66.42% while the online learning system has a weight of 33.58%. Overall, the AHP method succeeded in producing a fairly good consistency score in determining the best learning system based on the data from the student assessment survey.
Sistem Prediksi Kebutuhan Vitamin A Menggunakan Metode Fuzzy Mamdani Sri Nurhayati; Deden Supriadi; Tati Harihayati M
Jurnal Manajemen Informatika JAMIKA Vol 13 No 1 (2023): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v13i1.8147

Abstract

The purpose of this study is to create a system that can predict the need for vitamin A in a certain period, and provide convenience to related parties to meet the needs of the vitamin. Vitamin A is the most essential nutrient, this is because food consumption is not sufficient and is still low so it must be met from the outside. In this study, the method used to predict the need for vitamin A is the fuzzy mamdani method with input variables namely stock and demand and output variables namely needs. The predictions made are based on past statistics and on the basis of the characteristics of past vitamin A consumption. To calculate the error in predicting using the mean absolute percentage error (MAPE). Analysis of system requirements built using an object approach with Unified Modeling Language (UML) tools. The results of the overall prediction obtained the highest average accuracy value of 97.93% with an average error value as small as 2.07% while the lowest average accuracy value was 92.57% with an average error value as small as 7.43%. Testing on the system obtained a 100% functional value that went well in accordance with the needs analysis that had been made, so that the system had provided predictive information on vitamin A needs for a certain period and provided convenience for related parties to fulfill these needs.
Pengembangan Aplikasi Pengolahan Data Siswa Berbasis Android Menggunakan Metode Prototyping Muhamad Alda
Jurnal Manajemen Informatika JAMIKA Vol 13 No 1 (2023): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v13i1.8216

Abstract

Tritech Vocational School is one of the vocational high schools that, in the process of storing and processing student data, uses the Microsoft Excel application, so that the processing of student data is still considered less effective and efficient. This is due to the difficulty of distributing student data to those who need it; in addition, student data is only stored on a certain computer device, resulting in a lack of security, completeness, loss, or damage to data because it can be accessed by unauthorized parties and can also result in data loss if the computer device is damaged. The purpose of this research is to create an Android-based application that Tritech Vocational High School can use to process student data and make it easier to distribute student data. Prototyping is the systems development approach used in this study. includes stages of requirement communication, quick planning, quick design modeling, construction of a prototype and deployment, delivery, and feedback, while the system testing method uses the black box testing method. Android applications are built using the Kodular Framework and the Airtable database. Via an Android device and accessible online, the application developed helps Tritech Vocational Schools process student data, such as adding, changing, or deleting, and facilitate the distribution of student data. Processing student data using an Android-based application has higher security than using the Microsoft Excel application because it provides restrictions on access rights.
Implementasi Metode Mesin Rekomendasi User Based Filtering pada Sistem Penyewaan Alat Pertambangan Muhamad Faza Almaliki; Ika Purwanti Ningrum; Rizal Adi Saputra
Jurnal Manajemen Informatika JAMIKA Vol 13 No 1 (2023): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v13i1.8459

Abstract

The problem with most mining companies is a lack of information on the availability of ready-to-use (purchase or rent) heavy equipment and information on providers of heavy equipment spare parts, heavy equipment owners who have difficulty finding a market to sell or rent their equipment. Transaction processes that have been taking place so far have used telephone lines, chats and person-to-person emails where this is felt to be less effective and efficient. This research methodology contains stages regarding the process and procedure of data collection, method analysis procedures, system development procedures as well as the time and place of research. The purpose of this study is to implement the user based filtering recommendation machine method on mining equipment rental systems. The results of the study show that the recommendation system that has been built has succeeded in providing appropriate recommendations to customers who have made mining equipment rental transactions based on the parameters of the results of the recommendation accuracy test. The algorithm of the user based filtering recommendation engine method can be applied to the mining tool recommendation system that has been built. Based on testing the accuracy of the recommendation values, each value obtained in the calculation of the Mean Absolute Error (MAE) is 0.00936 so that the resulting recommendation accuracy is 99.99%. Then for the value of the Mean Absolute Percentage Error (MAPE) obtained a value of 27.84%, and for the value of the Mean Squared Error (MSE) obtained was 0.01702.
Analisis Knowledge Management Menggunakan Model Big Data di Media Sosial UMKM Prima Yulianti; Rahmi Fahmy; Hafiz Rahman; Harif Amali Rivai
Jurnal Manajemen Informatika JAMIKA Vol 13 No 1 (2023): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v13i1.8682

Abstract

Social media overcomes the limitations of technology and knowledge management. Previous generations of knowledge management were very rigid, often leaving companies stuck and overly reliant on outdated or obsolete knowledge. Lack of skills in the use of social media, lack of awareness of the value of knowledge management, availability of time to invest both in the acquisition of digital skills as well as in the creation and duration of content, creates perceived barriers to social media uptake. Through a concise and relevant knowledge management process, and utilizing the use of social media, MSMEs can display and communicate messages, products or services, images, and most importantly uniqueness which is their selling point. The purpose of this study is to conceptualize the use of social media in an effort to improve the performance of MSMEs in terms of the perspective of knowledge management-based human resource management with the model of big data for SME approach. The method used is a relevant literature review from 2018 to 2022. The results show that the importance of using social media and knowledge management through big data has a synergistic relationship. Shows that the use of strategic data, representation of knowledge-guided business planning, is a solution for MSMEs in implementing technology through the construction of new knowledge as a tool to encourage innovation and productivity in order to increase business competitiveness and its impact on MSME performance.

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