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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.
Arjuna Subject : -
Articles 192 Documents
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Prediksi Kelulusan Mata Kuliah Mahasiswa Teknologi Informasi Menggunakan Algoritma K-Nearest Neighbor Ahmad, Nazaruddin; Hafizh, Saifan; Sulthanah, Rana
Jurnal Manajemen Informatika JAMIKA Vol 14 No 2 (2024): 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.v14i2.12454

Abstract

This research aims to develop a predictive model using the K-Nearest Neighbor (KNN) method to forecast the course completion of students in the Information Technology program. The issue at hand is the uncertainty in predicting student success based on historical data and specific attributes. This study focuses on the importance of understanding the factors that influence student success in the Database Management Systems course to provide accurate predictions and help improve student pass rates in this course. The objective of this research is to build a predictive model using the KNN algorithm and to implement this model using the PHP programming language. The study aims to offer valuable insights for educational institutions to enhance teaching and learning processes and to expand understanding of data mining concepts in specific case studies. The prediction aims to determine whether a student will pass or fail the Database Management Systems course based on predetermined training and testing data. By calculating the nearest distance between the training data and the test data. The results showed an accuracy rate of 90% for predicting course completion using k=5, with a dataset consisting of 40 training data points and 20 testing data points.
Implementasi Decision Tree untuk Prediksi Kelahiran Bayi Prematur Rosida, Putri Lailatul; Nurmalasari, Mieke; Hosizah, Hosizah; Krismawati, Dewi
Jurnal Manajemen Informatika JAMIKA Vol 14 No 2 (2024): 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.v14i2.12797

Abstract

The early birth of baby in Indonesia is a case that has a very high incidence rate. According to data from the Ministry of Health in 2021, the presentation of premature babies in Indonesia is 84%. The number of infant deaths in Indonesia is still relatively high compared to other ASEAN countries. The purpose of this study was to predict the birth of premature babies with the implementation of decision tree, with this type of predictive analysis research. The population in this study is pregnant women patients with a sample of 350 pregnant women patient data covering the variables studied Age, BMI, Vaginal Discharge, History of Miscarriage, History of Prematurity and Pregnancy Spacing. The prediction was made by halving the training data by 245 and the testing data by 105. The results obtained are the variable Body Mass Index (BMI) is the riskiest factor for premature birth The decision tree model yields an AUC of 91.7%, it can be concluded that the decision tree has a good classification accuracy value.
Perbandingan Metode Exponential Smoothing dan Moving Average pada Arus Barang Bongkar Almaliki, Muhamad Faza; Isnawaty, Isnawaty; Satyadharma, Maudhy; Hado, Hado
Jurnal Manajemen Informatika JAMIKA Vol 14 No 2 (2024): 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.v14i2.12828

Abstract

In the logistics and distribution sector, an accurate understanding of the patterns of unloaded freight flows is essential for efficient operational planning. In this context, data analysis methods are key to understanding trends, seasonal patterns, and short-term fluctuations in the flow of unloaded goods. The purpose of this research is to understand the difference between Exponential Smoothing and Moving Average forecasting techniques as a more accurate forecasting technique in predicting the volume of unloaded goods flow. The methodology in the data analysis stage in this research consists of four stages, namely data preparation, creating functions, creating GUI, and displaying visualisation results. The conclusion obtained from this research is that the Exponential Smoothing method with an alpha value of 0.9 has results that are close to the actual value that has been determined. This can be seen from the results of the Mean Absolute Error which describes the average absolute prediction error, Mean Squared Error which describes the average of the squares of prediction errors, Mean Absolute Deviation which describes the average prediction error in the same unit as the data and Mean Absolute Percentage Error which describes the average percentage of prediction errors where the resulting values are 388501761.94 for MSE and 2.55 for MAPE values, then for MAE of 14681.39 and for MAD of 14681.39.
Tinjauan Literatur Manajemen Risiko Cyber dalam Proyek: Identifikasi, Evaluasi, dan Mitigasi Ancaman Br Sitorus, Milky Gratia; Maria, Novita; Safa, Yunisa Nur
Jurnal Manajemen Informatika JAMIKA Vol 14 No 2 (2024): 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.v14i2.12887

Abstract

In today's digital era, business projects are increasingly vulnerable to cyber threats, which can result in significant financial and reputational losses. This journal discusses an effective cyber risk management approach for projects, encompassing the identification, evaluation, and mitigation of digital threats. The objective is to provide an overview of risk management in projects. This journal explains how to identify risks by thoroughly analyzing various potential cyber threats, such as malware, phishing, and DDoS attacks that could impact the project. Subsequently, risk evaluation is conducted by assessing the vulnerability and potential impact of each identified threat, using a literature review method. The literature review includes the analysis of data obtained from relevant articles and books on the topic. The final stage involves risk mitigation, which includes developing strategies to reduce or eliminate the impact of threats, such as implementing security controls, providing employee education and training, and developing incident response plans. This study emphasizes the importance of a proactive and holistic approach to cyber risk management to ensure the success and sustainability of projects. The journal aims to provide an overview of risk management in projects, demonstrating that the integration of comprehensive cyber risk management practices can significantly enhance the resilience of projects against digital threats.
Implementasi Machine Learning Untuk Prediksi Harga Laptop Menggunakan Algoritma Regresi Linear Berganda Sari, Noer Nilam; Anisah, Tiyar Tohirotun; Fitriani, Risma
Jurnal Manajemen Informatika JAMIKA Vol 14 No 2 (2024): 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.v14i2.12923

Abstract

This article discusses the implementation of machine learning using multiple linear regression algorithms to predict laptop prices. The main objective of this research is to design an appropriate predictive model based on various features such as technical specifications and laptop brands. The research stages include literature study, collection of relevant datasets, pre-processing or data cleaning, Exploratory Data Analysis, Feature Engineering, data splitting, model building, and website development. The results show that the proposed model is able to provide price predictions with a high level of accuracy, measured using evaluation metrics such as Mean Absolute Error (MAE) which produces a value of 0.18 and R-squared (R²) which has a value of 0.68. Implementation was done by integrating Jupyter Notebook, Visual Studio Code (VS Code) and Streamlit for interactive web application development. The conclusion of this research is that the multiple linear regression algorithm is effective in predicting laptop prices, and can be used as a tool in making business decisions and pricing strategies.
Pengukuran Kualitas Layanan Sistem Informasi Poliklinik (SIPOLINK) dengan Metode Webqual 4.0 Mustopa, Ali; Pratama, Eri Bayu; Nawawi, Hendri Mahmud
Jurnal Manajemen Informatika JAMIKA Vol 14 No 2 (2024): 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.v14i2.12937

Abstract

The Polyclinic Information System (SIPOLINK) is designed to improve the quality of patient service by monitoring medical records more effectively and efficiently at the West Kalimantan Provincial Government Polyclinic. As an agency that handles health problems, the application of SIPOLINK provides significant added value for primary services, especially for users, namely all employees at the Polyclinic. This study aims to assess the quality of the SIPOLINK website services with the goal of improving service delivery to the community. The method used is Webqual 4.0, which includes three variables: usability quality, information quality, and interaction quality. Primary data was collected through a Likert scale questionnaire with 24 statements distributed to 30 respondents. Data analysis was conducted using descriptive statistical methods. The results indicate that interaction quality does not affect user satisfaction, while usability quality and information quality have a significant impact. The quality of SIPOLINK services affects user satisfaction by 87.3%, indicating that improvements in these areas can significantly enhance service delivery to the community.
Penyelarasan Strategi Bisnis dengan Strategi STI untuk Mencapai Tujuan Organisasi Menggunakan Ward and Peppard (Studi Kasus: SD XYZ) Akbar, Ananda Azizul; Maulana, Yoppy Mirza; Wardhanie, Ayouvi Poerna
Jurnal Manajemen Informatika JAMIKA Vol 14 No 2 (2024): 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.v14i2.13239

Abstract

SD XYZ is one of the oldest elementary schools in Gresik Regency which was established in 2010. The application of Information Systems and Technology at the school still does not support its organizational goals, where the Information Technology Systems used have not supported quality education and have not created active, creative and innovative learning. Therefore, this research makes a strategic planning of Information Technology Systems using the Ward and Peppard method or framework with stages such as external internal business analysis, and external internal Information Technology Systems analysis, then alignment is carried out using the Balanced Scorecard and also Critial Success Factors, based on the results of the alignment, it produces 15 application portfolios that are in accordance with the objectives of the organization, there are 2 key operational application portfolios for Quality A, 1 support application portfolio for Quality B, 2 support and 1 strategic for Quality C, 1 strategic, 3 high potential, 1 strategic and 2 support for Quality D, and 1 support for Quality E, and 2 application portfolios to support active, creative, and innovative learning.
Aplikasi Sistem Pakar Dengan Metode Naive Bayes untuk Mendeteksi Penyakit Diabetes Fauzi, Ahmad
Jurnal Manajemen Informatika JAMIKA Vol 15 No 1 (2025): 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.v15i1.12391

Abstract

Data IDF states that there will be 19.47 million people with diabetes in Indonesia in 2021. One of the causes is a lack of awareness of healthy food consumption which has an impact on increasing body weight due to high blood sugar. In overcoming this incident, it is necessary to implement an application to detect diabetes. The use of an expert system provides many conveniences for someone in health examinations and also for health workers or doctors in diagnosing a disease. In diagnosing, an expert system requires a method, one of which is the Naive Bayes classification method. In this study, data on diabetes sufferers was taken from the Kaggle site as training data, with a total of 768 data from nine attributes and one of the attributes as a label. To make it easier to operate the application, only four attributes were used as test samples based on calculating the highest correlation value, namely pregnancy, glucose, BMI and age. Next, the opinion of a health expert, namely a specialist in internal medicine, and calculating the accuracy value of diabetes data using the Naïve Bayes algorithm. The resulting data accuracy value is 79%. Implementation of a web-based expert system application using the PHP programming language and MySQL database. This expert system application aims to detect diabetes based on the results of a health check to predict whether it is positive for diabetes or negative for diabetes.
Array Sorting Algorithm vs Traditional Sorting Algorithm: Memory and Time Efficiency Analysis: Array Sorting Algorithm vs Algoritma Pengurutan Tradisional: Analisis Efisiensi Memori dan Waktu Pujiono, Imam Prayogo; Rachmawanto, Eko Hari; Winarsih, Nurul Anisa Sri
Jurnal Manajemen Informatika JAMIKA Vol 15 No 1 (2025): 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.v15i1.13230

Abstract

The development of information technology has changed various aspects of life, including the way we store and sort data. Data that used to be stored in filing cabinets is now stored in digital form on computers. However, digital data that is not well organised can make it difficult to search and verify. Therefore, data sorting has become very important, and various sorting algorithms have been developed to fulfil this need, such as the Array Sorting Algorithm (ASA), which is claimed to have efficient time complexity and is very competitive when compared to the time complexity of traditional algorithms. This research examines the memory efficiency and computation time between ASA and five traditional sorting algorithms (Bubble Sort, Shell Sort, Merge Sort, Quick Sort, and Heap Sort) using the Java programming language. The research was conducted by utilising random numerical datasets on three different scales (100, 1,000, and 10,000 data) to test the performance of the six algorithms in various scenarios. ASA, which utilises a two-dimensional array structure to manage element frequencies, showed impressive performance in terms of computation time, especially on datasets containing 1,000 and 10,000 data, compared to traditional algorithms that focus more on comparison and recursion methods. The test results confirm that on datasets of 1,000 and 10,000 data, ASA excels in terms of computational speed but loses in terms of memory usage. Therefore, if memory usage is not a major consideration, then ASA is a very suitable sorting algorithm for sorting data of 100 - 10,000. These findings provide important insights for the selection of efficient sorting algorithms based on memory efficiency and computation time on multiple data sizes, which is particularly useful when developing applications using the Java programming language.
Implementasi Metode Prototyping pada Aplikasi Pembelajaran Metode Tikrar Dalam Menghafal Al-Quran Berbasis Android Juarsyah, Muhammad; Ikhwan, Ali; Alda, Muhamad
Jurnal Manajemen Informatika JAMIKA Vol 15 No 1 (2025): 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.v15i1.13423

Abstract

In this modern era, technology is increasingly sophisticated and developing, which can be used to facilitate various learning activities. However, there are several obstacles faced by a person who is in the process of memorizing the Qur'an. One of the problems is not often repeating verses that are being or have been memorized. The purpose of this research is to build a Tikrar Method Learning application that can be used to learn materials about the tikrar memorization method through the features and menus contained in the application. The app can also help in testing memorization with a memorization testing feature that utilizes Google Speech API technology. The type of approach used in this study is a qualitative approach consisting of observation, interviews, and literature studies. And the system development method used is the prototyping method. The software used in building the application consists of the codeular framework, google sheets and google script. The result of this research is an application that applies the tikrar method feature in memorizing the Quran along with the memorization testing feature by applying Google Speech API to the application. The advantage of the tikrar method feature in the application is that it can display notifications regarding whether the verses being memorized can be deposited or not and display notifications regarding whether the verses tested through the application already have the correct tajweed or not based on the readings spoken by the user.

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