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Julia Jurnal
Published by Universitas An Nuur
ISSN : -     EISSN : 28294459     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Julia menerbitkan naskah terkait Web and Mobile Computing, Image Processing, Intelligent System, Sistem Informasi, Database, DSS, IT Project Management, Sistem Informasi Geografis, Teknologi Informasi, Jaringan dan Keamanan Komputer, Jaringan Sensor Nirkabel, dan lain-lain.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 14 Documents
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COMPUTER NETWORK ANALYSIS USING NETWORK MANAGEMENT SYSTEM AT AN NUUR UNIVERSITY Achmad Rizki Ramadhani; Muhammad Akbar Mustofa; Rahmawan Bagus Trianto
Julia: Jurnal Ilmu Komputer An Nuur Vol. 1 No. 01 (2021): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

During the pandemic, teaching and learning activities have changed. Which originally used the offline format to go online and its combinations. Internet bandwidth usage plays an important role in the success of the teaching and learning process on campus, including at An Nuur University. By using Cacti Network Management System it can be used as a monitoring system to monitor the movement of internet bandwidth whether it meets the needs of the online learning process or not. Internet bandwidth usage is influenced by several factors such as logical topology, physical topology and configuration in computer networks.   Keywords: Internet Bandwidth; Cacti; Network Management System;
GENETIC ALGORITHM FOR FEATURE SELECTION IN NAÏVE BAYES IN LIFE RESISTANCE CLASSIFICATION ON BREAST CANCER PATIENT Dhika Malita; Andri Triyono
Julia: Jurnal Ilmu Komputer An Nuur Vol. 1 No. 01 (2021): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

Breast cancer is the most common cancer in women's suffering and is the second leading cause of death for women (after lung cancer). More than one million cases and nearly 600,000 breast cancer deaths occur worldwide each year. Survival is generally defined as surviving patients over a period of time after the diagnosis of the disease. Accurate predictions about the likelihood of survival of breast cancer patients can allow doctors and healthcare providers to make more informed decisions about patient care. To classify the survival of breast cancer patients can do the utilization of data mining techniques with Naive Bayes algorithm. Naive Bayes is very simple and efficient but very sensitive to the features so from it the selection of the appropriate features is in need because irrelevant features can reduce the level of accuracy. Naive Bayes will work more effectively when combined with some attribute selection procedures such as Genetic Algorithm. In this study the researchers proposed the Genetic Algorithm for Feature Selection on Naive Bayes so as to improve the accuracy of breast cancer survival classification results. In this study using a private dataset breast cancer patients. The results show that Naive Bayes Genetic Algorithm has a higher accuracy of 90% compared to Naive Bayes with 86% accuracy .   Keywords; Breast Cancer, Survival, Classification, Feature Selection, Naive Bayes, Genetic Algorithm
STRATEGIC PLANNING OF MONTHLY DONATION PAYMENT INFORMATION SYSTEM AT SMK AT-THOAT TOROH Agus Susilo Nugroho; Eko Supriyadi
Julia: Jurnal Ilmu Komputer An Nuur Vol. 1 No. 01 (2021): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

The development of a school, has an impact on the development of various services in the school. If school doesn’t improve the services, schools can lose competition, especially for private schools. The same thing happened at SMK At-Thoat Toroh. This Vocational High School, located in Grobogan Regency, Central Java, experiences significant development every year. One of the indicators is the increasing number of new students enrolling to the school. Even though the number of new students is increasing, At-Thoat Toroh Vocational School must still be able to serve the needs of all its students well. One form of this service is the payment of monthly donations. So far, students who will pay monthly contributions have to come to the teacher's office to meet the administration department. This often creates a crowd at the teacher's office door. Apart from being uncomfortable, it's certainly not a good thing in the midst of the current Covid-19 outbreak. In addition, the recording of monthly contributions by the administrative division is still done manually. This often causes disorder and confusion in recording student monthly contributions. Even though this record is very sensitive, because it relates to school finances. To overcome this problem, it is necessary to have a strategic planning of a monthly donation payment information system. This strategic planning uses the waterfall method and SWOT analysis. It aims to facilitate the analysis and process of making a monthly donation payment information system. The result of this research is the formulation of a monthly donation payment information system business strategy.   Keywords: Information System, Strategic Planning, SWOT Analysis, Waterfall
COMPARISON OF SVM, KNN, AND NAIVE BAYES METHOD WITH N-GRAM IN TRAFFIC ACCIDENT CLASSIFICATION Dhika Malita; Andri Triyono
Julia: Jurnal Ilmu Komputer An Nuur Vol. 1 No. 01 (2021): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

Traffic accidents that occur in Indonesia are still relatively high, the information can be easily obtained through social media, one of which is Twitter. The amount of traffic accident information can be processed and classified according to certain categories. Traffic accident data classification is done using SVM, KNN and Naïve Bayes methods using n-gram feature extraction. The results of this study indicate the best accuracy is 87.63 using the KNN method.   Keywords; Traffic Accident, Classification, SVM, KNN, Naïve Bayes, N-Gram
EARLY DETECTION OF DIABETES MELLITUS USING RANDOM FOREST ALGORITHM andri triyono; Rahmawan Bagus Trianto; Dhika Malita Puspita Arum
Julia: Jurnal Ilmu Komputer An Nuur Vol. 1 No. 01 (2021): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

Diabetes mellitus is a deadly disease. Patients with this disease often do not realize that they are improving their diabetes mellitus. It is necessary to do early prevention in order to reduce the sudden death rate of people with diabetes mellitus. In addition, during the COVID-19 pandemic, which increases the risk of death for people with comorbid diabetes mellitus. A system model for the prediction of diabetes mellitus is needed for early diagnosis of this disease. By using machine learning techniques using the Random Forest algorithm and Information Gain can be used to predict diabetes mellitus. This model has a fairly high level of accuracy, which is 98.27%, precision is 97.69% and recall is 98%.   Keywords: Diabetes Mellitus; Random Forest; Information Gain; Machine Learning
Information System Using The Web For Garbage Bank Transactions (A Case Study of TPS 3R Sido Makmur, Sidoharjo, Pacitan) Tamara Maharani; Dhodit Rengga Tisna
Julia: Jurnal Ilmu Komputer An Nuur Vol. 2 No. 02 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

The construction of a web software, is expected to assist users in processing data and obtaining information quickly, precisely and as needed, along with technological developments, especially in the field of information technology This application contains the Garbage Bank Information System at TPS 3R Sido Makmur, Sidoharjo village, Pacitan district. Application is built using HTML, PHP and CSS programming. The database used is MySQL. With this information system, it is expected to be able to handle transactions that run at the waste bank and provide data reports needed by system users, so that the waste bank work process is more effective and efficient. Keywords: Garbage Bank; Information System; PHP; HTML; CSS;
Image Cluster Features Shape and Texture Determinants of Rice Quality Using the K Means Algorithm Eko Supriyadi
Julia: Jurnal Ilmu Komputer An Nuur Vol. 2 No. 02 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

There is a lot of fraud case in the forgery of ricequality by mixing good quality rice with low quality rice for increasing price. To protect the community from counterfeiting, we conduct research to detect the quality of rice which can later help the community to be able to distinguish good and bad quality. This paper presents a low-cost image processing system for assessing the quality of rice. Many factors affect the quality of rice such as grain fragments, non-uniform color, odor and other factors. This study uses procentage of broken rice grains and color uniformity to determine the quality of rice. We propose texture feature with Otsu segementation for determining the number of broken grains and color distribution for specifying the color uniform. The classification results using K Fold validation on the original data show the results of K-Nearest Neighbor have 99.70% accuracy.
Risk Management in Final Semester Exam Information System Using NIST 800-30 Method (Case Study of SMKN 2 Baleendah) Riyan Farismana; Dian Pramadhana
Julia: Jurnal Ilmu Komputer An Nuur Vol. 2 No. 02 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

In the use of information systems and technology, risk is something that must be anticipated. Risks can arise from various things such as information security, fire, hardware damage, etc. that can disrupt the organization's business processes. With the possible emergence of risks in the use of information systems and technology, risk management is needed to facilitate the identification of possible occurrences of these risks. Risk management is the practice of identifying, assessing, controlling and mitigating risks. SMK Negeri 2 Baleendah is a vocational high school that has 5 areas of expertise competence, namely culinary, beauty, fashion, industrial chemistry, and computer network engineering. SMK Negeri 2 Baleendah as an organization engaged in education has implemented online exam information technology. Of course, the application of information technology raises a problem. From these problems, risk management is needed to minimize risk by conducting a risk assessment. NIST 800-30 is a standard document developed by the National Institute of Standards and Technology. NIST 800-30 has two important stages, namely risk assessment and risk mitigation. This research will use the NIST SP 800-30 method as a method that will solve the existing problems. Therefore, a risk assessment was chosen using the NIST SP 800-30 method (Case Study: SMK Negeri 2 Baleendah)
PENGGUNAAN ALGORITMA FP-GROWTH UNTUK MENENTUKAN PAKET PENJUALAN PADA TOKO PERLENGKAPAN KONVEKSI SRI BUSANA andri triyono; Rahmawan Bagus Trianto; Dhika Malita
Julia: Jurnal Ilmu Komputer An Nuur Vol. 2 No. 02 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

Consumers of the Sri Busana convection shop are mostly tailors, both home and convection tailors, which are pretty large, especially in Grobogan district. The increasing number of fashion businesses or tailors in Grobogan district makes data on goods and sales at the sri busana convection shop increase because the sri busana convection shop always strives to meet the needs of tailors or home convection. In overcoming the problem of finding more efficient consumer patterns, an analysis of buying patterns is carried out. Consumer buying patterns were analyzed using Association rules and FP-Growth methods. With this algorithm, the process of determining consumer purchasing patterns consists of 2 product combinations with a support value of 50% and a confidence value of 100%. 3 product combinations with a support value of 40% and a confidence value of 80%. 4 product combinations with a support value of 40% and a confidence value of 80%.
OPTIMIZATION OF PARTICLE SWARM OPTIMIZATION IN NAÏVE BAYES FOR CAESAREAN BIRTH PREDICTION Dhika Malita; Andri Triyono; Eko Supriyadi; Rahmawan Bagus Trianto
Julia: Jurnal Ilmu Komputer An Nuur Vol. 2 No. 02 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

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Abstract

The Maternal Mortality Rate (MMR) in 2017 according to the World Health Organization (WHO) is estimated to reach 296,000 women who die during and after pregnancy or childbirth. Caesarean birth is the last alternative in labor if the mother cannot give birth normally due to certain indications with a high risk, both for the mother and the baby. factors of a mother giving birth by caesarean section, such as placenta previa, hypertension, breech baby, fetal distress, narrow hips, and can also experience bleeding in the mother before the delivery stage. It is hoped that delivery by caesarean method can minimize problems for the baby and mother. Accurate prediction of the condition of the mother's pregnancy can enable d octors, health care providers and mothers to make more informed decisions regarding the management of childbirth. To predict caesarean births, data mining techniques using the Naive Bayes algorithm can be used. Naive Bayes is very simple and efficient but very sensitive to features, therefore the selection of appropriate features is very necessary because irrelevant features can reduce the level of accuracy. Naive Bayes will work more effectively when combined with several attribute selection procedures such as Particle Swarm Optimization. In this study, the researcher proposes a Particle Swarm Optimization algorithm for attribute weighting in Naive Bayes so as to increase the accuracy of Caesarean birth prediction results

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