cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
informatika@unan.ac.id
Phone
+6282241418157
Journal Mail Official
informatika@unan.ac.id
Editorial Address
https://julia.ejournal.unan.ac.id/index.php/1/editorialTeam
Location
Kab. grobogan,
Jawa tengah
INDONESIA
Julia Jurnal
Published by Universitas An Nuur
ISSN : -     EISSN : 28294459     DOI : -
Core Subject : Science,
Computer Science & IT
Julia is an open access journal. Readers may read, download, copy, distribute, print, search, or link to the full text of this article free of charge. All submitted papers will be peer reviewed before being accepted for publication. Authors who wish to submit manuscripts to Julia must follow the norms described in the guidelines.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 27 Documents
 1   2   3 
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v1i01.12

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.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v1i01.13

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%. 
GENETIC ALGORITHM FOR FEATURE SELECTION IN NAÏVE BAYES IN LIFE RESISTANCE CLASSIFICATION ON BREAST CANCER PATIENT Dhika Malita Puspita Arum; Andri Triyono
Julia: Jurnal Ilmu Komputer An Nuur Vol 1 No 01 (2021): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v1i01.14

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 
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 01 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v2i01.15

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; Dhika Malita Puspita Arum; Rahmawan Bagus Trianto
Julia: Jurnal Ilmu Komputer An Nuur Vol 2 No 01 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v2i01.16

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 Puspita Arum; Andri Triyono; Eko Supriyadi; Rahmawan Bagus Trianto
Julia: Jurnal Ilmu Komputer An Nuur Vol 2 No 01 (2022): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v2i01.17

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 
PREDIKSI TINGKAT KELULUSAN MAHASISWA S1 UNIVERSITAS AN NUUR DENGAN METODE  DECISION TREE C4.5 Umar Haji Mussa’id; Agus Susilo Nugroho; Rahmawan Bagus Trianto
Julia: Jurnal Ilmu Komputer An Nuur Vol 4 No 1 (2024): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v4i1.18

Abstract

One of the private universities in Purwodadi is An Nuur Purwodadi University. Many students have graduated from An Nuur Purwodadi University, but there are some students who did not graduate on time. This poses a problem and raises a significant question as to why these students did not graduate on time. A decision tree is a suitable data mining method for this research because it has the advantage of identifying and summarizing patterns in the data. The Decision Tree algorithm has an accuracy of 96.25%. The recall values for each class are 97.37% for the "Late" class and 95.00% for the "On-Time" class. Meanwhile, the precision values for each class are 94.87% for the "Late" class and 97.44% for the "On-Time" class 
ANALYSIS OF SENTIMENT ON TEACHER MARKETPLACE ISSUES USING THE LEXICON AND K-NEAREST NEIGHBOR ALGORITHMS Addien Anaba; Rahmawan Bagus Trianto; Eko Supriyadi
Julia: Jurnal Ilmu Komputer An Nuur Vol 4 No 1 (2024): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v4i1.19

Abstract

The advancement of social media makes it easier for users to express opinions. Twitter has become one of the media that is loved by internet users, users can freely express their thoughts or opinions, apart from that they can also express everything that is being experienced. The busy issue of the Teacher Marketplace initiated by the Minister of Education, Nadiem Makarim, has invited many comments from internet users. Twitter users' tendencies in posting content can be determined by analyzing sentiment. In this research, the Lexicon and K-Nearest Neighbor (KNN) methods are proposed to analyze sentiment towards the education minister's discourse on Twitter social media on the topic of Teacher Marketplace Issue Sentiment by classifying it into positive, neutral and negative. The results of this research show that the accuracy value obtained was 91.70%, precision 90.51%, recall 71.95%. By carrying out this sentiment analysis, it is hoped that the problems contained in the Marketplace Guru topic controversy can be identified, used as input and consideration for further research.
IMPLEMENTASI ALGORITMA APRIORI UNTUK MENCARI POLA TRANSAKSI PENJUALAN PADA TOKO PERTANIAN TOKO BIDSALTANI Muhamad Nuryahya; Andri Triyono; Agus Susilo Nugroho
Julia: Jurnal Ilmu Komputer An Nuur Vol 4 No 1 (2024): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v4i1.20

Abstract

Progress in the industrial sector is currently growing rapidly, especially in medium and upper-class businesses, especially in agricultural shop businesses. Agricultural shops are one of the medium-sized businesses where competition is quite tight, this can be seen from the high consumer demand for fertilizer and agricultural equipment.With the high demand of consumers for agricultural needs as well as intense competition, agricultural shop companies must further improve their business performance in order to be able to face the problems that occur.Bidsal Tani is one of the many agricultural shops in Purwodadi District that sells agricultural necessities, such as chemical fertilizer, compost, plant seeds and all other agricultural necessities, it can be seen that to make a profit as expected.The a priori algorithm is a market basket analysis algorithm used to produce association rules. Association rules can be used to find relationships or cause and effect. The results of the research are that the products frequently purchased by consumers are PHONSKA, NPA, ZA, FASTAC, KOGE, UREA, GANDASIL, FLORAN, SP36, TSP, WUXAL, BAYFOLAN, BLOPATEK, KCL, HYDRASIL AND DECIS products.
Sistem Informasi Pembuatan Aplikasi Berbasis Web  Pada Konveksi ‘Sania Komveksi’ Erika Dwi Saputra; Muhammad Muzammil; Rheimanda Devin Emmanuel; Agus Susilo Nugroho; Eko Supriyadi
Julia: Jurnal Ilmu Komputer An Nuur Vol 5 No 1 (2025): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v5i1.21

Abstract

Perkembangan teknologi informasi yang pesat telah mempengaruhi berbagai sektor bisnis, termasuk industri konveksi. Sistem informasi berbasis web kini menjadi solusi efektif untuk meningkatkan efisiensi operasional dan manajemen data. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sebuah aplikasi berbasis web pada konveksi ‘Sania Konveksi’ yang dapat membantu dalam pengelolaan data produksi, pemesanan, inventaris, serta pelaporan secara lebih terstruktur dan real-time. Aplikasi ini dibangun dengan menggunakan metode pengembangan perangkat lunak Waterfall, dimulai dari tahap analisis kebutuhan, desain sistem, implementasi, sampai dengan pengujian. Hasil penelitian ini adalah sebuah aplikasi berbasis web yang mampu mengintegrasikan berbagai proses bisnis pada konveksi, memudahkan pihak manajemen dalam memonitor kinerja operasional, serta meningkatkan efisiensi dalam pengelolaan data dan proses produksi. Berdasarkan hasil pengujian, sistem ini terbukti dapat memberikan kemudahan dan efisiensi dalam pengelolaan operasional konveksi ‘Sania Konveksi’

Page 2 of 3 | Total Record : 27

 1   2   3 

Filter by Year

2021 2025


Reset
Filter By Issues
All Issue Vol 5 No 2 (2025): julia.ejournal.unan.ac.id Vol 5 No 1 (2025): Julia Jurnal Vol 4 No 1 (2024): Julia Jurnal Vol 3 No 1 (2023): Julia Jurnal Vol 2 No 01 (2022): Julia Jurnal Vol 1 No 01 (2021): Julia Jurnal