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All Journal Proceedings of KNASTIK Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknologi Informasi dan Ilmu Komputer Telematika JUITA : Jurnal Informatika Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Jurnal Eksplora Informatika Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal EDUMATIC: Jurnal Pendidikan Informatika Jurnal Abdi Insani Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Pendidikan dan Teknologi Indonesia Jurnal Pengabdian Masyarakat Indonesia JUSTIN (Jurnal Sistem dan Teknologi Informasi) Pamasa: Jurnal Pengabdian kepada Masyarakat Journal of Electronics Technology Exploration (JOeTEx) Mengabdi: Jurnal Hasil Kegiatan Bersama Masyarakat Journal of Industrial and Mechanical Engineering Journal of Current Research in Blockchain
Lasmedi Afuan
Informatika, Fakultas Teknik, Universitas Jenderal Soedirman, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : Jurnal Teknik Informatika (JUTIF)

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APLIKASI PENGELOLAAN KERJASAMA PEMBUATAN PROJEK PADA DINAS KOMUNIKASI DAN INFORMATIKA BANYUMAS Irfan Agus Tiawan; Lasmedi Afuan
Jurnal Teknik Informatika (Jutif) Vol. 1 No. 1 (2020): JUTIF Volume 1, Number 1, June 2020
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2020.1.1.10

Abstract

Penelitian ini mengembangkan sebuah aplikasi berbasis web. Aplikasi yang dikembangkan membantu Dinas Komunikasi dan Informatika (DINKOMINFO) Banyumas dalam pencatatan, pengarsipan, dan penyediaan informasi. Tujuan utama pengembangan aplikasi adalah untuk menjembatani antara developer dengan instansi daerah dalam proses kerja sama pembutan projek. Ada tiga tahapan yang dilakukan dalam pengembangan aplikasi yaitu tahapan pengumpulan data, tahapan analisis kebutuhan aplikasi, dan tahapan pengembangan aplikasi. Untuk tahapan pengumpulan data dilakukan dengan menggunakan metode wawancara dan observasi. Pengembangan aplikasi menggunakan metode pengembangan perangkat lunak Kanban. Aplikasi diimplementasikan menggunakan framework Laravel dengan bahasa pemrograman PHP. Untuk pengelolaan basisdata, aplikasi menggunakan Database Management System (DBMS) MySQL. Aplikasi yang telah dikembangakan dapat digunakan untuk menjembatani antara DINKOMINFO, instansi, dan developer dalam proses kerja sama pembuatan projek dengan memanfaatkan peran teknologi yang berbasis website.
DEVELOPMENT OF BUSINESS INCUBATOR MANAGEMENT INFORMATION SYSTEM AT UNSOED BUSINESS INCUBATOR CENTER lasmedi afuan; Arief Kelik Nugroho; Muhammad Randy Cahya Mardika
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 2 (2022): JUTIF Volume 3, Number 2, April 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.2.180

Abstract

The Unsoed Business Incubator Center (PIB) is one of the incubation centers under the General Sudirman University Community Service Institute. PIB Unsoed aims to help develop the businesses of MSMEs and Startups around the Jenderal Sudirman University area. In the incubation process, of course, there is a lot of data recording related to the tenant incubation process, such as administrative data, data development, data assistance, and other data related to the tenant incubation process. The process of recording data on PIB Unsoed is still done manually without any technological aids such as computers or cellphones. In addition, at PIB Unsoed, there are often cases of data loss regarding the business incubation process that has taken place at PIB Unsoed. From the background of the problem above, the author wants to create a Business Incubator Assistance Management Information System for PIB Unsoed. This system is based on a website using the Laravel framework and developed using a prototyping development method. The results of the research that has been done can be concluded that the Management Information System for managing the Business Incubator can be implemented at PIB UNSOED.
DESIGN AND BUILD A CAREER CENTER INFORMATION SYSTEM USING THE CODEIGNITER FRAMEWORK CASE STUDY AT UNIVERSITAS JENDERAL SOEDIRMAN USING WATERFALL METHOD Muhammad Fikri Rivaldi; Lasmedi Afuan; Arief Kelik Nugroho
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 3 (2022): JUTIF Volume 3, Number 3, June 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.3.322

Abstract

Universitas Jenderal Soedirman annually graduates thousands of qualified students. With so many graduates being issued, it is not uncommon for alumni to be confused about getting information about the world of work. Based on these problems, we need a place that accommodates all of them, namely the Career Center. Universitas Jenderal Soedirman has its own Career Center called Sudirman Career Center (SCC), which accommodating alumni to develop their careers. To do it all, SCC requires a computerized system that can help facilitate SCC in managing alumni data. This research aims to design a system that can make it easier for students, primarily alumni of Universitas Jenderal Soedirman, to find job vacancies and make it easier for agencies to manage their companies in the workforce. The data collection method used in this research is literature study, observation, and interviews, while the method for system development uses waterfall. The system design is done using UML. The programming language used is PHP combined with the Codeigniter framework and MySQL DBMS for data storage. From the research results, it can be concluded that alumni can use the existence of a web-based career center information system to obtain job vacancies information. Moreover, as a medium for the publication of each alumni's profile, it is easier for the SCC to manage alumni data and be helpful for agencies that need workers with various alumni backgrounds.
“IMPROVING GRADE 6 LEARNING OUTCOMES USING LEARNING MEDIA INFORMATION SYSTEM (CASE STUDY OF KRISTEN PENABUR WACANA ELEMENTARY SCHOOL PURWOREJO)" Victoria Angela Sugianto; Lasmedi Afuan; Nur Chasanah
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.391

Abstract

The Covid-19 pandemic that has entered since March 2020, requires every sector to carry out all their activities online. One of them is in the field of education. SD Kristen Penabur Wacana is having difficulty providing additional classes or enrichment to grade 6 students. Due to the Covid-19 pandemic, students are learning online. Parents of grade 6 students admit that it is difficult to find additional material and teach it to their children. The school also does not have a learning system that can facilitate students in online learning. To overcome the existing problems, the researcher created an information system entitled “Sistem Informasi Media Pembelajaran Untuk Meningkatkan Hasil Pembelajaran Kelas 6 Sekolah Dasar (Studi Kasus SD Kristen Penabur Wacana Purworejo)”This system was created to make it easier for schools to provide additional classes or online enrichment. The development method used in this research is the Waterfall method. This system is built using the Codeigniter framework. Testing on this system shows that there are no failures in each module's functionality, so that this system is in accordance with user needs. With the information system built, it can make it easier for the school to provide additional classes or enrichment and to improve the learning outcomes of grade 6 students.
ANALYSIS AND DESIGN OF DATA WAREHOUSE BASED ON SNDIKTI USING DATA WAREHOUSE LIFE CYCLE METHOD AT UNSOED ENGINEERING FACULTY Nurul Hidayat; Dadang Iskandar; Lasmedi Afuan; Arief Kelik Nugroho; Nandha Arwiansyah
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 3 (2022): JUTIF Volume 3, Number 3, June 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.3.514

Abstract

The National Standard for Higher Education (Standar Nasional Pendidikan Tinggi or SNDIKTI) is a standard unit that includes the National Education Standards, plus the Research Standards, and Community Service Standards. Based on the policy in the Regulation of the Minister of Education and Culture (Peraturan Menteri Pendidikan dan Kebudayaan or Permendikbud) No. 3 of 2020 regarding SNDIKTI, Jenderal Soedirman University (Unsoed) Architecture needs to prepare data/ information for analysis based on SNDIKTI 2020. The data is obtained from several internal systems and manual recapitulation within a predetermined period of time. Currently the architecture already has many information systems, but it is still difficult to manage the existing data. So it is important for the architecture to have an important repository to minimize human errors and data inconsistencies. So to perform complex data management, a data warehouse is needed. In this study, the data warehouse design uses the Data Warehouse Life Cycle (DWLC) method with the data warehouse model used is the star schema model. The results of the data warehousing process are in the form of a dashboard, Online Analytical Processing (OLAP), and reports intended for the executives of the Unsoed Faculty of Engineering. The output is presented using a BI (Business Intelligence) tool called Knowage.
WEBSITE BASED EMPLOYEE ACCEPTANCE INFORMATION SYSTEM AT PT NOTO TEKNOLOGI INDONESIA lasmedi afuan; Nurul Hidayat; Bangun Wijayanto; Indah Cahya Febriani
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.524

Abstract

The development of information technology is currently growing very rapidly, many companies want to improve their work processes by using information systems to process company data more quickly and efficiently. The process of accepting prospective employees at PT Noto Teknologi Indonesia is still done manually, i.e. prospective employees must register and deliver job application files to the office. To find out the results of the selection of employee recruitment, prospective employees still get information via WhatsApp. This makes the acceptance of new employee candidates less effective and efficient because it will take a lot of time and the possibility of data errors. So in this study a website based recruitment information system was created to facilitate the process of accepting new employees. The method used in making this system is the waterfall method where this method has 5 stages, namely user needs analysis, system design, implementation, testing and maintenance by PT Noto Teknologi Indonesia. The results of the black-box test show valid results for all features which indicate that this system is as expected. From the results of black-box testing, it can be concluded that this system is feasible to use as a tool to facilitate the process of accepting new employees at PT Noto Teknologi Indonesia.
OPTIMIZATION OF THE K-NEAREST NEIGHBORS ALGORITHM USING THE ELBOW METHOD ON STROKE PREDICTION Febri Sutomo; Daffa Ammar Muaafii; Daffa Naufaldi Al Rasyid; Yogiek Indra Kurniawan; Lasmedi Afuan; Teguh Cahyono; Eddy Maryanto; Dadang Iskandar
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 1 (2023): JUTIF Volume 4, Number 1, February 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.1.839

Abstract

Stroke is the second most deadly disease in the world according to WHO. The sufferer has an injury to the nervous system. Because of this, health experts, especially in the field of nursing, need special attention. Technological advances continue to change over time so that information needs are needed in life. Currently the data on stroke sufferers is extensive enough so that adequate information presentation techniques are needed so that the information received is very accurate and in accordance with user needs. Therefore, it is necessary to process data mining on stroke patient data to obtain useful information for users. This study aims to prove the performance of the Elbow Method to produce the optimum k value in the stroke prediction data using the K-Nearest Neighbors (KNN) algorithm. The optimum k value is generated from the Elbow Method which is executed with the Google Collaboratory using the Python programming language. The test results show that the Elbow Method produces the optimum k value at k = 7. The KNN model that uses the optimum k value from the Elbow Method can increase the accuracy and precision values ​​reaching 6% and 0.12, respectively.
IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION IN K-NEAREST NEIGHBOR ALGORITHM AS OPTIMIZATION HEPATITIS C CLASSIFICATION Susi Setianingsih; Maria Ulfa Chasanah; Yogiek Indra Kurniawan; Lasmedi Afuan
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.2.980

Abstract

Hepatitis has become a public health problem that is generally caused by infection with the hepatitis virus. One type of hepatitis caused by a virus is Hepatitis C. This disease can cause patients to experience inflammation of the liver. In the worst conditions, it can even lead to death. Initial predictions need to be made to increase the awareness of each individual against the threat of Hepatitis C by using the K-Nearest Neighbor method. K-Nearest Neighbor is a classification method that can give a pretty good percentage result in classifying, especially when using large training data. However, K-Nearest Neighbor still has a weakness, namely the determination of the value of K that is less precise so that it can reduce classification performance. To overcome these shortcomings, the researchers used the implementation of Particle Swarm Optimization on K-Nearest Neighbor to find the optimal K value. The existence of this implementation is expected to be able to increase the value of accuracy in classification and overcome solutions to weaknesses in the K-Nearest Neighbor algorithm. From the results of the K-Nearest Neighbor test, the accuracy value is 97.24% at K=5 and K=3. As for the results of testing the implementation of Particle Swarm Optimization on the K-Nearest Neighbor, there was an increase in the accuracy value of 2.07% to 99.31%. This test shows that the implementation of PSO can overcome the shortcomings of KNN and this model can be used as the best solution to determine the classification of Hepatitis C disease.
IMPLEMENTATION OF AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) METHOD FOR PT XL AXIATA TBK STOCK PRICE PREDICTION WITH WEBSITE-BASED DASHBOARD VISUALIZATION Alawiyah, Tuti; Permadi, Ipung; Afuan, Lasmedi; Maryanto, Eddy; Rahayu, Swahesti Puspita
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2700

Abstract

The financial market is a dynamic and uncertain sector, with stocks being one of the most commonly used investment instruments. PT XL Axiata Tbk, a telecommunications company listed on the Indonesia Stock Exchange as a blue chip stock, attracts the attention of many investors due to its financial stability and consistent performance. Technical analysis, particularly the ARIMA (Autoregressive Integrated Moving Average) method is used to predict prices. This research focuses on the use of the ARIMA method in predicting the closing price of PT XL Axiata Tbk shares and the implementation of visualization of prediction results through a web-based dashboard. The results of the analysis obtained the best model for stock prediction is ARIMA (2,1,2) with RMSE and MAPE are 50.743 and 0.01653, respectively. The closing price prediction results for 10 consecutive days are 2,190; 2,194; 2,193; 2,196; 2,194; 2,197; 2,195; 2,197; 2,195; and 2,197. Visualization for the results of this prediction is based on a website with the Streamlit framework that presents the results of stock prediction analysis. The existence of a website-based dashboard visualization can help readers find out the prediction results easily and interactively.
CORRELATION ANALYSIS OF SENTIMENT OF 2024 ELECTION RESULTS AND STOCK MOVEMENTS OF POLITICAL ACTORS IN INDONESIA Sari, Enjelita; Afuan, Lasmedi; Permadi, Ipung; Maryanto, Eddy; Rahayu, Swahesti Puspita
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2701

Abstract

General elections (elections) are one of the crucial moments in the political life of a country, where the public democratically elects leaders and their deputies to manage the government. Public sentiment towards the results of elections significantly impacts the political stability and economic conditions of a country. This research aims to analyze the relationship between public sentiment towards the 2024 General Elections in Indonesia and changes in the stock prices of political actors using technological approaches and data analysis. The Long Short-Term Memory (LSTM) method is used to classify sentiment based on Twitter data collected with Harvest Tweet. Evaluation of the LSTM model shows an accuracy rate of 90%, precision of 93.6%, and recall of 92.7%. The correlation analysis using the Spearman coefficient indicates a significant negative relationship with a coefficient of 0.402 and a p-value of 0.046. Implementation of an interactive dashboard using Streamlit facilitates visualization of the data used in this study. Recommendations include increasing the amount of training data for sentiment models, exploring alternative correlation methods for deeper analysis, and refining the interface and data integration on the dashboard to enhance user experience and analysis accuracy. This research is expected to contribute to understanding the dynamics of public sentiment and its impact on the stock market in the context of Indonesian politics.
Co-Authors Abidin, Dodo Zaenal Adi Pangestu Adyatma, Adrian Dwinanda Afrizal Nehemia Toscany Ahmad Ashari Ahmad Fauzi Ridlwan Aji, Pandu Wahyu Alfarez Marchelian, Reyno Alkaf, Zakiyyan Andreas, Roy Anin Ammbya Soulani Arief Kelik Arief Kelik Nugroho Arief Kelik Nugroho Arief Kelik Nugroho Arief Kelik Nugroho Arkan, Naofal Dhia As'ad, Mohamad Faris Asmoro Widagdo, Asmoro Bangun Wijayanto Bintang Pradana Yosua, Panky Dadang Iskandar Dadang Iskandar Daffa Ammar Muaafii Daffa Naufaldi Al Rasyid Didit Suprihanto, Didit Dodi Sandra Eddy Maryanto Eddy Maryanto Fandy Setyo Utomo Faris Akbar Abimanyu Febri Sutomo Ferry Darmawan Hidayat, Nurul Indah Cahya Febriani Indyastuti, Devani Laksmi Ipung Permadi Ipung Permadi Ipung Permadi Ipung Permadi Iqbal Iqbal Irfan Agus Tiawan Jasmir, Jasmir Joe, Michael Khanza, Muthia Kharisun, Kharisun Kurniawan, Yogiek Indra Maria Ulfa Chasanah Muhammad Fikri Rivaldi Muhammad Luthfi Muhammad Randy Cahya Mardika Muhammad Zein Albalki Muhammad, Katon Mulki Indana Zulfa, Mulki Indana Musaadah, Khalimah Najmudin Nandha Arwiansyah Nasichatul Umayah Niko Siameva Uletika Nofiyati Nofiyati, Nofiyati Nofiyati, Nofiyati Nur Chasanah Nurhadi Nurul Hidayat Nurul Hidayat Nurul Ismailiah Priandika Ratmadani Anugrah Purnama, Benni R. Rizal Isnanto Rahayu, Swahesti Puspita Rif’an, Muhammad Rista Afifah Rochmat Mulyo Sugihono Said, Rahaini Mohd Sari, Enjelita Sharipuddin, Sharipuddin Siti Nurhayati Slamet Widodo SRI LESTARI Susi Setianingsih Teguh Cahyono Tuti Alawiyah Victoria Angela Sugianto Wahid, Arif Mu'amar Yohanes Suyanto Yunindar, Galih Arditiya Zahira Hasyati, Adila