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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Teknologi dan Manajemen Informatika Prosiding SNATIKA Vol 01 (2011) Record and Library Journal Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Journal of Research and Technology Indonesian Journal of Artificial Intelligence and Data Mining JKTP: Jurnal Kajian Teknologi Pendidikan Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Terpadu EDUMATIC: Jurnal Pendidikan Informatika JUSIM (Jurnal Sistem Informasi Musirawas) SPIRIT Buletin Ilmiah Sarjana Teknik Elektro Zonasi: Jurnal Sistem Informasi JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Journal of Advanced in Information and Industrial Technology (JAIIT) SKANIKA: Sistem Komputer dan Teknik Informatika Teknika KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Data Science, Engineering, and Analytics (IJDASEA) DECODE: Jurnal Pendidikan Teknologi Informasi JITSI : Jurnal Ilmiah Teknologi Sistem Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Informatics, Electrical and Electronics Engineering Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science The Indonesian Journal of Computer Science INOVTEK Polbeng - Seri Informatika JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Anik Vega Vitianingsih
UNITOMO, Surabaya
Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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Strategic Insights into Educational Assessment: The Implementation and Constraints of SIMCPM in Monitor-ing Student Outcomes Seftin Fitri Ana Wati; Fitri, Anindo Saka; Vitianingsih, Anik Vega; Najaf, Abdul Rezha Efrat
IJDASEA (International Journal of Data Science, Engineering, and Analytics) Vol. 3 No. 2 (2023): International Journal of Data Science, Engineering, and Analytics Vol 3, No 2,
Publisher : Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijdasea.v3i2.5

Abstract

In response to the evolving challenges in educational institutions, the Ministry of Education and Culture emphasizes the crucial role of effective information systems in achieving optimal educational objectives. This study introduces the Student Learning Achievement Information System (SIMCPM) as a strategic solution for systematically monitoring and evaluating student performance. The research explores the implementation of SIMCPM, focusing on its role in functional testing within educational environments. With a user-centric approach, the study investigates how SIMCPM can be integrated as an innovative tool for monitoring student learning achievements, specifically in displaying grade and attendance data. The methodology outlines the comprehensive approach to SIMCPM's development, emphasizing the use of Laravel 8 for back-end infrastructure and HTML, CSS, and JavaScript for UI/UX development. Data visualization development is highlighted, showcasing the integration of ApexCharts.JS for effective communication of educational metrics. Functionality testing ensures the reliability of the system, encompassing testing scenarios, integration testing, load and performance testing, and mobile and tablet functional testing. Results and discussion present the outcomes of SIMCPM's implementation, including data simulation, dashboard rendering, and functionality testing. The study introduces dashboard features for students, lecturers, and the Head of Study Program, emphasizing speed, efficiency, and data visualization quality. Functionality testing results confirm the robustness of the system. The subsequent section interprets the results, addressing implications, strengths, limitations, and potential improvements in the SIMCPM system. The conclusion recommends continuous testing with real-time data, user feedback integration, and potential enhancements such as predictive analytics and personalized learning recommendations to ensure sustained effectiveness in supporting academic processes. Overall, SIMCPM emerges as a promising tool for efficient academic management, subject to continuous refinement and innovation.
REPRESENTASI DATA HASIL ANALISA SPASIAL DAERAH RAWAN PENYAKIT CAMPAK MENGGUNAKAN METODE WEIGHT PRODUCT MODEL Vitianingsih, Anik Vega; Choiron, Achmad; Umam, Azizul; Cahyono, Dwi; Suyanto
Journal of Research and Technology Vol. 6 No. 1 (2020): JRT Volume 6 No 1 Jun 2020
Publisher : 2477 - 6165

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (881.211 KB) | DOI: 10.55732/jrt.v6i1.139

Abstract

Measles is a part of many diseases that occur in the tropics as happened in East Java. Measles disease data recorded in the Health Profile Book contains information on tabular data on the number of measles cases, the fatality rate of measles cases, and data that contain infant measles immunization. The purpose of the discussion of this paper is to represent spatial and attribute data resulting from spatial data processing in the spatial analysis process by Weight Product Model (WPM) methods and in the Multiple Attribute Decision Making (MADM). Data representation to determine areas prone to tropical diseases based on infant immunization status, nutritional status, epidemics, and PD3I. The results of the spatial data modeling will be represented into spatial data and attribute data obtained from the preferential value of Vi with the category of classification of tropical disease-prone areas with good, average, fair, and poor immunization status.
Sistem Rekomendasi Pemilihan Komponen Komputer Menggunakan Metode AHP dan Profile Matching Salmanarrizqie, Ageng; Vitianingsih, Anik Vega; Kristyawan, Yudi; Maukar, Anastasia Lidya; Marisa, Fitri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7643

Abstract

Computers have become one of the technological tools that play a crucial role in enhancing society's productivity. Therefore, many desktop computer users assemble their own computers to achieve computer performance according to their preferences or needs. However, some people lack information about the variations, specifications, and capabilities of each computer component to be assembled. This research offers a recommendation system that is part of a decision support system (DSS) to assist users in providing recommendations for computer components that are being sought and needed based on brand, price, and specifications using the Analytic Hierarchy Process (AHP) and Profile Matching methods. Parameters are based on the processor, motherboard, graphics card (VGA), storage, RAM, power supply, and casing with priority categories based on specifications, price, and brand. Data weighting is done using the Analytic Hierarchy Process (AHP) method, while the Profile Matching method is used for ranking the weighting results. The research results show an accuracy rate of 60% using the Profile Matching method, while the AHP method achieves an accuracy rate of 57%.
Sentiment Analysis of Alfagift Application User Reviews Using Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) Methods Damayanti, Erika; Vitianingsih, Anik Vega; Kacung, Slamet; Suhartoyo, Hengki; Lidya Maukar, Anastasia
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 4 No. 2: JULI 2024
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v4i2.478

Abstract

The rapid advancement of mobile apps has emerged as an important aspect of the routine of internet-connected users. In Indonesia, many companies are introducing their apps to improve the quality of service for users, and Alfamart is one of them. However, users have identified many shortcomings in these apps. This feedback is provided by users on the review feature of the Alfagift app on the Google Play Store. This research aims to apply a sentiment analysis approach to identify the application's shortcomings so that developers can understand the aspects that need to be improved to improve the quality of application services. The research stages include data collection, preprocessing, labeling, weighting, classification of LSTM and SVM methods, and performance evaluation using a confusion matrix. The dataset consists of 1000 reviews obtained through web scraping techniques. This research uses the Lexicon-based method to classify the dataset into positive, negative, and neutral categories. The analysis results show that 801 data are classified as positive sentiment, 77 as negative sentiment, and 122 as neutral sentiment. Based on testing, both SVM and LSTM methods show good performance. The best accuracy results were obtained using the SVM method, which amounted to 83.5%. Meanwhile, the LSTM method achieved an accuracy of 82%.
Aplikasi Game Simulasi 3D Pencegahan Bullying Anak Remaja Berbasis Role Playing Menggunakan Metode FSM dan BT Dwi Prasetyo, Septian; Vitianingsih, Anik Vega; Choiron, Achmad; Cahyono, Dwi; Wikaningrum, Anggit
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1901

Abstract

The case of bullying among teenagers has become one of the most concerning problems in society. Therefore, innovative and interesting approaches need to be taken to overcome this. The development of multimedia game technology can be an innovation that can be offered to prevent the impact of bullying cases on adolescents. The purpose of this research is to develop a 3D simulation game application for bullying prevention based on role playing using finite state machine (FSM) and behavioral tree (BT). FSM is used for the control system on the player, while BT is used to control the behavior of Non-Player Character (NPC) through the level of decisions and actions that must be taken or executed. This research methodology uses multimedia development life cycle (MDLC), namely, determining game concepts, creating design scenarios, collecting asset materials, developing game applications, testing game applications, and distributing game applications. The test results using the Technology Acceptance Model (TAM) get a percentage value of 76%. The development of role playing-based bullying prevention simulation game applications in research is expected to be an alternative learning simulation media that is effective in preventing bullying for teenagers
Pemetaan Kawasan Permukiman Kumuh di Kabupaten Mojokerto Berbasis Webmap Vitianingsih, Anik Vega; Tiara Shanty, Ratna Nur; Sari, Dita Prawita; Kristanto, Titus
Journal of Advances in Information and Industrial Technology Vol. 1 No. 1 (2019): November
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.089 KB) | DOI: 10.52435/jaiit.v1i1.8

Abstract

Pada tahun 2016 masih terdapat 35.291 Ha permukiman kumuh perkotaan yang tersebar di hampir seluruh wilayah Indonesia Kondisi tersebut diperkirakan akan terus mengalami penambahan apabila tidak ada bentuk penanganan yang inovatif, menyeluruh, dan tepat sasaran. Kabupaten Mojokerto merupakan wilayah yang masuk dalam daftar kawasan permukiman kumuh, hal ini berdasarkan daftar kabupaten/kota yang ada dalam program KOTAKU (Kota Tanpa Kumuh). Sedangkan peraturan UU Nomor 1 Tahun 2011 tentang Penanganan permukiman kumuh wajib dilakukan oleh Pemerintah, Kepala daerah dan atau setiap orang. Tidak diketahuinya tingkat kumuh dan penanganan yang sesegera mungkin di suatu kawasan dapat menimbulkan kawasan permukiman kumuh baru.
Forecasting Model of Indonesia's Oil & Gas and Non-Oil & Gas Export Value using Var and LSTM Methods Rijal, Khaidar Ahsanur; Vitianingsih, Anik Vega; Kristyawan, Yudi; Maukar, Anastasia Lidya; Wati, Seftin Fitri Ana
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.13127

Abstract

As a country with abundant natural resources in the form of mineral and non-mineral products, Indonesia is characterized by its ability to fulfill domestic and foreign needs through export activities categorized into two commodities: oil and gas and non-oil and gas. Export activities are an indicator of the country's economic growth that often fluctuates in value, and these conditions are fundamentally caused by a decrease in production quantity and the instability of the global economic climate. The strategy to overcome these problems is to create a forecasting model. This research aims to develop a forecasting model using time series analysis methods, including vector autoregressive (VAR) and long short-term memory (LSTM) methods based on oil and non-oil and gas value parameters. The results of the Granger causality test stated that the values of oil and gas and non-oil and gas affect each other. The VAR model with the optimum lag produced by the Akaike Information Criterion (AIC) test obtained an accuracy value of MAPE oil & gas and non-oil and gas of 18.4% and 32.1%, respectively. LSTM generates the best model with a MAPE value of 6,23% for oil & gas and 8,18% for non-oil and gas.
Pengembangan Aplikasi Game Pengenalan Jenis-jenis Virus Berbasis RPG Pradana, Dwifa Yuda; Vitianingsih, Anik Vega; Cahyono, Dwi; Wikaningrum, Anggit; Wati, Seftin Fitri Ana
Jurnal Teknologi Terpadu Vol 10 No 2 (2024): Desember, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i2.1249

Abstract

The global community has been significantly affected by the COVID-19 pandemic in terms of health, education, the economy, social matters, and culture. Digital devices are increasingly being used for entertainment to combat boredom amidst restrictions on physical activity. However, this behaviour can also reduce adherence to health protocols, which can lead to high cases of COVID-19. Education about viruses is increasingly emphasized, especially for adolescents, who are a key group in preventing the spread of viral infections. Consequently, the media is required to introduce the different kinds of viruses and their survival strategies. This study aims to create an RPG-based "V-Fight" game application for virus types' exposure among teens. The research used a software development methodology that applied the Multimedia Development Life Cycle (MDLC), which consists of Concept, Design, Material Collecting, Assembly, Testing, and Distribution. The validation test conducted on 35 respondents obtained a validity level of 76.38%. This indicates that the tested game has sufficient criteria to be considered a practical learning tool.
Application of Faster R-CNN Deep Learning Method for Rice Plant Disease Detection Pujiono, Halim; Vitianingsih, Anik Vega; Kacung, Slamet; Lidya Maukar, Anastasia; Fitri Ana Wati, Seftin
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 8 No. 2 (2024)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v8i2.1165

Abstract

Plant diseases, particularly in staple crops like rice, significantly affect the stability of rice production in Indonesia. Crop failure caused by rice plant diseases present a critical challenge for farmers.  Early diagnosis is crucial for preventing and managing rice diseases, as it facilitates more effective preventive measures, reduces yield losses, and boosts overall agricultural production. This study aims to apply the Faster Region Convolutional Neural Network (Faster R-CNN), a deep learning approach, to detect rice plant diseases. The Grid Search method was employed as a hyperparameter tuning technique to identify the optimal parameter combination for enhancing algorithm performance. Experimental results demonstrate the model's performance, achieving an accuracy rate of 88%, recall and precision of 100%, and an F1 Score of 93%. These findings indicate that the Faster R-CNN method effectively recognizes and classifies rice plant diseases with a high degree of accuracy.
Sentiment Analysis of Brand Ambassador Influence on Product Buyer Interest Using KNN and SVM Putri, Natasya Kurnia; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Yasin, Verdi
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 2 (2024): September 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i2.29469

Abstract

In the dynamic marketing, companies usually use strategies involving celebrities or influencers to promote their products or brands. The currently popular strategy is using Korean boy bands as brand ambassadors. This collaboration certainly gets a lot of opinion responses through tweets on X app social media. This research aims to analyze sentiment to determine how the product buyer's interest responds to brand suitability, brand image management, and the influence of issues that arise in this collaboration. The research stages consist of data collection, pre-processing, labeling, weighting, and classification with K-Nearest Neighbor and Support Vector Machine and performance evaluation using a confusion matrix. The dataset used was 696 tweets taken using web scrapping techniques. This research uses the Lexicon-based method to divide the dataset into positive, negative, and neutral classes. The SVM method shows superior test results by achieving an accuracy rate of 83.34% compared to the KNN method, which produces an accuracy value of 71.2% in its calculations
Co-Authors Abdul Rezha Efrat Najaf Achmad Choiron Ade Susianti, Febrina Adharani, Salza Kartika Agustinus Noertjahyana Ahmad, Sharifah Sakinah Syed Al-Karaki, Jamal N. Ana Wati, Seftin Fitri Anastasia Lidya Maukar ANGGI FIRMANSYAH Arumsari, Andini Dwi Azzahra, Morra Fatya Gisna Nourielda Badrussalam, Nanda Budi Suprio, Yoyon Arie Cahyono, Cahyono Kaelan Damayanti, Erika DWI CAHYONO Dwi Indrawan, Dwi Dwi Prasetyo, Septian Fardhan Maulana, Abelardi Fauzan, Rizky Fauzi, Ariq Ammar Fawaidul Badri Febrian Rusdi, Jack Firmansyah, Deden Fitri Ana Wati, Seftin Fitri, Anindo Saka Ghibran Jhi S, Moch Hamidan, Rusdi Hengki Suhartoyo, Hengki Hermansyah, David Hikmawati, Nina Kurnia Jazaudhi’fi, Ahmad Khusnaini, Geovandi Gamma KRISTIAWAN KRISTIAWAN Li, Shuai Lidya Maukar, Anastasia MARIFANI FITRI ARISA Maukar, Anastasia L Maukar, Anastasya Lidya Maulidiana, Putri Dwi Rahayu Miftakhul Wijayanti Akhmad, Miftakhul Wijayanti Minggow, Lingua Franca Septha Mudinillah, Adam Mustafa, Zulfikar Amirul Muzaki, Mochammad Rizki Niken Titi Pratitis Oktafamero, Yomara Omar, Marwan Pamudi Pamudi, Pamudi Pangestu, Resza Adistya Pradana, Dwifa Yuda Pramisela, Intan Yosa Pramudita, Atanasia Pramudita, Krisna Eka Pujiono, Halim Puspitarini, Erri Wahyu Putra Selian, Rasyid Ihsan Putri, Jessica Ananda Putri, Natasya Kurnia Rahmansyah, Ragada Ramadhan, Prayudi Wahyu Ramadhani, Illham Ratna Nur Tiara Shanty, Ratna Nur Tiara Rijal, Khaidar Ahsanur Riza , M. Syaiful Rusdi Hamidan Rusdi, Jack Febrian Salmanarrizqie, Ageng Sari, Dita Prawita Seftin Fitri Ana Wati Slamet . Slamet Kacung, Slamet Slamet Riyadi, Slamet Riyadi Slamet Winardi Sufianto, Dani Suyanto Suyanto Suyanto Tiara Shanty, Ratna Nur Titus Kristanto Tri Adhi Wijaya, Tri Adhi Umam, Azizul Voni Anggraeni Suwito Putri Warsito Sujatmiko, Achmad Wati , Seftin Fitri Ana Wati, Seftin Fiti Ana Wati, Seftin Fitri Ana Wijiono, Aditya Kusuma Wikaningrum, Anggit Wikanningrum , Anggit Yasin, Verdi Yoyon Arie Budi Suprio Yudi Kristyawan, Yudi Yunior, Kevin Heryadi Zandroto, Yosefin Yuniati Zangana, Hewa Majeed