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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SKANIKA: Sistem Komputer dan Teknik Informatika The Indonesian Journal of Computer Science Akademika Jurnal Teknologi Pendidikan
Anik Vega Vitianingsih
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Social Sciences

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Inventory Information System Using Fifo And Holt Winters Multiplicative Methods Firmansyah, Verdi Tri; Anik Vega Vitianingsih; Syahadiyanti, Litafira; Pamudi; Alda Raharja
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13791

Abstract

In the era of society 5.0, information technology plays an important role in daily life, company operations, and management. Medium-scale stores such as Nisrina Mart require an inventory control process to determine the number of products to be restocked quickly and accurately. However, what happened was the opposite, shop owners experienced a lot of losses because the inventory control process carried out manually had the potential to experience inaccurate data and material losses. Based on these problems, this research tries to propose the development of an inventory information system for reporting incoming and outgoing goods using the First In First Out (FIFO) method. Stock forecasts based on previous sales data are generated to project future stock needs using the Holt-Winters Multiplicative trend moment method. The software development model uses a waterfall which includes requirements, design, implementation, testing, and maintenance. The test results of the Holt Winter multiplication method show a prediction error rate of 0.27. Meanwhile, the level of accuracy in predicting goods sales is 73%. The implementation of this information system is expected to provide convenience in stock monitoring, reduce prediction errors, and increase the accuracy of product data analysis reports to support more effective and efficient management decision-making.
APLIKASI 3D GAME SIMULASI UNTUK PENGENALAN PROFESI PADA ANAK USIA DINI Ibnu Hanafi; Anik Vega Vitianingsih; Achmad Choiron; Dwi Cahyono; Anggit Wikanningrum
Akademika Vol 13 No 01 (2024): Akademika : Jurnal Teknologi Pendidikan
Publisher : Akademika : Jurnal Teknologi Pendidikan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34005/akademika.v13i01.3802

Abstract

The introduction of professions at an early age is important for children's character building. Educational games can be an interesting and interactive learning media to introduce various professions to children.The purpose of this research is to develop a game application to turn educational content into an interactive learning experience that can be accessed via Android. The research method adopts the Multimedia Development Life Cycle (MDLC) method which consists of determining the application concept, designing 3-dimensional objects, material collecting, developing applications, testing applications and publishing applications.The research results obtainedinclude: validation of understanding various professions obtained a percentage of 83% with valid criteria, validation of control interaction obtained a percentage of 74% with valid criteria, validation of liking the use of games obtained a percentage of 84% with valid criteria, and validation of the desire to play obtained a percentage of 72% with valid criteria. From the results of the validation test that has been carried out on 30 respondents, it shows an average value of 79.44% and it can be concluded that this game is included in the qualifications worth using as a more efficient learning media.
Sistem Pakar Diagnosa Organisme Pengganggu Tanaman (OPT) Semangka Menggunakan Metode Fuzzy Tsukamoto Wistu Ari Wibowo; Anik Vega Vitianingsih; Yudi Kristyawan; Slamet Kacung
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3653

Abstract

Diagnosa yang tepat sangat penting untuk mengendalikan dan mencegah penyebaran organisme pengganggu tanaman semangka. Namun, seringkali petani kesulitan dalam mendiagnosa organisme pengganggu tanaman yang menyerang semangka. Masalah yang dihadapi adalah kurangnya pengetahuan dan pengalaman petani dalam mengetahui jenis organisme pengganggu semangka. Hal ini dapat mengakibatkan kesalahan dalam diagnosa dan pengobatan yang tidak tepat dapat mengurangi produksi dan kualitas buah yang dihasilkan. Tujuan penelitihan ini adalah membuat sistem pakar untuk identifikasi jenis organisme pengganggu tanaman semangka menggunakan metode Fuzzy Tsukamoto berdasarkan parameter organisme pengganggu tanaman semangka yang menyerang daun, batang dan kulit buah semangka. Metode tersebut digunakan karena mudah diterapkan dan bisa menghasilkan keputusan dengan masukan data yang samar. Variabel keluaran adalah kondisi besar serangan hama dan penyakit tanaman semangka yang dikelompokkan menjadi empat kategori yaitu ringan, sedang, berat dan puso.
Mapping Residential Land Suitability Using a WEB-GIS-Based Multi-Criteria Spatial Analysis Approach: Integration of AHP and WPM Methods Anik Vega Vitianingsih; Ullum, Choirul; Maukar, Anastasia Lidya; Yasin, Verdi; Wati, Seftin Fitri Ana
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 2 (2024): April 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i2.4520

Abstract

Along with the increase in population and the acceleration of economic expansion, there has been a concomitant increase in the urgent requirement for additional property that can serve as a venue for a wide variety of community activities. It is not uncommon for large cities, which are the epicenter of urbanization, such as the city of Surabaya, to experience a sharp increase in the demand for land. One of the regions that has excellent accessibility is the Sidoarjo Regency, which is comparable to the City of Surabaya in this regard. The goal of this research is to use Web-GIS to conduct an analysis of spatial data to identify the land functions that are most suitable for use in residential areas. The Analytic Hierarchy Process (AHP) and the Weighted Product Model (WPM) are two of the methodologies that are included in the spatial data modeling method that uses multi-criteria decision making (MCDM). The parameters of the characteristics that are used are derived from data such as the distance to the city center, the distance to the market, the distance to the hospital, the distance to public transportation, the slope, the type of soil, and the amount of rainfall. The results of the spatial data modeling categorize the suitability of new residential land into categories of land that is not suitable for residential use and land that is acceptable for residential use. A K value of 0.27 is the result of the comparison test that was run between the two MCDM approaches using Cohen's Kappa coefficients.
ANALISIS SENTIMEN ULASAN PRODUK SPAREPART MOTOR DI E-COMMERCE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) Reza Ega Resnanda; Dwi Cahyono; Anik Vega Vitianingsih
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 9 No 1 (2026): Jurnal SKANIKA Januari 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v9i1.3608

Abstract

This study was motivated by the increasing use of e-commerce in Indonesia, which highlights the importance of analyzing customer reviews as a basis for evaluating product and service quality. This study aims to analyze the sentiment of reviews of Honda motorcycle spare parts at the Ducks Garage store on the Tokopedia platform using the Support Vector Machine (SVM) algorithm. The dataset used consists of 2.537 reviews obtained through web scraping techniques and processed through text preprocessing stages, including data cleaning, normalization, tokenization, stopword removal, and stemming. Sentiment labelling was carried out into three classes, namely positive, negative, and neutral, with lexicon-based and feature weighting using the Term Frequency–Inverse Document Frequency (TF-IDF) method. Data distribution imbalance was handled using the Synthetic Minority Over-Sampling Technique (SMOTE) method. The SVM model was tested using three types of kernels, namely Linear, Polynomial, and Radial Basis Function (RBF). The test results showed that the RBF kernel produced the best performance with an accuracy of 92.79%, followed by the Linear kernel at 89.89% and the Polynomial kernel at 72.57%. The conclusion of this study shows that the application of SVM with SMOTE data balancing is effective in classifying the sentiment of e-commerce product reviews and can be used to support data-driven business decisions based on customer data.
Co-Authors Achmad Choiron Alda Raharja Anastasia Lidya Maukar Anggit Wikanningrum DWI CAHYONO Firmansyah, Verdi Tri Ibnu Hanafi Litafira Syahadiyanti Pamudi Pamudi, Pamudi Reza Ega Resnanda Slamet Kacung Ullum, Choirul Wati, Seftin Fitri Ana Wistu Ari Wibowo Yasin, Verdi Yudi Kristyawan