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All Journal Jurnal Transformatika Sinkron : Jurnal dan Penelitian Teknik Informatika KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Teknologi Informasi Cyberku Jurnal DIMASTIK
Rastri Prathivi
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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GAME SCORING SUPPORTING OBJECTS MENGGUNAKAN AGEN CERDAS BERBASIS ARTIFICIAL INTELLIGENCE Astrid Novita Putri; Rastri Prathivi
Jurnal Transformatika Vol 13, No 2 (2016): January 2016
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v13i2.331

Abstract

Game are activity most structure, one that ordinary is done in fun and also education tool and help to develop practical skill, as training, education, simulation or psychological. On its developing current game have until 3D. In one game, include in First Person Shutter  necessary scoring  one that intent to motivate that player is more terpacu to solve game until all through,  on scoring  Super Mario's game Boss, Compass does count scoring haven't utilized Artifical Intelligent so so chanted, while player meet with supporting objects example ammor  ability really guns directly dead, so is so easy win. Therefore at needs a count scoring  interesting so more motivated in finishing problem Scoring accounting point for First Person Shutter's game .This modelling as interesting daring in one game, since model scoring  one that effective gets to motivate that player is more terpacu in plays and keep player for back plays. Besides model scoring  can assign value that bound up with game zoom.On Research hits scoring this game will make scoring bases some criterion which is health Point, Attack point, Defence point, And  Magic  what do at have  supporting objects ,then in this research do compare two method are methodic statistic and Fuzzy. Result of this research 83,4 % on testing's examination and on eventually gets to be concluded that fuzzy's method in trouble finish time more long time but will player more challenging to railroad.  
ANALISA PENDETEKSIAN WORM dan TROJAN PADA JARINGAN INTERNET UNIVERSITAS SEMARANG MENGGUNAKAN METODE KALSIFIKASI PADA DATA MINING C45 dan BAYESIAN NETWORK Rastri Prathivi; Vensy Vydia
Jurnal Transformatika Vol 14, No 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.440

Abstract

Worm attacks become a dangerous threat and cause damage in the Internet network. If the Internet network worms and trojan attacks the very disruption of traffic data as well as create bandwidth capacity has increased and wasted making the Internet connection is slow. Detecting worms and trojan on the Internet network, especially new variants of worms and trojans and worms and trojans hidden is still a challenging problem. Worm and trojan attacks generally occur in computer networks or the Internet which has a low level of security and vulnerable to infection. The detection and analysis of the worm and trojan attacks in the Internet network can be done by looking at the anomalies in Internet traffic and internet protocol addresses are accessed.This research used experimental research applying C4.5 and Bayesian Network methods to accurately classify anomalies in network traffic internet. Analysis of classification is applied to an internet address, internet protocol and internet bandwidth that allegedly attacked and trojan worm attacks.The results of this research is a result of analysis and classification of internet addresses, internet protocol and internet bandwidth to get the attack worms and trojans.
FEATURE RECOGNITION BERBASIS CORNER DETECTION DENGAN METODE FAST, SURF, DAN FLANN TREE UNTUK IDENTIFIKASI LOGO PADA AUGMENTED REALITY MOBILE SYSTEM Rastri Prathivi; Vincent Suhartono; Guruh Fajar Shidik
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 11 No 2 (2015): Jurnal Teknologi Informasi CyberKU Vol.11 no 2
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (360.371 KB)

Abstract

Logo is a graphical symbol that is the identity of an organization, institution, or company. Logo isgenerally used to introduce to the public the existence of an organization, institution, or company.Through the existence of an agency logo can be seen by the public. Feature recognition is one of theprocesses that exist within an augmented reality system. One of uses augmented reality is able torecognize the identity of the logo through a camera. The first step to make a process of feature recognitionis through the corner detection. Incorporation of several method such as FAST, SURF, and FLANN TREEfor the feature detection process based corner detection feature matching up process, will have the betterability to detect the presence of a logo. Additionally when running the feature extraction process there areseveral issues that arise as scale invariant feature and rotation invariant feature. In this study theresearch object in the form of logo to the priority to make the process of feature recognition. FAST, SURF,and FLANN TREE method will detection logo with scale invariant feature and rotation invariant featureconditions. Obtained from this study will demonstration the accuracy from FAST, SURF, and FLANNTREE methods to solve the scale invariant and rotation invariant feature problems
Detection of Plastic Bottle Waste Using YOLO Version 5 Algorithm Yasiri, Jamilatur Rizqil; Rastri Prathivi; Susanto
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14242

Abstract

Plastic bottle waste management has become one of the most pressing environmental issues, especially in countries with high plastic usage rates, such as Indonesia. This research uses the YOLOv5 (You Only Look Once version 5) algorithm to detect plastic bottle waste automatically. The YOLOv5 algorithm was chosen because it has efficient detection performance and high accuracy in small object recognition. The dataset consists of 500 images of plastic bottles obtained through cameras and internet sources. The data is processed through several stages: annotation (bounding box and labeling using Roboflow), split dataset (70% for training, 20% for testing, and 10% for validation), pre-processing (resizing images to 460x460 pixels), and augmentation (adding data variations to improve model performance). Training and evaluation of the YOLOv5 model using the precision metric of 89.8% indicates the ability of the model to accurately identify plastic bottles from the overall prediction, recall of 83.1% indicates the success of the model in detecting the majority of plastic bottles in the test data, and mean average precision (mAP) of 89.2% represents the average precision at various prediction thresholds. Test results on varied bottle image test data obtained detection accuracy between 82%-93%, indicating the model can recognize plastic bottles consistently. Sometimes, this model needs help detecting overlapping picture objects. However, this research proves the potential of the yolov5 algorithm as an automated litter detection solution that will be integrated with a system and support faster and better plastic waste management.
Penerapan Metode Piotroski F-Score Untuk Sistem Rekomendasi Saham Berbasiskan Website Setiyawanto, Setiyawanto; Rastri Prathivi
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 5 (2024): April 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i5.1759

Abstract

Stock investment is an important aspect in allocating resources in the hope of gaining profits in the future. The Indonesian capital market shows positive growth at the end of 2022, encouraging investors' interest in investing. The problem currently faced by investors is that many investors still have difficulty analyzing the fundamentals of a company because it takes a long time and the complexity of the implementation techniques means that many experience losses when investing. This research aims to develop a stock investment recommendation system by integrating the Piotroski F-Score Method. This method uses nine criteria to assess company performance and provides a score between 0 and 9. Previous research results show that the Piotroski F-Score is effective on stocks with low Book-to-Market (BM) providing a more accurate picture of financial fundamentals. System development uses an Agile Development approach to develop systems because it allows system development faster than other methods and the tools used in system design are UML (Unified Modeling Language). The results of the research are a website-based stock recommendation system to simplify and speed up the time for making investment decisions, and the results of ADRO, ANTM, ESSA, INCO, and ITMG shares achieved the highest score each with a value of 9. The share value that reached the highest value shows that These shares are worth investing in.
Sosialisasi dan Pelatihan Sistem Informasi Pemberdayaan Potensi Desa Wisata Kandri Gunung Pati Semarang Soiful Hadi; Hetty Catur Ellyawati; Qurinta Shinta; Rastri Prathivi; Prathivi, Rastri
Jurnal DIMASTIK Vol. 3 No. 2 (2025): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v3i2.12439

Abstract

Desa Wisata Kandri menghadapi tantangan dalam pengelolaan dan promosi wisata akibat tidak adanya data digital dan kurangnya kemampuan dalam mengelola sistem informasi. Hal ini menghambat penyebaran informasi wisata dan menyebabkan rendahnya visibilitas desa di platform digital. Untuk mengatasi permasalahan ini, solusi yang ditawarkan adalah pembuatan sistem informasi resmi yang berisi informasi lengkap tentang potensi desa dengan alamat url https://kandri.id/ serta penerapan strategi SEO agar lebih mudah ditemukan di mesin pencari. Selain itu, pelatihan pengelolaan sistem informasi diberikan kepada pengelola desa agar mereka dapat memperbarui dan mengoptimalkan konten secara mandiri. Metode yang digunakan meliputi analisis kebutuhan, pengembangan sistem informasi, penerapan SEO, dan pelatihan berbasis praktik. Implementasi solusi ini  dapat meningkatkan jumlah kunjungan wisatawan, mempermudah pengelolaan potensi desa, serta meningkatkan daya saing Desa Wisata Kandri dalam industri pariwisata digital. Dengan demikian, inovasi digital ini dapat mendukung pengelolaan wisata yang lebih efektif dan berkelanjutan.
Co-Authors Astrid Novita Putri, Astrid Guruh Fajar Shidik Hetty Catur Ellyawati, Hetty Catur Qurinta Shinta Rastri Prathivi Setiyawanto, Setiyawanto Soiful Hadi Susanto Susanto Vensy Vydia Vincent Suhartono Yasiri, Jamilatur Rizqil