Jurnal Sekolah Tinggi Teknik Surabaya
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Chi-Square Histogram Analysis of Woven Fabric Images Made from Natural Dyes Due to Exposure to Sunlight
Full text linkThis research aims to conduct a Chi-square analysis on the histogram of woven fabric images dyed with natural dyes following exposure to sunlight. Woven fabrics dyed with natural dyes have attracted attention in the textile industry due to their sustainability and environmental safety. Continuous sunlight is a significant factor influencing color changes in woven fabric dyed with natural dyes. The methodology involves capturing images of woven fabric pre- and post-sunlight exposure, followed by histogram analysis using Chi-Square testing, mean, mode, and standard deviation. We utilize pre-cropped and resized grayscale images. Research findings demonstrate that sunlight significantly impacts the histogram of woven fabric images dyed with natural dyes, causing shifts in color distribution, standard deviation, and mode. These findings hold critical implications for the textile industry, particularly for manufacturers of woven fabrics dyed with natural dyes. The application of Chi-Square analysis and standard deviation provides guidelines for product design, maintenance procedures, and consumer education regarding the preservation of color quality in fabrics exposed to sunlight. Changes in the quality of woven fabric images under sunlight exposure can offer essential guidance in the care and maintenance of textile products dyed with natural dyes. This research contributes to a deeper understanding of the interplay between natural dyes, sunlight, and woven fabrics, supporting the development of sun-resistant natural dyes
Procedural Map Generation for 'Splatted': Enhancing Player Experience through Genetic Algorithms and AI Finite State Machines in a Snowball Throwing Game
Full text linkGames, a now extremely prevalent form of global entertainment, have emerged as a leading industry in the entertainment media, surpassing other entertainment media such as books, films, and music. However, game development is a complex endeavor, requiring a diverse set of talents to create a decent game for people to enjoy. Some of the talents needed to create a good game is a game designer, which dictates how a player can interact with the world, a writer, which pours a meaningful story inside said world, and a composer, which uses music to elevate the emotions evoked by the game and its events. With that being said, this research aims to streamline the creation process of the game designers, specifically the level designers by focusing on procedural map generation and artificial intelligence to create a map that is in a playable state for the players to play in. Procedural map generation, facilitated by a genetic algorithm inspired by Darwin's evolutionary theory, expedites the level design process. The research explores two types of map generation—tile-based and template-based, each with distinct advantages and disadvantages. Through user acceptance tests and expert-level analysis, it is evident that the genetic algorithm performs effectively, achieving a noteworthy level of player satisfaction
Predictive Buyer Behavior Model as Customer Retention Optimization Strategy in E-commerce
Full text linkLazada is one of the rapidly growing E-commerce platforms in this digital era. One of the main challenges faced by Lazada is customer retention, where customers make purchases once or a few times before switching to other platforms. Therefore, it is important to understand buyer behavior in E-commerce through customer prediction to identify factors influencing retention. This study employs the Random Forest (RF) method to analyze Lazada customer data and formulate more effective marketing strategies. The analysis is conducted by loading preprocessed datasets into the KNIME workflow and utilizing various nodes and algorithms available in KNIME to build and evaluate predictive models. The Random Forest model is trained multiple times to achieve the highest Accuracy rate, which is 72.472%, with a fairly high level of agreement and a balanced trade-off between recall and precision. Additionally, this model successfully predicts that customers purchasing electronic equipment are potentially churning at a rate of 3.85%. Subsequently, customer strategy analysis for customer retention optimization in the E-commerce industry is conducted through data visualization using Tableau. Predictive analysis of customer behavior serves as a strong foundation for formulating effective retention strategies in the E-commerce industry. With this approach, Lazada can enhance customer experience and ensure sustainability in facing the increasingly fierce competition in the digital market
Implementation of DenseNet Architecture With Transfer Learning to Classify Mango Leaf Diseases
Full text linkMango plants (Mangifera indica) are a significant export commodity in the horticultural industry, offering numerous nutritional and economic benefits. They are rich in essential micronutrients, vitamins, and phytochemicals, contributing to their high demand globally. However, mango plants are susceptible to various diseases that can severely impact their yield and quality. These diseases pose a challenge to mango farmers, many of whom struggle to identify and treat them effectively, leading to potential harvest failures. This study aims to address this challenge by implementing a Deep Learning approach to classify diseases in mango leaves. Specifically, the research utilizes a Convolutional Neural Network (CNN) with DenseNet architecture, known for its efficiency in image classification tasks. The study incorporates Contrast Limited Adaptive Histogram Equalization (CLAHE) for image preprocessing to enhance detail and improve the model’s performance. Transfer Learning is utilized to optimize the DenseNet model, leveraging a pre-trained model to achieve high accuracy even with a relatively small dataset. The dataset used in this research comprises 4000 labeled images of mango leaves, covering seven disease categories and healthy leaves. These images include common diseases such as Anthracnose, Dieback, Powdery Mildew, Red Rust, Cutting Weevil, Bacterial Canker, and Sooty Mould. The DenseNet model achieved an overall accuracy of 99.5% in classifying mango leaf diseases
Hand Sign Virtual Reality Data Processing Using Padding Technique
Full text linkThis study focuses on addressing the challenges of processing hand sign data in Virtual Reality environments, particularly the variability in data length during gesture recording. To optimize machine learning models for gesture recognition, various padding techniques were implemented. The data was gathered using the Meta Quest 2 device, consisting of 1,000 samples representing 10 American Sign Language hand sign movements. The research applied different padding techniques, including pre- and post-zero padding as well as replication padding, to standardize sequence lengths. Long Short-Term Memory networks were utilized for modeling, with the data split into 80% for training and 20% for validation. An additional 100 unseen samples were used for testing. Among the techniques, pre-replication padding produced the best results in terms of accuracy, precision, recall, and F1 score on the test dataset. Both pre- and post-zero padding also demonstrated strong performance but were outperformed by replication padding. This study highlights the importance of padding techniques in optimizing the accuracy and generalizability of machine learning models for hand sign recognition in Virtual Reality. The findings offer valuable insights for developing more robust and efficient gesture recognition systems in interactive Virtual Reality environments, enhancing user experiences and system reliability. Future work could explore extending these techniques to other Virtual Reality interactions
Perancangan Aset Visual 3D untuk Mobile Game Bertema Superhero
Full text linkIndustri video game telah berkembang pesat dalam satu dekade terakhir oleh karena ketersediaan video game di berbagai platform, seperti komputer, konsol game, ponsel, dan berbagai perangkat genggam. Indonesia merupakan salah satu pasar game terbesar, sehingga banyak pengembang game bermunculan, salah satunya adalah Artbid Studio. Artbid berencana untuk membuat permainan baru bernama Transforming Superhero Rush yang merupakan jenis endless run. Dalam membuat game tentunya tidak lepas dari aset visual yang menarik. Oleh karena itu dalam penelitian ini akan dibuat aset visual untuk mobile game bertema Superhero. Permainan ini berbasis Android dan dikembangkan dengan Unity. Dalam pembuatan penelitian ini terdapat 4 tahapan dasar untuk mencapai kesuksesan dari tujuan yang ingin dicapai. Tahapan tersebut meliputi pengumpulan data, visual development untuk menentukan desain aset visual, 3D production sebagai proses pembuatan game ready asset, dan implementation to game engine yang merupakan penerapan aset serta tahap testing pada aset yang telah dibuat. Hasil akhir pada penelitian ini terbagi menjadi karya utama yang merupakan aset visual dalam bentuk model 3D. Hasil aset visual ini berupa model 3D karakter dengan rigging yang telah terpasang, environment, dan objek properti yang dirancang pada software 3D modeling dan siap digunakan pada game engine. Hasil karya dievaluasi kepada 50 orang responden dengan kriteria berusia 12-17 tahun, tinggal di Indonesia, dengan nilai bonus jika gemar bermain video game. Mayoritas responden memberikan tanggapan positif terhadap karya penelitian ini. Berdasarkan hasil kuesioner, sebanyak 80,6% responden memberi jawaban positif yang menunjukkan ketertarikan pada pemain terhadap tampilan aset visual. Berdasarkan fungsinya, aset visual 3D pada game ini dinyatakan berhasil yang mana sebanyak 97,43% responden memberi jawaban positif dan menunjukkan tidak adanya kendala yang menghambat alur permainan
Comparison of CNN Transfer Learning in Detecting Superior Local Fruit Types in Bali
Full text linkBali Province is an island that has unique geographical conditions, as well as the diversity of fruit it has. The specialty of local fruit is not only of economic value for food needs but also for religious ceremonial needs. Bali provincial government is currently actively promoting local fruit so that it can be used as consumption for Bali's increasingly rapid tourism. Several superior fruits were developed as an effort to raise the potential of local fruit in the tourism sector. Some of the superior fruits are Balinese snake fruit and sapodilla. However, snake fruit is one of the superior local fruits in Bali which has not experienced degradation over time. This research aims to detect the types of snake fruit in Indonesia. This fruit is not popular compared to imported fruit. Therefore, an application is needed to recognize this type of snake fruit automatically. This research uses a deep learning method with the CNN (Convolutional Neural Network) algorithm. This algorithm is able to recognize and classify an image well. The fruit images used were 400 fruits for 4 types of snake fruit. Where the training data for snake fruit is special because it has different skin and fruit contents. In this research, 2 transfer learning models from the CNN algorithm were also compared, namely mobilenetv2 and ResNet152. Based on the test results, it was found that the best level of accuracy was obtained using the ResNet152 model with an accuracy value of 92% in identifying images of Balinese snake fruit
Peran Moderasi Keamanan Kerja Pada Hubungan Psychological Contract Breach dan Turnover Intention
Full text linkTurnover intention adalah fenomena yang menarik untuk diteliti karena memiliki dampak yang signifikan terhadap berbagai aspek dalam sebuah organisasi. Dengan memahami faktor-faktor yang mempengaruhi turnover, organisasi dapat mengambil langkah-langkah proaktif untuk mengelola turnover dan meningkatkan kinerja serta keberlanjutan organisasi dalam jangka panjang. Psychological contract breach (pelanggaran kontrak psikologis) dan keamanan kerja adalah dua faktor yang sering dikaitkan dengan tingginya turnover intention dalam konteks organisasi. Ketika karyawan merasa kontrak psikologisnya dilanggar, hal ini dapat meningkatkan niat untuk berpindah kerja. Di sisi lain, keamanan kerja yang tinggi dapat memberikan rasa nyaman dan keyakinan bahwa mereka dapat mengandalkan pekerjaan mereka untuk jangka waktu yang lama. Studi ini menguji pengaruh psychological contract breach terhadap turnover intention. Studi ini juga menguji keamanan kerja karyawan sebagai pemoderasi pada hubungan psychological contract breach dan turnover intention. Data dikumpulkan dengan desain survei melalui distribusi kuesioner. Responden studi ini adalah 165 karyawan yang bekerja sebagai tenaga penjual dan tenaga pemasaran di berbagai industri di Surabaya. Pendistribusikan kuesioner dilakukan secara daring dengan menggunakan google form kepada karyawan yang berada pada lingkup jejaring sosial. Pengujian hipotesis dilakukan dengan menggunakan analisis regresi hirarkikal. Hasil Penelitian ini menunjukkan bahwa psychological contract breach berpengaruh postitif pada turnover intention dan keamanan kerja memoderasi hubungan antara psychological contract breach dan turnover intention. Pada akhir artikel ini dibahas keterbatasan dan saran penelitian serta implikasi praktis untuk organisasi
Prediction of Physico-Chemical Characteristics in Batu Tangerine 55 Based on Reflectance-Fluorescence Computer Vision
Full text linkOranges (Citrus sp.) are one of the most abundant agricultural commodities in Indonesia. One of the popular local citruses is Batu Tangerine 55. Harvesting tangerines begins 252 days after the flowers bloom. Conventionally, we still determine the level of maturity by observing the color, shape, and hardness. The results of manual grouping tend to be subjective and less accurate. Destructive testing could be carried out and provide objective results; however, it would require sampling and damaging the fruits. Computer vision could be used to evaluate the maturity level of the fruit non-destructively. Dual imaging computer vision, i.e., reflectance-fluorescence mode, could be used to enhance the accuracy of the prediction. This study aims to develop a classification model and predict the physico-chemical characteristics of Batu Tangerine 55. Destructive testing is still being carried out to determine the value of TPT, the degree of acidity, and the firmness of the fruit. Non-destructive testing was carried out to obtain reflectance and fluorescence images. Once we obtain the destructive and non-destructive data, we will incorporate them into the classification and prediction models. The machine learning method for maturity classification uses three models, namely KNN, SVM, and Random Forest. The best results on the reflectance data (RGB) SVM model resulted in an accuracy of 1 for training data and 0.97 for testing data. The maturity parameter prediction method uses the PLS method. The best results for the predicted Brix/Acidity ratio R2 parameter are 0.81 and RMSE 3.4
Penggunaan Value Stream Analysis Tools (VALSAT) dan Waste Assessment Model (WAM) untuk Mereduksi Waste Pada Pabrik Timah di Pasuruan
No full textPT. XYZ merupakan pabrik penghasil lead alloy dengan menggunakan bahan baku berupa aki bekas. Produksi dilakukan melalui 3 proses yaitu, proses battery breaker, proses furnace, proses refining. Penelitian ini akan mengamati proses produksi secara menyeluruh untuk mengetahui pemborosan yang terjadi. Metode yang diterapkan adalah Waste Assessment Model (WAM) dan metode Value Stream Analysis Tools (VALSAT). Hasil dari pengamatan ini menemukan rata-rata tingkat pelayanan sebesar 87% yang berarti tingkat efektifitas pelayanan masih kurang karena masih dibawah 100% sehingga masih dapat dilakukan perbaikan. Dan untuk memperbaiki tingkat pelayanan, maka perusahaan dapat menggunakan metode WAM yaitu dengan melakukan analisis atau pengamatan terhadap pemborosan yang terjadi terlebih dahulu. Usulan perbaikan yang direkomendasikan meliputi pengeliminasian pemborosan pada battery breaker untuk permasalahan pengeringan menggunakan energi matahari dapat digantikan dengan menggunakan mesin filter press dan untuk permasalahan pengumpulan hasil crushing dari aki bekas dapat diganti dengan langsung meletakkan hasil crushing pada wadah supaya dapat lebih cepat. Sedangkan pada proses refining dapat dilakukan penambahan jumlah operator dan untuk permasalahan produk menunggu sesuai lot untuk di kemas dapat dilakukan penambahan kapasitas mesin untuk menghindari penyimpanan berlebih