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All Journal Jurnal Teknologi dan Manajemen Informatika CommIT (Communication & Information Technology) Jurnal TIMES Sinkron : Jurnal dan Penelitian Teknik Informatika JIKO (Jurnal Informatika dan Komputer) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jiko (Jurnal Informatika dan komputer) JURIKOM (Jurnal Riset Komputer) JURTEKSI Building of Informatics, Technology and Science Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Ilmiah Smart Journal of Applied Computer Science and Technology (JACOST) Bulletin of Computer Science Research Journal of Artificial Intelligence and Engineering Applications (JAIEA) Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Journal of Computing Theories and Applications Jurnal Ilmiah Smart
Robet Robet
STMIK TIME
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health

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Penerapan Metode Webqual 4.0 Dalam Pengukuran Kualitas Website Awicoffee Robet; Agus Maringan Siahaan; Satriya Miharja
Bulletin of Computer Science Research Vol. 4 No. 2 (2024): Februari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i2.339

Abstract

The measurement of Awicoffee’s website quality was conducted with the aim of enabling the website owner to develop aspects that have low value, so that they can continue to develop in line with the times. The data used for this research is the result of questionnaire distribution given to 100 respondents. Website quality measurement is carried out using the webqual 4.0 method with 3 aspects assessed, namely Usability, Information Quality, and Service Interaction Quality. The purpose of this research is to determine the satisfaction value of Awicoffee website users and to determine the most significant instrument in determining  user satisfaction. Based on the research results, it was found that these three variables have an influence of 76.59% on user satisfaction, while 23.41% is influenced by variables that were not examined. Also, the variable that has the most significant impact on user satisfaction is Information Quality with a value of 5.97, whereas the Usability variable has a value of 3.42 and the Service Interaction Quality variable has a value of 3.30.
PERANCANGAN WEBSITE E-COMMERCE MULTI CABANG PADA PT. PASAR SWALAYAN MAJU BERSAMA MENGGUNAKAN ALGORITMA JACCARD COEFFICIENT Andy, Andy; Agus Maringan Siahaan; Satriya Miharja; Robet, Robet; Didik Aryanto
Majalah Ilmiah METHODA Vol. 14 No. 1 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

PT. Pasar Swalayan Maju Bersama is a company engaged in the supermarket sector and has 3 branches, namely Maju Bersama Glugur, Maju Bersama Merak Jingga, and Maju Bersama Marendal. But in practice, PT. Maju Bersama Supermarkets still have not utilized good marketing media, both internally and externally. On the internal side, the company has not been able to properly integrate the sales processes of its three branches. In addition, the main problem is related to the amount of transaction data stored in the company's storage. Transaction data recorded every day will certainly burden storage if it is not used properly to become useful knowledge for the company. From the description of the problem, it is necessary to develop a multi-branch based system that is implemented on an E-Commerce website. This research also implements the Jaccard Coefficient algorithm so that it can process company data which turns a lot of knowledge into product recommendations for customers. The results of the study show that the Jaccard Coefficient algorithm is proven capable of processing company data into knowledge in the form of product recommendations that are relevant to customers.
Image Encryption using Half-Inverted Cascading Chaos Cipheration Setiadi, De Rosal Ignatius Moses; Robet, Robet; Pribadi, Octara; Widiono, Suyud; Sarker, Md Kamruzzaman
Journal of Computing Theories and Applications Vol. 1 No. 2 (2023): JCTA 1(2) 2023
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jcta.v1i2.9388

Abstract

This research introduces an image encryption scheme combining several permutations and substitution-based chaotic techniques, such as Arnold Chaotic Map, 2D-SLMM, 2D-LICM, and 1D-MLM. The proposed method is called Half-Inverted Cascading Chaos Cipheration (HIC3), designed to increase digital image security and confidentiality. The main problem solved is the image's degree of confusion and diffusion. Extensive testing included chi-square analysis, information entropy, NCPCR, UACI, adjacent pixel correlation, key sensitivity and space analysis, NIST randomness testing, robustness testing, and visual analysis. The results show that HIC3 effectively protects digital images from various attacks and maintains their integrity. Thus, this method successfully achieves its goal of increasing security in digital image encryption
Implementation of Deep Learning Model for Classification of Household Trash Image Robet, Robet; Perangin Angin, Johanes Terang Kita; Pribadi, Octara
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14198

Abstract

The problem of household waste management is a very important issue today, where the rapid urbanization, consumptive culture, and the tendency to dispose of waste without sorting it first from home, makes the volume of waste in landfills increase. Therefore, household waste management needs to be managed quickly and appropriately, so as not to have a major impact on environmental, hygiene, and health problems. Although some environmental communities and local governments have made efforts to manage waste through recycling systems, the long-term use of human labor is inefficient, expensive, and harmful to workers' health. Therefore, utilizing artificial intelligence technology is the best solution to classify waste types quickly and accurately. This research tries to test several pre-trained convolutional neural network (CNN) models to perform classification. The results of testing pre-trained CNN models, such as AlexNet, VGG16, VGG19, ResNet50, and ResNeXt50, found that the pre-trained model ResNext50 is better with 100% accuracy, while the training loss and validation loss are 0.0414 and 0.0304, respectively. Then the second best model is the pre-trained ResNet50 model with 100% accuracy with training loss and validation loss of 0.0832 and 0.1077, respectively.
Pemanfaatan Dana Desa Untuk Meningkatkan Kesejahteraan Masyarakat Melalui Promosi Produk UMKM Menggunakan Collaborative Filtering Berbasis Android Siahaan, Agus Maringan; Robet; Jonathan Kevin Fernando; Donna Natalia
Bulletin of Computer Science Research Vol. 5 No. 1 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i1.377

Abstract

Utilizing village funds through Badan Usaha Milik Desa (BUMDes) is a strategic effort to improve the welfare of rural communities. However, its implementation often faces challenges such as suboptimal management of local economic potential and limited promotion of Micro, Small, and Medium Enterprises (MSMEs) products. This study aims to develop an Android-based application utilizing the Collaborative Filtering method as an innovative solution to support the promotion of village MSME products, enhance the effective use of village funds, and drive economic growth in rural areas. The application is designed to provide MSME product recommendations based on user preferences. Integrating the Collaborative Filtering method, the application analyzes user interaction data to offer relevant product suggestions. Its key features include product search, personalized recommendations, and a user-friendly interface that is easy for rural communities to operate. The black-box method testing results show that this application works according to the designed specifications with a system interface functional success rate of 100% of 31 functional interfaces. increased the promotion and sales of local MSME products.
Improving Resnet Model In Safety Gear Classification Using Finest Optimizer Robet; Johanes Terang Kita Perangin Angin; Edi Wijaya
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.703

Abstract

The Occupational accidents that occur in the work environment are increasing day by day. This is caused by workers' non-compliance with the established work safety equipment. Although the supervision of the use of work safety equipment has been carried out, it is still done manually involving less effective human resources. Therefore, it is necessary to develop an intelligent model that can classify the use of work safety equipment more accurately. This study uses the pre-trained ResNet50 model and is combined with the best optimization model to improve accuracy. The results of the study showed that the RMSProp optimization model has better performance with an accuracy value of 97.01% in the 17th epoch of 50 epochs of data training and with training loss and validation loss values ​​of 0.3268 and 0.145, respectively. Testing of 20 images with each image, 10 images using safety equipment, and 10 images not using safety equipment can be classified correctly.
Akurasi K-Means dengan Menggunakan Cluster dan Titik Grid Terbaik pada Pemetaan Grid Interatif K-Means Perangin Angin, Johanes Terang Kita; Rizkita, Ari; Robet, Robet; Pribadi, Octara
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp127-129

Abstract

Traditional K-Means face 2 (two) main problems, namely: Determination of Initial Centroid and poor initial cluster. Determining the initial centroid using random numbers is one of the main problems in classical K-Means which results in low accuracy and long computation time. Likewise, determining the good centroid of each cluster without being accompanied by a process of paying attention to the performance of each cluster can also cause the accuracy value obtained is not good. This study will contribute to how the performance obtained by determining a good initial centroid is combined with the use of a good cluster. Determination of a good initial centroid is done by using the K-Means Grid Mapping which divides the determination of the centroid into several Grid Points. The result of this research is a combination of Iterative K-Means with Grid Mapping K-Means to become Iterative Grid Mapping K-Means which will get a good initial centroid and also a good cluster shown in the table of iris and abalone, comparison of the variables in the iris and abalone affecting the best cluster as a result.
Integrating Hybrid Statistical and Unsupervised LSTM-Guided Feature Extraction for Breast Cancer Detection Setiadi, De Rosal Ignatius Moses; Ojugo, Arnold Adimabua; Pribadi, Octara; Kartikadarma , Etika; Setyoko, Bimo Haryo; Widiono, Suyud; Robet, Robet; Aghaunor, Tabitha Chukwudi; Ugbotu, Eferhire Valentine
Journal of Computing Theories and Applications Vol. 2 No. 4 (2025): JCTA 2(4) 2025
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.12698

Abstract

Breast cancer is the most prevalent cancer among women worldwide, requiring early and accurate diagnosis to reduce mortality. This study proposes a hybrid classification pipeline that integrates Hybrid Statistical Feature Selection (HSFS) with unsupervised LSTM-guided feature extraction for breast cancer detection using the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. Initially, 20 features were selected using HSFS based on Mutual Information, Chi-square, and Pearson Correlation. To address class imbalance, the training set was balanced using the Synthetic Minority Over-sampling Technique (SMOTE). Subsequently, an LSTM encoder extracted non-linear latent features from the selected features. A fusion strategy was applied by concatenating the statistical and latent features, followed by re-selection of the top 30 features. The final classification was performed using a Support Vector Machine (SVM) with RBF kernel and evaluated using 5-fold cross-validation and a held-out test set. Experimental results showed that the proposed method achieved an average training accuracy of 98.13%, F1-score of 98.13%, and AUC-ROC of 99.55%. On the held-out test set, the model reached an accuracy of 99.30%, precision of 100%, and F1-score of 99.05%, with an AUC-ROC of 0.9973. The proposed pipeline demonstrates improved generalization and interpretability compared to existing methods such as LightGBM-PSO, DHH-GRU, and ensemble deep networks. These results highlight the effectiveness of combining statistical selection and LSTM-based latent feature encoding in a balanced classification framework.
IMPLEMENTASI METODE PROTOTYPING DALAM PERANCANGAN UI/UX DESIGN PADA MEDIA DIGITAL TERANG KITA Rizkita, Ari; Perangin Angin, Johanes; Robet; Pribadi, Octara
Jurnal TIMES Vol 14 No 1 (2025): Jurnal TIMES
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51351/jtm.14.1.2025834

Abstract

Perkembangan teknologi informasi pada era saat ini bergerak sangat pesat dan mencakup seluruh aspek kehidupan manusia, termasuk pada bidang media. Media digital terangkita.com, sebuah platform yang bergerak di bidang edukasi dan penyebaran konten positif berbasis nilai-nilai sosial. Proses perancangan dilakukan melalui tahapan metode prototyping, mulai dari pengumpulan kebutuhan pengguna, pembuatan sketsa awal, hingga pengujian desain interaktif. Pendekatan ini memungkinkan kolaborasi yang dinamis antara desainer dan pengguna, serta memberikan fleksibilitas untuk melakukan revisi berdasarkan umpan balik secara iteratif. Hasil penelitian menunjukkan bahwa metode prototyping mampu meningkatkan kualitas desain UI/UX secara signifikan, ditinjau dari aspek keterpahaman, kemudahan navigasi, dan kepuasan pengguna terhadap antarmuka. Temuan ini memberikan kontribusi terhadap pengembangan desain media digital yang lebih human-centered, serta menjadi acuan dalam proses desain interaktif berbasis kebutuhan pengguna. Kata kunci: UI/UX Design, Prototyping, Media Digital, Desain Interaktif, Terang Kita
Aplikasi Pencarian Bengkel Tambal Ban Dan Spbu Terdekat Di Kota Medan Menggunakan Metode Dijkstra Dan Haversine Berbasis Android Robet, Robet
Jurnal TIMES Vol 10 No 1 (2021): Jurnal TIMES
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (659.225 KB) | DOI: 10.51351/jtm.10.1.2021633

Abstract

Sarana transportasi yang paling banyak dimiliki dan digunakan oleh masyarakat kota Medan pada saat ini adalah sepeda motor. Walaupun saat ini peningkatan jumlah sepeda motor yang pesat menimbulkan berbagai permasalahan dari sisi ekonomi, sosial dan lingkungan. Namun di sisi lain, sepeda motor memiliki harga yang mudah dijangkau oleh masyarakat dalam menunjang berbagai aktivitas bisnis, pekerjaan, pendidikan untuk berpergian dari satu tempat ke tempat yang lain. Dengan kemudahan mobilitas yang tinggi dan jangkauan akses ke suatu tempat, namun ada kekurangan dari sepeda motor yaitu mudahnya terjadi kebocoran ban serta mudahnya kehabisan bahan bakar minyak dikarenakan umumnya tangki minyak sepeda motor yang kapasitasnya kecil, sehingga pengendara sepeda motor terpaksa harus berhenti dan mendorong motornya. Fakta di lapangan para pengendara sepeda motor yang mengalami kebocoran ban dan kehabisan bahan bakar minyak, untuk mencari lokasi tambal ban ataupun SPBU seringkali dilakukan secara konvensional. Namun yang menjadi permasalahan, karena luasnya kota Medan membuat kesulitan bagi pengendara sepeda motor untuk menelusuri satu per satu lokasi bengkel tambal ban ataupun SPBU apalagi ketika malam hari tidak banyak kedua tempat tersebut buka. Memang saat ini pencarian tempat tambal ban dan SPBU sudah bisa dilakukan melalui aplikasi Google Map, namun kekurangannya adalah aplikasi Google Map belum dapat memberikan rekomendasi bengkel tambal ban dan SPBU terdekat dari posisi pengendara sepeda motor. Oleh sebab itu maka perlu dilakukan penelitian untuk membangun aplikasi pencarian bengkel tambal ban dan SPBU berbasis Android dengan penerapan metode Dijkstra dan Haversine dalam memberikan rekomendasi lokasi terdekat bengkel tambal ban dan SPBU di kota Medan.
Co-Authors Aghaunor, Tabitha Chukwudi Agus Maringan Siahaan Alvin Alvin, Alvin Andi Andi Andy Andy Barus, Hanisa putri Bayu Teta Br Tarigan, Widia CANDRA GUNAWAN Carles Juliandy Chandra Chandra Darwin, Jenime De Rosal Ignatius Moses Setiadi Didik Aryanto Donna Natalia edi edi Edi Wijaya Edi Wijaya Edi Wijaya Feriani Astuti Tarigan Feriani Astuti Tarigan Feriani, Feriani Astuti Tarigan Hendri Hendri Hoki, Leony Hose, Fernando Jackri Hendrik Johanes Terang Kita Perangin Angin Jonathan Kevin Fernando Juan Charles Kartikadarma , Etika Kohsasih, Kelvin Leonardi Lase, Wisriani Liecero, Marcus Michael Angelo Nurhayati Harahap Octara Pribadi Ojugo, Arnold Adimabua Panjaitan, Tabitha Martha Agustine Parapak, Yehezkiel E.A Perangin Angin, Johanes Rizkita, Ari Robin Robin Robin Robin, Robin Robin Zheng Sarker, Md Kamruzzaman Satriya Miharja Setiawan, Jerico Setyoko, Bimo Haryo Siahaan, Agus Maringan Simanjuntak, Martina Sances Sinaga, Asra Gretya Siregar, Tarq Hilmar Suyud Widiono Tio, Nicholas Ugbotu, Eferhire Valentine Vincent Vincent, Vincent Wirawan, Haria Yuliana Yuliana