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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JSI (Jurnal sistem Informasi) Universitas Suryadarma Jurnal Mantik Tematik : Jurnal Teknologi Informasi Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Kajian Ilmiah Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat IICS Journal of Students‘ Research in Computer Science (JSRCS) Jurnal Abdimas Ekonomi Dan Bisnis (JAMEB) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jurnal Sistim Informasi dan Teknologi Jurnal Pengabdian Pelitabangsa International Journal of Information Technology and Computer Science Applications (IJITCSA) Jurnal Sistem Informasi Indonesian Journal of Education And Computer Science Jurnal Inovasi dan Pengembangan Hasil Pengabdian Masyarakat VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Journal of Computer Science Contributions (Jucosco) The Indonesian Journal of Computer Science Journal of Informatics and Information Security Jurnal Komtika (Komputasi dan Informatika)
Priatna , Wowon
Informatika, Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Crawling Engine Pada Website Mann, Baldwin, Fleetguard Dan Pengelompokan Produk Menggunakan K-Means Rahman, Andi; Priatna, Wowon; Lestari, Tyastuti Sri; Hidayat, Agus
Jurnal Pelita Teknologi Vol 19 No 2 (2024): September 2024
Publisher : Universitas Pelita Bangsa

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

Abstract

Tujuan penelitian ini adalah untuk mengelompokan produk pada beberapa web site. Dalam crawling engine akan sangat membantu dalam memasukan data produk secara otomatis mengambil data dari website produk tersebut, kemudian di input dalam aplikasi Odoo. Algoritma k-means klustering sendiri adalah algoritma mengelompokkan pengamatan ke dalam kelompok k, di mana k merupakan parameter input. Tiap data kemudian ditetapkan pada setiap pengamatan cluster berdasarkan kedekatan pengamatan nilai rata-rata cluster. Pengelompokan ini akan sangat membantu dalam klasifikasi produk berdasarkan cross reference. Hasil dari penelitian ini adalah produk produk terinput secara otomatis dan data sesuai dengan website produk tersebut dan produk terkelompok sesuai dengan cross reference.
Implementasi Algoritma Naïve Bayes dan Algoritma C4.5 Untuk Melakukan Analisis Sentimen terhadap Ulasan Komentar Pengguna TikTok di Google Play Store Aprilyana, Dhea Putri; Priatna, Wowon; Setiawati, Siti
Jurnal Pelita Teknologi Vol 19 No 1 (2024): Maret 2024
Publisher : Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/pelitatekno.v19i1.2488

Abstract

TikTok is a popular application among young people. TikTok was an application initially launched in China before landing in Indonesia at the end of 2017. Unfortunately, the popularity of TikTok stems from personal lack of self-image, for example wearing sexy clothes, dancing in erotic and inappropriate moves. This is based on many positive and negative comments from TikTok users. So we need a way to automatically classify reviews through sentiment analysis. The purpose of this study is to classify TikTok user comments on Google Play Store using Naive Bayes and C4.5 algorithms. This study used 1330 data, of which 602 data were negative and 728 data were positive. The results show that the Naive Bayes algorithm produces accuracy values ​​of 79.00%, 79.00% precision, 78.00% recall, and 78.00% F1 score. The C4.5 algorithm produces 68.00% accuracy, 68.00% precision, 68.00% recall, and 68.00% F1 score. We can conclude that the Naive Bayes algorithm is the best algorithm compared to the C4.5 algorithm. The Naive Bayes algorithm achieves an accuracy value of 79.00%.
Algoritma First in First Out (FIFO) Untuk Perancangan Aplikasi Pemesanan Kaos Sablon Widianto, Ilham Rizky; Priatna, Wowon; Lubis, Hendarman
Jurnal Kajian Ilmiah Vol. 23 No. 2 (2023): May 2023
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/tva3pd96

Abstract

The purpose of this study is to solve the problem of screen-printing T-shirt shops. For manual screen printing t-shirt shops, customers often have to visit the store in person or contact them via chat or phone, often encountering the following issues when ordering t-shirts: B. Irregular orders for those who have placed an order in advance or who have been waiting for a long time. One way to solve the queuing problem is the FIFO algorithm. FIFO algorithms are methods for organizing, processing, and manipulating basic data structures in computer systems. The FIFO algorithm phases in this study begin with the data preparation phase, the Gantt cart process, and finally his FIFO wait time. The result of the FIFO stage translates into creating applications using the Java programming language, Android Studio, and the FireBase database. The results of this study can be applied to his FIFO algorithm for customer queues in ordering T-shirts. A t-shirt ordering application was tested using the white box method by running the test case in four passes. All tests passed, so you can use the ordering application based on the FIFO algorithm.
Perancangan Sistem Registrasi Pelayanan Pernikahan Pada KUA Pasar Minggu Jakarta Wowon Priatna; Siti Setiawati, Andika Yusuf Hidayat
Journal of Informatic and Information Security Vol. 1 No. 2 (2020): Desember 2020
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jiforty.v1i2.156

Abstract

The Office of Religious Affairs (KUA) is one of the work units of the Ministry of Religion which is tasked with fostering and providing services to the community at the sub-district level. The Pasar Minggu Subdistrict Religious Affairs Office as the government agency coordinates activities and carries out internal and cross-internal activities in the sub-district area. To that end, the Office of Religious Affairs carries out documentation of marriage statistics, builds mosques in its territory, monitors zakat, waqf, baitul maal and other social services, monitors population and develops sakinah family programs. In carrying out the registration of marriage, the KUA of Pasar Minggu Subdistrict still has shortcomings in the system for recording marriages that are carried out. The drawbacks include the manual marriage registration process, making it less effective and inefficient. The manual recording is still making marriage reports which are still recorded in the ledger, so if you want to find data, the staff will manually look for the report data. Seeing this obstacle, the authors have the idea to create a system that can process data easier and simple in use so as to save time and streamline the work of KUA staff. In this study, the authors used several stages of work, starting from the process of analysis, planning, design using the PHP programming language and MySQL database, to the implementation stage with an object-oriented approach using UML (Unified Modeling Language). The results obtained from a system that the author created can help KUA staff in inventorying marriage data, helping them also in making systemized marriage reports and in finding registrants and marriage reports to be given to the Head of the Office of Religious Affairs (KUA).
Optimizing Multilayer Perceptron with Cost-Sensitive Learning for Addressing Class Imbalance in Credit Card Fraud Detection Priatna, Wowon; Hindriyanto Dwi Purnomo; Ade Iriani; Irwan Sembiring; Theophilus Wellem
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5917

Abstract

The increasing use of credit cards in global financial transactions offers significant convenience for consumers and businesses. However, credit card fraud remains a major challenge due to its potential to cause substantial financial losses. Detecting credit card fraud is a top priority, but the primary challenge lies in class imbalance, where fraudulent transactions are significantly fewer than non-fraudulent ones. This imbalance often leads to machine learning algorithms overlooking fraudulent transactions, resulting in suboptimal performance. This study aims to enhance the performance of Multilayer Perceptron (MLP) in addressing class imbalance by employing cost-sensitive learning strategies. The research utilizes a credit card transaction dataset obtained from Kaggle, with additional validation using an e-commerce transaction dataset to strengthen the robustness of the findings. The dataset undergoes preprocessing with RUS and SMOTE techniques to balance the data before comparing the performance of baseline MLP models to those optimized with cost-sensitive learning. Evaluation metrics such as accuracy, recall, F1 score, and AUC indicate that the optimized MLP model significantly outperforms the baseline, achieving an AUC of 0.99 and a recall of 0.6. The model's superior performance is further validated through statistical tests, including Friedman and T-tests. These results underscore the practical implications of implementing cost-sensitive learning in MLPs, highlighting its potential to significantly enhance fraud detection accuracy and offer substantial benefits to financial institutions.
The Effects of Data Sampling and Feature Selection on Public Service Satisfaction Using an Ensemble Classifier Algorithm Priatna, Wowon
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4533

Abstract

Customer satisfaction is an important factor that determines quality. User satisfaction analysis can identify the service quality and measure quality through an evaluation process to improve services. This research aims to measure the performance of services provided by the village government. Villages and sub-districts offer services based on the community's specific needs. Nevertheless, by delivering impeccable service, it is possible to satisfy the community without causing physical or material harm. An essential requirement is the development of a service user classification methodology to enhance service quality, efficiently address service user grievances, detect recurring trends, and promptly offer feedback to enhance the offerings of products and services. Machine learning approaches can be used to quantify public service satisfaction in the analytical process. Machine learning is an algorithmic approach used to assess and prioritize satisfaction with public services offered by service providers. The main approach for machine learning is an ensemble classifier. The data was analyzed using Excel; then, the data was processed first to create a classification model. At the preprocessing stage, the data is grouped to obtain labels/targets to be processed based on algorithmic classification. The classification uses the Classifier aggregation algorithm. Type improvements using optimization features using the Particle Swarm Optimization (PSO) sampling algorithm and random subsampling techniques. This research produced an accuracy value before adding sampling techniques and a PSO accuracy value of 92.68. After adding sampling techniques and PSO optimization, an accuracy value of 100% was obtained
Perancangan Dan Implementasi Sistem Monitoring Arus Listrik Berbasis Iot Dengan Algoritma Moving Average Dan Thingspeak Dimas Abimanyu Prasetyo; Joni Warta; Wowon Priatna
Indonesian Journal of Education And Computer Science Vol. 3 No. 2 (2025): INDOTECH - August 2025
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/indotech.v3i2.1416

Abstract

Berdasarkan data PLN, gangguan kelistrikan di wilayah perumahan meningkat sebesar 12%, sementara pembelian energi oleh pembangkit listrik naik sebesar 6% dibandingkan tahun sebelumnya. Sebagian besar gangguan disebabkan oleh ketidakstabilan arus listrik serta penggunaan peralatan rumah tangga secara bersamaan tanpa manajemen beban memadai. Pada tahun 2024, tingkat susut energi tercatat 8,55%, terdiri atas susut transmisi 2,03% dan susut distribusi 6,65%, menunjukkan bahwa pengelolaan energi yang efisien masih menjadi tantangan. Tujuan penelitian ini adalah merancang sistem yang mampu mendeteksi dan memantau faktor daya secara real-time, mengukur dan mencatat nilai energi listrik secara akurat dan real-time, serta merancang platform berbasis IoT untuk monitoring arus listrik. Penelitian dilakukan di lingkungan rumah tangga nyata, dengan penyesuaian lokasi dan waktu untuk mendukung proses pengambilan data. Hasil menunjukkan sistem berhasil mengirimkan data arus, daya, dan energi dengan interval 15 detik. Sensor PZEM-004T menunjukkan akurasi tinggi. Metode Simple Moving Average (SMA) juga memberikan hasil akurat dalam menghitung total daya. Sistem IoT yang dirancang mampu memantau penurunan faktor daya secara real-time serta mencatat energi yang digunakan. Melalui platform ThingSpeak, sistem menyediakan informasi arus listrik yang berguna bagi pengguna rumah tangga untuk mengelola konsumsi energi secara efisien.
Deteksi Anomali dalam Penipuan E-commerce Menggunakan Hybrid Autoencoder-Transformer Frameworks Priatna, Wowon; Prasetyo, Sri Yulianto Joko; Wijono, Sutarto; Maria, Evi; Manongga, Danny
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 11, No 1 (2025): Volume 11 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v11i1.82330

Abstract

Peningkatan e-commerce telah menyebabkan peningkatan aktivitas penipuan, seperti pencurian identitas dan transaksi palsu, yang menimbulkan risiko signifikan terhadap keamanan transaksi online. Penelitian ini mengusulkan kerangka kerja hybrid yang menggabungkan Autoencoder (AE) untuk reduksi dimensi dan representasi laten data, serta Transformer untuk menangkap ketergantungan global dan lokal melalui mekanisme self-attention. Pendekatan ini dirancang untuk mengatasi keterbatasan metode tradisional dalam mendeteksi pola data kompleks dan meningkatkan kinerja deteksi anomali. Evaluasi menggunakan dataset transaksi e-commerce menunjukkan bahwa Hybrid AE-Transformer mencapai akurasi sebesar 95,2%, precision sebesar 89,0%, recall sebesar 74,0%, F1 score sebesar 80,0%, dan AUC sebesar 82,0%. Model ini menunjukkan peningkatan precision sebesar 12,0%, recall sebesar 7,0%, F1 score sebesar 8,0%, dan AUC sebesar 1,0% dibandingkan model terbaik lainnya seperti Ensemble. Validasi statistik melalui Uji Friedman dan Uji T-Test mengonfirmasi bahwa Hybrid AE-Transformer secara signifikan mengungguli model konvensional seperti DNN, LSTM, dan RNN dalam mendeteksi anomali pada transaksi e-commerce.
Implementasi Deep Learning Untuk Rekomendasi Aplikasi E-learning Yang Tepat Untuk Pembelajaran jarak jauh Priatna, Wowon; Purnomo , Rakhmat; Putra , Tri Dharma
Jurnal Kajian Ilmiah Vol. 21 No. 3 (2021): September 2021
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (554.294 KB) | DOI: 10.31599/jki.v21i3.521

Abstract

The purpose of this study is to recommend e-learning applications that are appropriate for use in online learning in college environments. The large number of e-learning platforms used by lecturers for online lecture activities results in students being forced to use several e-learning applications depending on the lecturer who teaches the courses taken, for the university also finally gives lecturers policies for distance learning reports each finished giving the material. In this study the data collection method began by taking data from the faculty to find out which e-learning applications were widely used by lecturers, then distributing questionnaires to students and lecturers who used the e-learning application to measure the e-leaning application with the e-learning criteria. Appropriate. The data is then processed into a dataset. The algorithm used in implementing deep learning is Artificial Neural Network (ANN). For the implementation of ANN, 27 variables were determined from the e-learning criteria and 1 target. In this ANN stage, prediction was used with classifications based on preparation, training, learning, evaluation and prediction using the python programming. The results obtained in this study that the Moodle application gets the highest score with an accuracy of 97% to be used as a recommendation for e-learning applications that are appropriate for universities to conduct online lectures.
Pelatihan Talents Mapping Pada Guru-Guru SMK Negeri 11 Bekasi Priatna, Wowon; Purnomo, Rakhmat; Fadjriya, Andry; Kustanto, Prio
Journal Of Computer Science Contributions (JUCOSCO) Vol. 2 No. 1 (2022): Januari 2022
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/27aesk67

Abstract

Talents Mapping is an application tool for recognizing one's talents based on 34 talent themes adopted from Gallup's research, so that someone can also find out their personal strength and typology's strength. Talend mapping training is motivated by a request from the leadership of SMK Negeri 11 Bekasi so that teachers can get to know their respective talents so that in teaching and educating students more optimally and teachers after receiving this activity can teach back to their students. This training begins by recording teachers' emails to create a classroom account to ask preliminary aptitude test questions and share material. The training was conducted at the Computer Lab of SMK Negeri 11 on 12 July 2020 with 46 teachers participating. The results of the training for teachers using the lecture method, filling out the instruments, and comments from resource persons. The teachers fill in the questions about themselves at www.temubakat.com, then the answers are mapped using talents mapping to find out the potential talents of each teacher.
Co-Authors -, Rasim ., Rasim Ade Iriani Adi Setiawan Aditiya Dwi cahyo Afina Putri Dzulqiyana Agung Nugroho Agung Nugroho Agus Hidayat Agus Hidayat Agus Hidayat Aida Fitriyani, Aida Ajif Yunizar Pratama Yusuf Alexander, Allan D Alhillah, Yumaris Alfi Andi Lawrence Hutahaean, Johanes Andi Rahman Andri Fajriya Andy Achmad Hendharsetiawan Annisa Oktavianti Hermadi Aprilyana, Dhea Putri Asep R. Hamdani Asep Ramdhani M Atika , Prima Dina Danny Manongga Dimas Abimanyu Prasetyo Dwi Budi Srisulistiowati Dwipa Handayani Eka Nur A’ini Endah Prawesti Ningrum Endang Retnoningsih Enggar Putera, dkk, Diaz Evi Maria Fadjriya, Andry Faisal Adi Saputra Fajar Mukharom Fathurrazi, Ahmad Febry Sandrian Sagala Fefbiansyah Hasibuan Galih Apriansha Pradana Hadi Kusmara Hamdani, Asep R. Hendarman Lubis Herlawati Herlawati Hernowo, Pandit Hindriyanto Dwi Purnomo Ikhsan Romli Ilham Rizky Widianto Irwan Sembiring Ismaniah, Ismaniah Iwan Setyawan Joni Warta Joni Warta Joniwarta Joniwarta Jumi Saroh Hidayat Kapriadi, Engkap Karyaningsih, Dentik Khoirunnisaa, Nabiilah Kustanto , Prio Lestari, Tyastuti Sri Lubis, Hendarman M. Fadhli Nursal Mahbub, Asep Ramdhani Manrejo, Sumarno Mayadi Mayadi Mayadi, Mayadi Meutia, Kardinah Indrianna Mugiarso Mugiarso, Mugiarso Muhammad Khaerudin Noe’man,, Achmad Nurjeli Nurjeli Pasaribu, Ahmad Muchlisin Natas Pradana , Galih Apriansha Prima Dina Atika Purnomo , Rakhmat Purnomo, Rakhmat Purnomo, Rakhmat Putra , Tri Dharma Rahmadya Trias Handayanto Rakhmat Purnomo Rasim Rasim Regita Ari Rahmadanti Rejeki , Sri Rinaldi Tunnisia Ritzkal, Ritzkal Sagala, Febry Sandrian Saputra , Faisal Adi Silvi - Siti Setiawati Siti Setiawati SITI SETIAWATI Siti Setiawati, Andika Yusuf Hidayat Sri Lestari, Tyastuti Sri Rejeki Sri Yulianto Joko Prasetyo Sudiantini, Dian Sulistiyo, Dwi Suryadi Sutarto Wijono Syahbaniar Rofiah Tb Ai Munandar, Tb Ai Theopillus J. H. Wellem Tri Dharma Putra Tri Dharma Putra Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Widianto, Ilham Rizky Wiyanto Wiyanto Zahra, Nurul