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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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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%.
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
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.
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.
Penerapan Aplikasi Pelayanan Desa untuk Implementasi Smart Village di Desa Mangunjaya Mayadi, Mayadi; Priatna, Wowon; Setiawati, Siti
Journal Of Computer Science Contributions (JUCOSCO) Vol. 3 No. 1 (2023): Januari 2023
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/ja811v22

Abstract

Desa Mangunjaya , which is located at Jalan Pendidikan 1 No.13 Mangunjaya, South Tambun District, Bekasi, West Java 17510, is still developing information technology. This village in conveying information is still done manually so that the potential of the village is less published, with that the village community still has difficulty receiving information from the village government and conveying various suggestions and aspirations of the community. In conveying information it is still done manually so that the potential of the village is not published. The problem faced by Mangunjaya village is that the community has difficulty in getting information and complaints in conveying aspirations to the village. The making of certificates is still carried out by the community directly to village officials. The goal in this PKM is to implement a smart village to make the village digitized by designing the Village Service application to make it easier to submit letters from villagers. The method in Community Service is to design an application and conduct socialization for the use of the Application to the community, RT, RW and Village Officials. The result of this PKM is that the Village service application to support Smart Village can be used and training has been carried out for using the Application.
Pendampingan Implementasi Sistem Informasi Desa Untuk Meningkatkan Efisiensi Pelayanan Administrasi Dan Tata Kelola BUMDes Manrejo, Sumarno; Ningrum, Endah Prawesti; Priatna, Wowon; Hernowo, Pandit; Pasaribu, Ahmad Muchlisin Natas; Endah Prawesti Ningrum
Jurnal Pengabdian kepada Masyarakat UBJ Vol. 8 No. 2 (2025): Juni 2025
Publisher : Lembaga Penelitian Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/6mwtdp28

Abstract

Digital transformation at the village level is essential to improve the efficiency of public services and strengthen local economic management. However, many villages still rely on manual administrative processes and conventional business management systems for Village-Owned Enterprises (BUMDes). This community service activity aimed to implement a Smart Village application integrated with BUMDes management in Neglasari Village, Sumedang Regency. The program was carried out through several stages, including socialization, training, technology implementation, mentoring, and evaluation. The implemented system integrates three main components: digital village administration services, integrated BUMDes and MSME management, and digital promotion of village products. The results show that the application improved administrative service efficiency, reducing service time from 15–20 minutes to 5–7 minutes per request. In addition, the system reduced administrative recording errors and enabled real-time monitoring of BUMDes transactions and financial reports. Training activities also increased participants' understanding of system usage, with an average score of 4.3 on a five-point scale. Overall, the implementation of the Smart Village application contributes to improving service efficiency, strengthening village business management, and supporting sustainable digital transformation in Neglasari Village
Implementasi Fuzzy Logic Pada Sistem Kontrol pH Air Mineral Berbasis IOT Joniwarta; Priatna, Wowon; Hamdani, Asep R.; Alexander, Allan D.
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): 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.v12i4.3356

Abstract

Implementation of Fuzzy Logic in the IOT-Based Mineral Water pH Control System for various existing bottled mineral water products, this system can measure the pH value, to find out if the value is still within the limits suitable for consumption or not based on government regulations. The public finds it challenging to understand the level of the pH value of the product because the current state of information regarding the pH level of mineral water generally is not listed in the mineral water bottle circulating on the market. Hardware design, application design, and hardware and software integration were the three steps of this research project. The pH value will be read by this control system from the output of the sensors then the data is collected into a data set. The data will be examined for trends using fuzzy logic, which will be used to classify the maximum and minimum pH levels, acidity levels, and base levels. The study's findings show that an internet-based web of things can access the mineral water pH control system to ascertain each mineral water product's pH value and temperature. This information can then be used by consumers to ascertain the pH level of each mineral water product.
Particle Swarm Optimization Untuk Optimasi Klasifikasi Tingkat Kepuasan Layanan Publik Priatna, wowon
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3441

Abstract

Tujuan dari penelitian ini adalah untuk mengetahui tingkat kepuasan terhadap pelayanan yang diberikan oleh pemerintah daerah sebagai penyedia layanan publik dengan mengklasifikasikan data yang diperoleh dari survei yang dilakukan. Saat ini desa dan kelurahan telah memberikan pelayanan sesuai kebutuhan masyarakat, namun jika tidak sepenuhnya memberikan pelayanan yang optimal maka dapat menimbulkan ketidakpuasan dan merugikan masyarakat baik secara fisik maupun materil. Untuk meningkatkan kualitas layanan dan menyelesaikan keluhan pengguna layanan secara efektif, mengidentifikasi pola dan memberikan umpan balik yang tepat waktu untuk meningkatkan produk dan layanan yang diberikan, diperlukan metode klasifikasi pengguna layanan. Metode pengumpulan data pada penelitian ini menggunakan metode survei dengan menyebarkan kuesioner kepada masyarakat pengguna layanan publik di desa dan kelurahan. Data yang diperoleh dianalisis menggunakan Excel untuk mengolah data terlebih dahulu untuk membuat model klasifikasi. Pada tahap prepROCessing, data dikelompokkan untuk mendapatkan label/target sehingga data tersebut dapat diolah menggunakan algoritma klasifikasi. Klasifikasinya menggunakan algoritma Decision Tree (DT), Naïve Bayes, Support Vector Machine (SVM), K-Nearest Neighbor (KNN). Tingkatkan klasifikasi dengan pengoptimalan fitur menggunakan Particle Pool Optimization (SPO). Penelitian ini menghasilkan nilai akurasi tertinggi pada klasifikasi pohon keputusan dengan mendapatkan nilai akurasi tertinggi sebesar 97,74%, disusul algoritma KKN memperoleh akurasi sebesar 77,90%, algoritma Naïve Bayes sebesar 64,4% dan algoritma yang memperoleh nilai akurasi terkecil adalah algoritma SVM. yaitu 59,90%. Setelah dilakukan optimasi, nilai akurasi tertinggi terdapat pada algoritma SVM dan algoritma KNN sebesar 98,3%, pohon keputusan sebesar 97,77%, dan akurasi terkecil pada algoritma Naïve Bayes sebesar 69,30%.
Co-Authors -, Rasim Ade Iriani Adi Setiawan 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 Anisya Wulandari Annisa Oktavianti Hermadi Aprilyana, Dhea Putri Asep R. Hamdani Asep Ramdhani M Asep Ramdhani Mahbub Asep Ramdhani Mahbub Atika , Prima Dina Danny Manongga Dimas Abimanyu Prasetyo Dwi Budi Srisulistiowati Dwipa Handayani Dzulqiyana, Afina Putri 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 Hendharsetiawan, Andy Achmad Herlawati Herlawati Hernowo, Pandit Hindriyanto Dwi Purnomo Ikhsan Romli Ilham Rizky Widianto Irwan Sembiring Ismaniah Ismaniah Ismaniah, Ismaniah Iwan Setyawan Joni Warta Joni Warta Joniwarta Joniwarta Jumi Saroh Hidayat Kapriadi, Engkap Karyaningsih, Dentik Khoirunnisaa, Nabiilah Kustanto , Prio Lestari, Tyastuti Sri M. Fadhli Nursal Manrejo, Sumarno Mayadi Mayadi Mayadi, Mayadi Meutia, Kardinah Indrianna Mugiarso Mugiarso, Mugiarso Muhammad Khaerudin Muhammad Yasir Noe’man,, Achmad Nurjeli Nurjeli Pasaribu, Ahmad Muchlisin Natas Pradana , Galih Apriansha Prima Dina Atika Purnomo, Rakhmat Purnomo, Rakhmat Rahmadanti, Regita Ari Rahmadya Trias Handayanto Rakhmat Purnomo Rasim Rasim Rasim . Rasim Rasim 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 Tia Aulia Tri Dharma Putra Tri Dharma Putra Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Wiyanto Wiyanto