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All Journal ComEngApp : Computer Engineering and Applications Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) Format : Jurnal Imiah Teknik Informatika Jurnal Informatika Faktor Exacta Jurnal Pengabdian Pada Masyarakat ILKOM Jurnal Ilmiah IJISCS (International Journal Of Information System and Computer Science) Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Pengabdian Masyarakat Asia Computer Science (CO-SCIENCE) Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia Journal of Systems Engineering and Information Technology Hexagon Jurnal Pengabdian Masyarakat Nasional IJISCS (International Journal of Information System and Computer Science)
Wawan Gunawan
Universitas Mercu Buana
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences Other

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Pemanfaatan Algoritma K-Means dalam Klasterisasi Gempa Sulawesi Wibowo, Arief; Gunawan, Wawan
Faktor Exacta Vol 17, No 3 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i3.23169

Abstract

Indonesia is a region that frequently experiences earthquakes, especially in the Sulawesi area which has significant active faults. Sulawesi is an area that has quite high seismic intensity, and there are several active faults which are earthquake source zones. This study uses M-Means with a total of 9,710 records starting from 2019-2023 and the attributes consist of event_id, date_time, latitude, longitude, magnitude, mag_type, depth_km, phase_count, azimuth_gap, location, agencydengan. This data processing compares magnitude and depth consisting of 3 clusters, namely 51-132 Km depth with a total of 1,311, 3-50 Km depth with a total of 7,527, 133-300 Km depth with a total of 872, while the process with magnitude, depth and azimuth gap attributes consists of 4 clusters with each cluster respectively 3,957, 1,546, 1,458, and 2,749. By using a different set of input features, this research identifies that the results from 3 clusters or 4 clusters indicate that the province of South Sumatra shows a high level of earthquake proneness and frequent frequency in all clusters with the epicenter of the earthquake being in the Maluku Sea, between South Sulawesi with Southeast Sulawesi, as well as the province of Gorontalo. Based on the results obtained, there is a need for early prevention related to disasters, especially earthquakes that occurred on the island of Sumatra based on earth faults that run through the island..
Kombinasi algoritma base64 dan caesar cipher pada aplikasi Devianto, Yudo; Gunawan, Wawan; Sukowo, Bambang; Susafaati, Susafaati
Faktor Exacta Vol 17, No 1 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i1.20680

Abstract

Digital information systems must also pay attention to data security because it is confidential, there are many problems with data security which result in loss of data or damage caused by irresponsible parties. This research will combine the BASE64 and CAESAR CIPHER algorithms in applications to maintain the security of financial data so that it cannot be seen by users who do not have access to the application. The system development in this research looks like in Figure 1 which uses the Extreme Programming method. The testing carried out was using Black box and white box testing which produced the same cyclomatic complexity value, namely 4. So it can be concluded that the system is running well because the testing produces the same value
Imbalanced Data NearMiss for Comparison of SVM and Naive Bayes Algorithms Gunawan, Wawan; Devianto, Yudo; Sari, Anggi Puspita
Computer Engineering and Applications Journal Vol 13 No 03 (2024)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v13i03.485

Abstract

The study aims to improve the diagnosis, management, and prevention of HIV/AIDS by using classification algorithms. The dataset used consists of 707,379 records and 89 columns. Data preprocessing includes removing irrelevant attributes, handling inconsistencies, and balancing the data using the NearMiss method, resulting in a balanced proportion of reactive and non-reactive HIV cases. Once the data is balanced, it is split into several ratios: 60:40, 70:30, 80:20, and 90:10. The classification models used in this study are Naive Bayes and SVM. The models are evaluated using the metrics Accuracy, Precision, Recall, and F1-Score. The results show that the SVM model achieves the highest accuracy of 82.6% with a 90:10 data split at a 6-fold value, and 82.2% with a 60:40 data split at a 5-fold value. On the other hand, Naive Bayes achieves the highest accuracy of 61.1% with a 60:40 data split.
Implementasi Rekomendasi Content Based Filtering dan Apriori Berbasis Android Mardani, Latif Dwi; Gunawan, Wawan
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 2 (2024): Volume 10 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i2.74383

Abstract

Proban Motoparts merupakan sebuah toko retail dan jasa yang bergerak dibidang otomotif dengan menjual beberapa produk suku cadang untuk sepeda motor. Banyaknya variasi produk yang ada di Proban Motoparts, membuat pelanggan merasa kesulitan saat memilih produk yang dibutuhkan. Solusi dari kendala tersebut adalah dengan implementasi sistem rekomendasi produk yang dapat memudahkan pelanggan mendapatkan produk yang mereka butuhkan. Sistem rekomendasi ini menggunakan data histori penjualan manual di salah satu toko Proban Motoparts, dengan total jumlah data transaksi sebanyak 5 transaksi. Implementasi sistem rekomendasi content-based filtering menggunakan algoritma apriori ini untuk menghasilkan produk dengan nilai support tertinggi yang akan direkomendasikan kepada pelanggan. Aplikasi rekomendasi ini memudahkan pelanggan dalam memesan berbagai kebutuhan suku cadang motor yang mereka butuhkan cukup menggunakan perangkat android, hasil persentase pilihan pelanggan diketahui hingga 50.79% memilih sangat setuju dan 35.19% memilih setujuberdasarkan hasil kuesioner dengan 42 responden yang bersedia, dan sebanyak 87.09% merasa puas dengan sistem rekomendasi produk ini.
Deteksi Email Spam menggunakan Algoritma Convolutional Neural Network (CNN) Bachri, Chris Moulana; Gunawan, Wawan
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 1 (2024): Volume 10 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i1.73306

Abstract

Deteksi email spam merupakan isu penting dalam keamanan siber di Indonesia, yang menempati posisi delapan teratas di dunia dalam hal pengiriman spam. Untuk mengatasi tantangan ini, penelitian ini memperkenalkan penggunaan algoritma Convolutional Neural Network (CNN). Dengan kemampuan superior dalam mempelajari dan mengenali pola dari dataset besar, CNN menawarkan pendekatan berbasis kecerdasan buatan yang lebih efektif daripada metode tradisional. Penelitian ini mengembangkan model CNN dengan menganalisis teks dari 15.271 email berbahasa Inggris dan Indonesia dengan menggunakan teknik pembersihan teks dan Tokenization. Hasilnya menunjukkan keefektivitasan CNN yang signifikan dalam mengklasifikasikan email dengan tingkat akurasi tinggi sebesar 99.67% untuk data uji 20%, 99.64% untuk data uji 30%, dan 99.63% untuk data uji 40%. Berdasarkan hasil pengujian tersebut menunjukkan bahwa algoritma CNN berpotensi kuat dalam meningkatkan keamanan digital.
Penentuan mahasiswa berprestasi menggunakan algoritma FP-Growth dan SAW Ridwan, Wawan; Gunawan, Wawan
Faktor Exacta Vol 17, No 3 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i3.23936

Abstract

This research discusses the importance of utilizing technology in inventory management and student achievement determination. The transformation from manual systems to computerized systems has proven to increase efficiency and accuracy. In determining outstanding students, the criteria used often focus solely on academic aspects, neglecting other skills such as leadership and creativity. This study proposes the use of the FP-Growth and Simple Additive Weighting (SAW) algorithms to address this issue. FP-Growth is used to identify high-frequency patterns in student achievement data, while SAW assigns weights to each criterion variable for more accurate decision-making. The criteria for assessment include GPA, student achievements, study duration, and activity participation. The implementation is expected to provide a more effective solution in determining outstanding students and managing inventory. The FP-Growth method helps identify significant patterns in transaction data, while SAW assists in ranking alternatives based on specified criteria. This research demonstrates that the combination of these two algorithms can improve accuracy and efficiency in inventory management and student achievement determination, providing a competitive advantage for institutions. Based on the research results, the ranking of outstanding students is led by student C, followed by student B, with respective scores of 0.8875 and 0.825.
Pemanfaatan Chi Square dan Ensemble Tree Classifier pada Model SVM, KNN dan C4.5 dalam Penjualan Online Indriyanti, Prastika; Gunawan, Wawan
Faktor Exacta Vol 17, No 3 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i3.24149

Abstract

This research aims to assist MSMEs in overcoming problems in online sales. Currently, sellers only prepare stock without knowing how well the products are sold in their market segment. In the city of Tangerang alone, there are 222,602 MSMEs with various product categories. Therefore, besides utilizing offline sales, business actors should also engage in online sales. This research conducts feature selection using the Chi-Square method and Ensemble Tree Classifier to select the top 6 and 10 features. The SVM, KNN, and C4.5 algorithms are used to build prediction models based on the selected features. Using feature selection, it was found that the influential features are Estimated Shipping Cost, Shipping Cost Paid by Buyer, Total Product Price, and Estimated Shipping Cost Discount. The evaluation results using the three algorithms, SVM, KNN, and C4.5, indicate that the highest accuracy value is obtained when using the C4.5 model with data from the ensemble tree classifier with 6 features at 0.86%, followed by the C4.5 model with 10 features, KNN with 6 features, and KNN with 10 features, all of which source data from the ensemble tree classifier with an accuracy value of 0.85%.
Pemodelan Penentuan Pupuk Menggunakan Metode AHP dan SAW Eliyani, Eliyani; Gunawan, Wawan; Wahyuningram, Nugroho; Triyono, Gandung
Faktor Exacta Vol 17, No 3 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i3.24580

Abstract

The dataset used in this study comprises criteria and fertilizer brands for rice, based on assessments conducted by farmers. The criteria were: price (C1), product (C2), quality (C3), quantity (C4), recommendation (C5), effectiveness (C6), and suitability (C7). Each criterion is weighted as Very Good (4), Good (3), Fair (2), and Poor (1). The evaluated fertilizers consisted of 15 brands: Nitrea, Caping Tani, Pertiphos, NPK padi kuning, SP 36, Meroke, Pusri, Nitroku, Ponska, ZA, Urea, and NPK Pak Tani. The assessments were carried out by distributing questionnaires to 50 farmers who shop at Cv. Sari Alam Tani Store, where farmers could select more than one brand of fertilizer. The most chosen fertilizer by the farmers was Urea. This study aims to verify if Urea is indeed the best fertilizer using the AHP and SAW algorithms based on the established criteria. The results indicate that NPK Padi Kuning was ranked first with a score of 1.72, followed by NPK Tawon and NPK Pak Tani with scores of 1.61 and 1.40, respectively. Urea, despite being the most chosen by farmers, ranks fourth with a score of 1.25.
APPLICATION ARABIC LEARNING BASED ON MULTIMEDIA USING ASYNCHRONOUS METHOD Wawan Gunawan
IJISCS (International Journal of Information System and Computer Science) Vol 4, No 2 (2020): IJISCS (International Journal Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v4i2.894

Abstract

Every school has different featured programs but it has similar goals to educate the nation based on faith and piety on Quran and As-Sunnah. Daily conversation will often be used between the school and the student's parents, both basic and later. To obtain maximum results in the learning process, it is necessary to use Arabic communication between the parents and the students outside the school. There are Parents difficulties to speak Arabic daily conversation to support the teaching and learning process at school and home. There is a deadlock between parents and students due to parents' lack of understanding in Arabic. How to helping the realization of the Arabic learning process given to students outside the school environment by repeating the learning process with parents with multimedia application tools and building Arabic learning applications by using asynchronous based multimedia applications.
DESIGNING CHATBOT FOR COLLEGE INFORMATION MANAGEMENT Herry Derajad Wijaya; Wawan Gunawan; Reza Avrizal; Sutan M Arif
IJISCS (International Journal of Information System and Computer Science) Vol 4, No 1 (2020): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v4i1.826

Abstract

Information plays an important role in human daily life in which it is expected to be more understood, fast, clear and accurate. In line with technology development and the mission of Informatics study program to develop its services for college students, that is, information is derived through information systems and chat. Students in this case is whom study at the university, institution or academy. This study aims to create Chatbot as Virtual Assistant that provides information for college students through data stored on the system which contains Informatics study program and new information if the data is not founded. Chatbot is a computer program designed to socialize interactive conversations or communication to users (humans) through a text, sound and visual. Through this application, they are able to communicate for various pratical purposes such as customer service, information acquisition and a value of digital campus with integrated information system. Thus, Chatbot with artificial intelligence eases users to obtain information quickly and precisely. 
Co-Authors Achmad Santoso Agung Lesmana Anggi Puspitasari, Anggi Bachri, Chris Moulana Bambang Sukowo Desi Ramayanti Desti Listiani Devi Fitrianah Diwiryo, Bagus Seno Prasetyo Dwiki Jatikusumo Dwityo Fauzan Nugroho Eliyani Eliyani Eliyani, Eliyani Eugenius Kau Suni Faishal, Imam Ibnu Fajar Rizky Firmansyah, Muhammad Riski Herry Derajad Wijaya Herry Derajad Wijaya Hery Derajad Wijaya Hidayat, Rahmat Rian Ibrahim Mahardika Seno Indriyanti, Prastika Ivan Anggriawan Mardani, Latif Dwi Misbah Ramadani Muhamamd Valensyah Alfansyuri Muhammad Riski Firmansyah Muhammad Yusuf Rizqon Rangkuti Novia Nurrohmah Reza Avrizal Rias Akmal Sembiring Ridwan, Wawan Sari, Anggi Puspita Saruni Dwiasnati Susafaati SUF Susafaati, Susafaati Sutan M Arif Triyono, Gandung Wahyuningram, Nugroho Wibowo, Arief Yudo Devianto