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All Journal Dinamik Techno.Com: Jurnal Teknologi Informasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Brilliance: Research of Artificial Intelligence Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian Cahaya Pengabdian Welfare: Jurnal Pengabdian Masyarakat
Siswandi, Arif
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Prediction of Employee Assessments for Contract Extensions at PT Sagateknindo Sejati Using the Naïve Bayes Algorithm Naya, Candra; Siswandi, Arif; Butsianto, Sufajar; Febriyanti, Febriyanti
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4170

Abstract

Companies must be selective in conducting employee assessments in order to retain employees with the best performance. When assessing employee performance, it is seen from their perseverance and discipline. However, in reality, good employee performance sometimes gets bad reviews and even gets reprimanded by their superiors. This is caused by the employee assessment monitoring system used, namely only personal assessment without using an assessment system and the data collected is less than optimal. This research uses the Naive Bayes method to process data using a data mining algorithm to obtain predictions that can be used as additional references in making employee performance assessment decisions. Aims to predict employee assessments of contract extensions at PT Sagateknindo Sejati. This research is important because it helps in making more accurate decisions regarding employee contract extensions based on existing historical data. Naive Bayes is a data processing algorithm that is classified as a calculation that is easy to understand but its accuracy results are reliable. It is used because it is efficient in managing data with various attributes and is able to produce predictions based on the probability of each existing attribute. The data used in this research includes various variables, using the Rapidminer supporting application to test the accuracy of the system created. Testing was carried out by preparing 320 data and testing 50 randomly selected data. Test data will be analyzed using the Rapidminer supporting application. The test results produced an accuracy of 83.96%.
Application of the C 4.5 Algorithm to Classify Customer Characteristics at PT. Bayer Indonesia Siswandi, Arif; Anwar, M. Syaibani; Susilo, Arif; Hasibuan, Sultan
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4174

Abstract

PT. Bayer Indonesia is a company engaged in drug production. In running its business, companies need to know customer characteristics in determining what actions to take next. This research aims to apply the C 4.5 algorithm in classifying customer characteristics at PT. Bayer Indonesia. The C 4.5 algorithm is a decision tree algorithm that is often used in data mining for classification purposes. This research was conducted to make it easier to find out customer characteristics. Starting with collecting data, then selecting the attributes that will be used. Then the data is separated using split data, the initial comparison used is 60% train data and 40% test data. Then training data is carried out using the C4.5 algorithm. Next, the classification results were evaluated using the confusion matrix method. The data used was 200 data with 9 attributes, obtained an accuracy of 86.25%, precision of 86.25% and recall of 54.55%. Then change the data split parameters to 70% : 30%, 80% : 20% and 90% : 10%. The best accuracy is 100%. The research results show that the C 4.5 algorithm has good performance in classifying the characteristics of PT customers. Bayer Indonesia. The resulting model can be used by companies for more effective marketing strategies and personalized customer service.
Analysis Prediksi Wilayah Rawan Banjir dengan Algoritma K-Means Effendi, Muhammad Makmun; Inka, Inka; Siswandi, Arif
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4770

Abstract

Along with the high amount of rainfall in Bekasi -West Java, floods have started to inundate several areas of Bekasi , one of the causes is the high rainfall factor. According to (Regional Disaster Management Agency) BPBD, the most flood points are in the Bekasi area, causing several activities of the surrounding community to be disrupted, transportation hampered, and also the emergence of disease problems such as skin diseases, diarrhea, and so on. The problem of flooding is a shared responsibility that requires a solution. also the role of technology to help facilitate the provision of information to the public regarding flood-prone areas in the Bekasi area. One technique that can be used is using the K-Means Clustering Algorithm to group flood-prone areas. The flood dataset was processed using the RapidMiner application, for the dataset taken to carry out this analysis from January to December 2022, there were 24 data from areas affected by flooding from various sub-districts and villages in the city of Bekasi. The results of the research produced 3 clusters, namely, the high flood, medium flood and low flood categories, which received a Davies Bouldin index value of -0.452.
Pelatihan dan Pendampingan Learning Management System (LMS) Pada SMK Negeri 1 Tambelang Kabupaten Bekasi Fauzi, Ahmad; Miharja, Muhammad Najamuddin Dwi; Siswandi, Arif; Wangsadanureja, Miftah; Maulana Majid, Annisa
Welfare : Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2023): Welfare : March 2023
Publisher : Fakultas Ekonomi dan Bisnis Islam, IAIN Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/welfare.v1i1.334

Abstract

The industrial revolution 4.0 has an impact on every field, one of which is the development of the world of education. Developments in the world of education can be seen in learning methods, including teaching and learning processes that are currently easily accessible for teachers and students. In the field of education, new learning methods such as the Moodle-based Learning management system are used to facilitate the teaching and learning process, but there is no implementation of a learning management system to manage online learning activities at SMK Negeri 1 Tambelang, Bekasi Regency. In this service, the implementation of the learning management system was carried out at SMK Negeri 1 Tembelang, Bekasi Regency. The Learning Management System is proven to facilitate the teaching and learning process for teachers and students at SMK Negeri 1 Tambelang, Bekasi Regency.
Implementasi K-Means Clustering Berbasis RapidMiner untuk Optimalisasi Segmentasi Penjualan Produk dalam Meningkatkan Efektivitas Strategi Pemasaran Butsianto, Sufajar; Siswandi, Arif
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8439

Abstract

The Indonesian electronic retail industry is experiencing rapid growth along with digital transformation. However, available sales data is often only stored as transaction records without further analysis, so it has not been optimally utilized for marketing decision making or customer segmentation. This study aims to implement the RapidMiner-based K-Means Clustering algorithm to analyze segmentation patterns of electronic products at XYZ Store. The dataset used includes the variables Transaction_ID, Product_ID, Product_Name, Category, Quantity, Unit_Price, Revenue, and Recency. The research stages include data collection, preprocessing (filtering, aggregation, and Z-Score normalization), K-Means application, and interpretation of clustering results. Determination of the number of clusters in this study uses the Elbow Method, which shows an optimal point at K = 3, so that number of clusters is chosen for the data grouping process. Based on the results of the application of the K-Means algorithm with the three clusters, the following are obtained: (1) Cluster 0 (High Sales & High Revenue) consisting of Smartphones, Laptops, and Tablets as superior products with a contribution of almost 60% of total revenue; (2) Cluster 1 (Medium Sales & Moderate Revenue) includes Televisions, Refrigerators, and Smartwatches with a stable contribution of around 27%; and (3) Cluster 2 (Low Sales & Low Revenue) contains Washing Machines, Speakers, Headphones, and Printers with a low contribution of only 14%. These findings provide a strategic basis for management in making business decisions, such as procurement priorities, seasonal promotions, product bundling, and clearance strategies. This study proves that the application of data mining with K-Means Clustering is effective in increasing operational efficiency and supporting the competitiveness of the electronics retail business in Indonesia.
Pendampingan Pembuatan Sistem Keamanan Jaringan Menggunakan Firewall Open Source Di SMK Garuda Nusantara Siswandi, Arif; Soejarminto, Yos; Rilvani, Elkin; Muktiali, Saiful
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 3 No. 2 (2025): Desember 2025
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v3i2.166

Abstract

The rapid development of information and network technology requires vocational schools to implement reliable network security systems to protect digital infrastructure and data. SMK Garuda Nusantara has adequate network facilities; however, network security implementation has not been optimally configured. This community service program aims to provide assistance in developing and implementing an open-source firewall-based network security system. The implementation method includes preparation, socialization, theoretical training, firewall configuration practice, mentoring, and evaluation. Open-source firewall solutions are utilized as cost-effective and educational tools for network security learning. The results indicate improved participants’ understanding and skills in network security concepts, traffic management, and access control using firewalls. This program supports project-based learning, enhances cybersecurity awareness, and strengthens collaboration between higher education institutions and vocational schools. Keywords: Network Security, Open Source Firewall, Community Service, Vocational Education
Analisis Sentimen Pada Media Sosial X Terhadap Pemimpin Muda Menggunakan Pendekatan Algoritma Support Vector Machine Effendi, Muhammad Makmun; Ermanto, Ermanto; Zy, Ahmad Turmudi; Siswandi, Arif
Techno.Com Vol. 25 No. 1 (2026): February 2026
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v25i1.15489

Abstract

Media sosial telah menjadi sarana utama bagi masyarakat untuk menyampaikan opini dan persepsi terhadap tokoh publik, termasuk pemimpin muda. Platform X (Twitter) menyediakan data teks yang kaya dan dinamis yang mencerminkan sentimen publik secara luas. Penelitian ini bertujuan untuk menganalisis sentimen pengguna media sosial X terhadap pemimpin muda menggunakan pendekatan algoritma Support Vector Machine (SVM). Dataset yang digunakan dalam penelitian ini terdiri dari 12.487 tweet yang dikumpulkan melalui teknik crawling pada rentang waktu Januari hingga Juni 2024. Tahapan praproses data meliputi case folding, penghapusan stopword, normalisasi, tokenisasi, stemming, pelabelan data, serta ekstraksi fitur menggunakan metode Term Frequency–Inverse Document Frequency (TF-IDF). Selanjutnya, algoritma SVM diterapkan untuk mengklasifikasikan sentimen ke dalam tiga kelas, yaitu positif, negatif, dan netral. Evaluasi kinerja model dilakukan menggunakan confusion matrix dan metode 10-fold cross-validation. Hasil penelitian menunjukkan bahwa algoritma SVM mampu mengklasifikasikan sentimen dengan baik, dengan nilai akurasi sebesar 84,66%, precision 84,12%, recall 83,74%, dan F1-score 83,93%. Analisis distribusi sentimen menunjukkan bahwa sentimen positif mendominasi dengan persentase 41,18%, diikuti sentimen negatif sebesar 34,64%, dan sentimen netral sebesar 24,18%. Temuan ini menunjukkan bahwa pendekatan SVM berbasis TF-IDF efektif digunakan untuk analisis sentimen pada data Twitter berskala besar serta mampu memberikan gambaran yang reliabel mengenai persepsi publik terhadap pemimpin muda.   Kata Kunci- Analisis Sentimen, Twitter, Pemimpin Muda, SVM, dan Media Sosial
Peningkatan Kompetensi Siswa SMK dalam Menghadapi Ancaman Keamanan Siber Nugroho, Agung; Widiyatmoko, Arif Tri; Siswandi, Arif; Susilo, Arief; Suwarno, Agus
Cahaya Pengabdian Vol. 2 No. 2 (2025): Desember 2025
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/cp.v2i2.268

Abstract

This community service aims to improve the competence of vocational school students in the field of cyber security through training activities and the effective use of learning technology. Vocational school students as prospective skilled workers need to be equipped with basic cybersecurity competencies to protect personal data and understand cyber risks. The method of implementing activities includes coordination with the school, module development, and intensive training using lecture, discussion, practicum, and demonstration methods. In addition, this activity utilizes information technology such as digital simulations for phishing and malware threats, as well as password strength testing tools. The results of the service showed that the activities carried out ran smoothly and had a positive impact in improving students' understanding and competence of cyber security threats. This service is expected to produce graduates who have critical thinking, creative, and problem-solving skills who are ready to enter the world of work
Co-Authors . Ermanto Abdul Ghofir Afrianto, Irfan Agus Suwarno, Agus Andriani Anwar, M. Syaibani ARIF SUSILO Butsianto, Sufajar Effendi, Muhammad Makmun Elkin Rilvani Ermanto Fachrial Banyu Asmoro Fauzi Ahmad Muda febriyanti febriyanti Gitawijaya, Dhea Hasibuan, Sultan Ikhsan Romli Inka, Inka Maulana Majid, Annisa Miharja, Muhammad Najamuddin Dwi muhidin, asep Naya, Candra Nugroho, Agung Pradini, Purnama Sakhrial Purnama Sakhrial Saiful Muktiali Setyawan, Wisnu Soejarminto, Yos Surojudin, Nurhadi Susilo, Arief Turmud Zy, Ahmad Wangsadanureja, Miftah Widiyatmoko, Arif Tri Zy, Ahmad Turmudi