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DETEKSI SERANGAN PADA INTRUSION DETECTION SYSTEM ( IDS ) UNTUK KLASIFIKASI SERANGAN DENGAN ALGORITMA NAÏVE BAYES, C.45 DAN K-NN DALAM MEMINIMALISASI RESIKO TERHADAP PENGGUNA Niko Suwaryo; Ismasari Nawangsih; Sri Rejeki
JSI (Jurnal sistem Informasi) Universitas Suryadarma Vol 8, No 2 (2021): JSI (Jurnal sistem Informasi) Universitas Suryadarma
Publisher : Universitas Dirgantara Marsekal Suryadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35968/jsi.v8i2.732

ABSTRACT Intrusion Detection System is the ability possessed by hardware or software that serves to detect suspicious activity on the network and analyze and search in general. The purpose of this study is to classify attack detection on the Intrusion Detection System using the C.45, Naïve Bayes and K-NN algorithms to see how big the attack is. The benefits gained in this study are as a test and learning material in analyzing, classifying attacks so that they can prevent and minimize attacks to users. To overcome this problem, this study uses the C.45 algorithm, Naïve Bayes, K-NN, K-NN algorithm produces an accuracy rate of 82.58%, Recall 81.73% and Precision 84.11% while the Naïve Bayes accuracy 96.91%, Recall 97,45% and Percision 96.18% and the algorithm produces an optimal value of C.45 accuracy 97.80% Recall 98.18% and Precision 97.60%. On the attribute (attack) which has the number of classes or normal labels, dos, probes, r21. The results of the lowest K-NN algorithm are caused or normal to be considered yes(an attack) which should be No(no attack)and the C.45 algorithm attribute(attack) normal, dos, probe and r21, normal(no attack), yes(the presence of an attack) is optimal in the classification of attack detection data on Intrusion Detection System(IDS). Keywords: Data Mining, C.45, Naïve Bayes and K-NN, Intrusion Detection System(IDS)

Klasterisasi Stok Produk Retail Untuk Menetukan Pergerakan Kebutuhan Konsumen Dengan Algoritma K-Means Niko Suwaryo Niko; Arif Rahman; Dewi Marini Umi Atmaja; Amat Basri
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.736

− Retail product clustering is a product arrangement that is adjusted to the flow of placement or this layout is more suitable for product placement according to standards. Utilization of existing data through the clustering method approach can be applied in analyzing product grouping of data on availability and inventory of goods in warehouses so that it can provide knowledge and information. The clustering method is processed using the K-Means algorithm, where the results also show a new insight, namely grouping products based on 3 clusters. Cluster 1 is a product category with low availability or Low, namely 939 out of 1000 availability categories based on the number of products tested, then cluster 2 is a product category with medium or Medium availability, namely 51 out of 1000 availability categories based on the number of products tested, and finally cluster 3 is a product category with fairly high availability or High, namely 10 out of 100 availability categories based on the number of products tested. Tests using Rapid Miner tools can also produce similar insights, namely that each cluster has cluster group members according to manual calculations such as Cluster_0 in Rapid Miner has 51 cluster members representing the Medium cluster, Cluster_1 has 939 cluster group members representing the Low cluster, and Cluster_2 has 10 cluster members corresponding to the cluster representation High.

Prediksi Penyakit Diabetes Untuk Pencegahan Dini Dengan Metode Regresi Linear Niko Suwaryo Niko; Arif Rahman; Dewi Marini Umi Atmaja; Amat Basri
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.739

Estimation is a method in which we can estimate the population value by using the sample value and which can model an equation to calculate the estimate i.e. a linear regression algorithm attempts to model the relationship between two variables by fitting a linear equation to observe the data. The application of a simple Linear Regression algorithm model can be implemented well and is able to provide a new insight for the need for predictions about the condition of diabetes data quality in controlling sugar levels in the body. Predictions of diabetes in the future can be known through the use of datasets using a prediction method approach through structured stages in analyzing the data used to produce an RSME value when evaluating a model of 0.000 +/- 0.000. Performance testing of the models and algorithms used in the evaluation can produce a picture that is relevant to the scenario being modeled. The RMSE value is obtained when evaluating the model performance of 0.000 +/- 0.000 through the RapidMiner Studio application.

Analysis of the Apriori Algorithm for Enhancing Retail Product Staple Sales Recommendations Kurniawan, Avip; Suwaryo, Niko
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 3 (2023): DECEMBER 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i3.1877

Products are fundamental commodities in the market that cater to various consumer needs and desires. This research employs the Apriori algorithm to generate product recommendations based on the analysis of high-demand patterns arising from product sales and association patterns. Specifically, we focus on identifying elevated sales in categories such as Bulk Products, Biscuits/Snacks, Drinks, Milk/Coffee/Tea, and Sauces & Spices during specific time intervals. The model's evaluation and validation entail measuring the Lift Ratio value, a key metric. In our assessment using the RapidMiner Studio application, we find that the Lift Ratio value equals 1. Consequently, our model asserts that combinations with a Lift Ratio value greater than or equal to 1 are deemed valid and beneficial.

PELATIHAN KLASTERISASI STOK PRODUK RETAIL UNTUK MENETUKAN PERGERAKAN KEBUTUHAN KONSUMEN Niko Suwaryo
PROFICIO Vol. 5 No. 1 (2024): PROFICIO: Jurnal Abdimas FKIP UTP
Publisher : FKIP UNIVERSITAS TUNAS PEMBANGUNAN SURAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36728/jpf.v5i1.2940

Pelaku bisnis harus selalu memikirkan cara untuk terus bertahan dan jika mungkin mengembangkan skala bisnis. Dalam hal ini, evaluasi yang dilakukan untuk kegiatan PKM pelatihan klasterisasi stok produk retail untuk menetukan pergerakan kebutuhan konsumen bisa dilakukan dengan cara mengumpulkan umpan balik dari para peserta pengabdian masyarakat, yaitu guru-guru yang mengikuti pelatihan penggunaanaplikasi. Umpan balik tersebut bisa berupa pertanyaan, saran atau pemasukan yang bisa membantu dalam mengevaluasi keberhasilan kegiatan PKM. Selain itu, evaluasi juga bisa dilakukan dengan cara mengevaluasi hasil akhir dari pengabdian masyarakat, yaitu aplikasi berbasis website yang dibuat. Evaluasi ini bisa dilakukan dengan cara mengecek apakah aplikasi yang dibuat sudah sesuai dengan yang diharapkan, serta juga apakah aplikasi yang dibuat sudah sesuai dengan yang dibutuhkan, serta juga apakah aplikasi tersebut sudah bisa diakses.

PELATIHAN PENGGUNAAN APLIKASI E-LAUNDRY DENGAN MEMANFAATKAN TEKNOLOGI LOCATION BASED SERVICES BERBASIS MOBILE DAN WEBSITE PADA UMKM DI DESA SETIA MEKAR KECAMATAN TAMBUN SELATAN Dewi Marini Umi Atmaja; Arif Rahman Hakim; Niko Suwaryo
PROFICIO Vol. 5 No. 1 (2024): PROFICIO: Jurnal Abdimas FKIP UTP
Publisher : FKIP UNIVERSITAS TUNAS PEMBANGUNAN SURAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36728/jpf.v5i1.3026

Salah satu faktor yang mendukung perkembangan UMKM adalah karena pemanfaatan sarana TIK (Teknologi, Informasi dan Komunikasi). Kemenkop RI melaporkan sudah ada sekitar 8 juta UMKM yang sudah Go-Digital pada tahun 2017 lalu. Angka ini diharapkan dapat terus bertambah karena tingginya jumlah UMKM yang Go-Digital sejalan dengan tujuan pemerintah yang ingin menjadikan Indonesia sebagai Digital Energy of Asia. Saat ini UMKM yang berkembang cukup pesat adalah usaha laundry yang memberikan jasa layanan berupa cuci dan setrika pakaian. Pengusaha laundry harus senantiasa meningkatkan pelayanan untuk menjaga loyalitas konsumen lama dan menarik konsumen baru. Hal tersebut dapat direalisasikan dengan membangun sebuah sistem informasi e-laundry yang dapat mempermudah pengusaha dalam mengelola data konsumen, sehingga adanya risiko kesalahan human error dapat dihindari. Usaha UMKM yang dibarengi dengan kemajuan teknologi akan mempermudah pengusaha dalam mengembangkan bisnisnya. Melalui kegiatan Pengabdian kepada Masyarakat (PkM) ini, diharapkan para pelaku usaha UMKM laundry akan mendapatkan edukasi tentang pentingnya teknologi untuk kemajuan bisnis, serta pelatihan penggunaan sistem informasi e-laundry. Kegiatan PkM dilakukan secara luring dalam bentuk ceramah dan implementasi sistem informasi e-laundry, sehingga para pelaku usaha dapat langsung mengaplikasikan sistem tersebut kedalam bisnisnya. Penerapan sistem informasi e-laundry diharapkan dapat memberikan dampak pada peningkatan nilai bisnis serta mempermudah kegiatan operasinal agar lebih efektif dan efisien.

Implementasi Sistem Pakar untuk Diagnosis Penyakit Lambung Menggunakan Pendekatan Fuzzy Mamdani Berbasis Website Yansyah, Ilham Roni; Atmaja, Dewi Marini Umi; Hakim, Arif Rahman; Suwaryo, Niko
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3534

This study aims to develop a more specific diagnostic approach for various gastric diseases in humans, such as gastritis, peptic ulcers, gastric cancer, gastric tumors or polyps, dyspepsia, gastroesophageal reflux disease (GERD), gastroparesis, and gastroenteritis. This approach seeks to enhance the accuracy of disease identification based on more detailed symptoms. An expert system utilizing the Fuzzy Mamdani method is designed to reduce reliance on internal medicine specialists, enabling patients to gain preliminary insights into the type of gastric disease they may have. This expert system is implemented on a web-based platform, leveraging information technology to integrate large-scale databases, supporting efficiency, accuracy, and relevance to the latest developments in medical science. By analyzing digestive disorder symptoms, the system can provide detailed diagnoses, offer insights into identified symptoms, and recommend appropriate treatment solutions.

Tongue Detection For Identification Of Syndrome Diagnosis In Heart Disease Using Convolutional Neural Network Niko Suwaryo; Koniasari; Amat Basri
Tech-E Vol. 8 No. 2 (2025): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v8i2.3285

Convolutional Neural Network (CNN) which is one of the Deep Learning methods for Image identification and CNN models can identify images well but in this case it requires higher accuracy because the case is very crucial to determine the risk of heart disease. The initial stage in this study was the collection of tongue image data, 4836 training data and 1209 testing data. The image data used were the front, right side, left side of the tongue and under the tongue. The dataset was obtained from taking pictures using a smartphone camera centimeters above the object. The distribution of data in each class is shown in the following figure. The model from the two CNN algorithm experiments has accuracy performance. Based on the training results the model from the algorithm gets an accuracy value and Testing by identifying 20% of the total dataset as test data. The identification results are formed in a Confusion Matrix to then be poured into a classification report and obtain: train loss 0.301446, train accuracy 0.862696, test loss 0.314132 and test accuracy 0.850290 so that from the results of the tongue data test it can be concluded that the accuracy value is quite good, above 80%.

Implementasi Sistem Pakar untuk Diagnosis Penyakit Lambung Menggunakan Pendekatan Fuzzy Mamdani Berbasis Website Yansyah, Ilham Roni; Atmaja, Dewi Marini Umi; Hakim, Arif Rahman; Suwaryo, Niko
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3534

This study aims to develop a more specific diagnostic approach for various gastric diseases in humans, such as gastritis, peptic ulcers, gastric cancer, gastric tumors or polyps, dyspepsia, gastroesophageal reflux disease (GERD), gastroparesis, and gastroenteritis. This approach seeks to enhance the accuracy of disease identification based on more detailed symptoms. An expert system utilizing the Fuzzy Mamdani method is designed to reduce reliance on internal medicine specialists, enabling patients to gain preliminary insights into the type of gastric disease they may have. This expert system is implemented on a web-based platform, leveraging information technology to integrate large-scale databases, supporting efficiency, accuracy, and relevance to the latest developments in medical science. By analyzing digestive disorder symptoms, the system can provide detailed diagnoses, offer insights into identified symptoms, and recommend appropriate treatment solutions.

Optimalisasi Analisis Penjualan dan Prediksi Permintaan Pada UMKM dengan Business Intelligence di Kelurahan Pematang Sulur Santoso, Santoso; Suwaryo, Niko; Nurali, Nurali; Gunarso, Sandy; Tugiman, Tugiman; Paryadi, Agus; Hidayah, Safitri
I-Com: Indonesian Community Journal Vol 5 No 2 (2025): I-Com: Indonesian Community Journal (Juni 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/i-com.v5i2.7317

UMKM play an important role in the economy, but often face challenges in analyzing sales and predicting product demand. This Community Service (PkM) aims to optimize sales analysis and demand prediction in UMKM in Pematang Sulur Village, Telanaipura District, Jambi City by implementing Business Intelligence (BI). The methods used include: identification and analysis of needs by collecting sales data with surveys, training and introduction of business intelligence targeting 23 UMKM to provide more accurate insights in decision making, implementation of a business intelligence system with trend analysis, application of BI-based predictive models, mentoring and evaluation, sustainability monitoring. The results of the PkM show that the application of BI can improve operational efficiency, identify demand patterns and help UMKM in developing more appropriate business strategies. With the BI system, UMKM actors can optimize stock of goods, reduce the risk of excess or shortage of products, and increase profitability. Keywords: UMKM, Business Intelligence, Sales Analysis, Demand Prediction, Competitiveness.

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