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All Journal TEKNIK INFORMATIKA Jurnal Simantec Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan Jurnal IPTEK Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIV : International Journal on Informatics Visualization INTEGER: Journal of Information Technology Network Engineering Research Operation [NERO] PROMINE Prosiding Seminar Nasional Sains dan Teknologi Terapan Jurnal Telematika Jurnal Teknologi Terpadu TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) International Journal of Artificial Intelligence and Robotics (IJAIR) Jurnal Tika Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer
Muchamad Kurniawan, Muchamad
Institut Teknologi Adhi Tama Surabaya
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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Implementasi Metode Clarke and Wright Savings dalam Penyelesaian Vehicle Routing Problem di PT. Adiguna Gasindo Munir, Misbahul; Kurniawan, Muchamad; M, Moch. Kalam; Setyawati, Indah
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.876

Abstract

A vehicle routing problem (VRP) is a problem in finding the most optimal route with the addition of a constraint. PT. Adiguna Gasindo is one of the LPG gas agents who needs help in shipping to agents, the problem is that there is a limit to the amount of LPG cargo that can be transported. In this research, we will solve the LPG delivery problem by optimizing distance and cost. The Clarke and Wright Savings Method, commonly known as the Saving Matrix, will be implemented to complete VRP. In this study, the distance approaches are the nearest insert and nearest neighbor. The test scenarios were carried out using three types of vehicles with different capacities, namely small (225 kg), medium (275 kg), and large (480 kg). The results obtained will be compared with the actual results (routes done) due to validation. From the results of 90 different scenarios, the results obtained by vehicles with large loads are those of vehicles that get the most optimal route in terms of distance and cost. The saving matrix will be more optimal if it is done by adding the nearest insert or nearest neighbor technique.
Implementasi Algoritma Caesar Cipher dan Rivest Shamir Adleman Super Enkripsi Teks Pesan dengan Karakter Ascii Fahrezi Kusuma, Andra; Agustini, Siti; Hakimah, Maftahatul; Kurniawan, Muchamad
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2024: SNESTIK IV
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2024.5714

Abstract

Humans are never separated from information needs when viewed from technology use. Data security is important because it relates to confidentiality, integrity, authentication, and privacy. Some information has privacy that the public should not share. Therefore we need a way to secure information so that the information does not spread widely to unauthorized parties. This study used Caesar Cipher and RSA Algorithms to secure a text message. So the data would not be easily hacked by irresponsible parties. The encryption process started using the Caesar Cipher Algorithm by entering a key/shift of letters to produce a ciphertext. Ciphertext Caesar is used for the encryption process for the second time using the RSA algorithm. RSA ciphertext result was converted into ASCII characters. The algorithm proposed to secure message text data using a combination of letters and numbers in each trial. The Caesar Cipher Algorithm implementation results obtained an average avalanche effect value of 35.03%. At the same time, the RSA algorithm obtained an average avalanche effect value of 55.10%. And the Caesar-RSA algorithm obtained an average avalanche effect value of 59.015%. The best test results were obtained by combining the two algorithms, Caesar Cipher and RSA, which showed that the proposed algorithm could secure message text data effectively.
Implementasi Mengamankan Pesan Teks Menggunakan Metode GOST (Gosundarstevenny Standard) Ritonga, Mario Franko Ezra Hasiholan; Kurniawan, Muchamad; Agustini, Siti
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2024: SNESTIK IV
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2024.5713

Abstract

The increasing development of technology has made it easier for people to communicate with each other. Sometimes, some of the information sent must be kept confidential so that it is not misused by irresponsible people. This research deals with securing messages using the GOST method during information exchange. The output messages of chats converted into ciphertext served as the research materials. The research results indicated that the application to secure text messages successfully implemented encryption and decryption techniques through the GOST method. The more bit changes occurred, the more difficult the cryptographic algorithm was to solve.
Klasterisasi Produk Berdasarkan Data Penjualan Menggunakan Algoritma K-Means Dengan Penentuan Centroid Awal Istighfariansyah, Risaldi; Hakimah, Maftahatul; Kurniawan, Muchamad
Prosiding Seminar Nasional Sains dan Teknologi Terapan 2023: Transformasi Riset, Inovasi dan Kreativitas Menuju Smart Technology dan Smart Energy
Publisher : Institut Teknologi Adhi Tama Surabaya

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Abstract

Kondisi pandemi pada awal Tahun 2020 membuat pada pemilik usaha terutama usaha kuliner memasang strategi untuk membuat produknya laku. Hal tersebut terjadi di salah satu Café di Surabaya dimana dalam kurun waktu satu tahun pada periode tahun 2020, tingkat penjualan suatu produk yang ditawarkan kurang maksimal. Salah satu strategi yang bisa diambil dan dibahas pada penelitian ini adalah memetakan produk penjualan mulai yang paling laku sampai dengan yang kurang laku. Pemetaan tersebut bisa dilakukan dengan pendekatan klasterisasi. Penelitian ini menerapkan metode yang sederhana dan efektif dalam klasterisasi yakni K-Means. K-means merupakan salah satu partition-based clustering yang bekerja dengan cara menentukan secara acak centroid dari tiap cluster kemudian tiap instance akan dikelompokkan ke dalam cluster dengan jarak terdekat. Namun Metode K-Means memiliki kekurangan yaitu penentuan centroid awal dengan acak. Sehingga, penelitian ini menerapkan K-Means Dengan Penentuan Centroid Awal. Berdasarkan hasil pengujian, K-Means Dengan Penentuan Centroid Awal bisa meningkatkan nilai Davies bouldin index (DBI) dari K-Means Standart sebesar 71,68% dan dapat menurunkan nilai Sum of Squared Error (SSE) dari K-Means Standart sebesar 35,73%.
SISTEM DETEKSI PENYAKIT PADA OTAK DENGAN PENDEKATAN KLASIFIKASI CNN DAN PREPROCESSING IMAGE GENERATOR Kurniawan, Muchamad; Abdullah, Ryan Gading
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4371

Abstract

In today's digital era, artificial intelligence technology has become an important part of various human activities, including in the healthcare sector. One of its focal points is the detection of brain diseases, which have significant implications for health and medical expenses. This study addresses the issue of accuracy in brain disease detection through the utilization of Convolutional Neural Network (CNN) methodology and preprocessing Image Generator. Previous research suggests that CNN with preprocessing Image Generator has the potential to enhance detection accuracy. The research employs the Computed Tomography (CT) of the Brain dataset from Kaggle, comprising 259 data points categorized into three classes: aneurysm, tumor, and cancer. Experimental findings indicate that the CNN method with preprocessing Image Generator yields higher accuracy in both training and testing phases, with reduced complexity. In conclusion, this method holds promise for more effective detection of brain diseases
PERBANDINGAN K-MEANS DAN K-MEDOIDS UNTUK PENGELOMPOKKAN DATA TITIK PANAS BUMI DI PULAU KALIMANTAN Ilmi, Hilmi Maulana; Kurniawan, Muchamad; Faruq, Umar Al; Muhima, Rani Rotul
Jurnal Simantec Vol 13, No 1 (2024): Jurnal Simantec Desember 2024
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v13i1.17138

Abstract

This dtudy aims to determine the comparison of the performance of two methods, namely K-Means and K-Medoids. The performance of both is based on Sum Square Error (SSE) value. Both methods were used to group geothermal hotspot data on the island of Kalimantan. The geothermal point dataset used was obtained from the official NASA website. The parameters used are latitude, longitude, bright_ti4, scan, track, bright_ti5 and frp. In this study, it was carried out with variation in the value of k = 2, 3, 4, ...,12. Then the Elbow method was used to determine the optimal cluster of both methods. Based on the results, K-means provides greater group variation and better SSE values than the K-Medoids method on the optimal number of clusters. However, overall the results showed that K-Medoids had a better average SSE value than K-Means.Keywords: Clustering, K-Means, K-Medoids, Geothermal Hotspot
RANCANG BANGUN SISTEM INFORMASI TOUR & TRAVEL BERBASIS WEB MENGGUNAKAN MODEL PROTOTYPE Wardhana, Septiyawan Rosetya; Nurlaily, Firdausiyah; Kurniawan, Muchamad
Prosiding Seminar Nasional Sains dan Teknologi Terapan 2024: Menjembatani Energi Berkelanjutan dan Ekonomi Hijau melalui Transformasi Riset dan Teknologi T
Publisher : Institut Teknologi Adhi Tama Surabaya

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Abstract

Seiring berjalannya waktu, perkembangan teknologi informasi telah memberikan dampak signifikan dalam berbagai sektor kehidupan, termasuk industri pariwisata. Saat ini, proses pengelolaan data dan transaksi di Prima Adventure masih menggunakan cara manual yang dianggap kurang efisien. Penelitian ini bertujuan untuk merancang dan mengembangkan Sistem Informasi Tour and Travel agar proses pengelolaan data dan transaksi menjadi lebih mudah dan efisien. Sistem Informasi Tour and Travel di bangun menggunakan model prototype. Model prototype memungkinkan calon pengguna untuk berpartisipasi aktif dalam proses perancangan sistem informasi. Berdasarkan evaluasi yang telah dilalukan, didapatkan hasil yang sangat baik dalam aspek kegunaan dengan nilai sebesar 85%, aspek fungsionalitas dengan nilai sebesar 95%, dan aspek efisiensi dengan nilai sebesar 92%. Dengan ini didapatkan hasil evaluasi secara keseluruhan sebesar 90% yang termasuk dalam kategori sangat baik. Hal ini menunjukkan bahwa penggunaan model prototype dalam pengembangan sistem ini berhasil dilakukan dan proses pengelolaan data transaksi menjadi lebih baik dari proses sebelumnya.
PERBANDINGAN KINERJA METODE CNN DALAM MENGKLASIFIKASI ORANG MEROKOK Muchamad Kurniawan; Arum Indah Sari; Priska Amelia de Jong
PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer Vol. 11 No. 2 (2024): Prosisko Vol. 11 No. 2 September 2024
Publisher : Pogram Studi Sistem Komputer Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/prosisko.v11i2.8533

Abstract

Merokok merupakan sebuah perilaku yang telah menjadi kebiasaan bagi masyarakat di dunia dan terutama di Indonesia. Hampir sebagian besar perokok didominasi oleh kaum laki-laki dibandingkan kaum perempuan. Di era yang sudah digital banyak penelitian yang telah dilakukan yaitu salah satu penerapannya dalam penelitian dalam pendekatan klasifikasi. Penelitian yang dilakukan ini mengangkat sebuah permasalahan nilai akurasi atau keakuratan nilai dari pendekatan klasifikasi orang perokok dan bukan perokok berdasarkan data gambar, dengan menggunakan perbandingan metode CNN. Tujuan dari penelitian ini yaitu untuk membandingkan empat arsitektur dari metode CNN yaitu ResNet50, VGG16, Inception Net dan Mobile Net, dari keempat arsitektur tersebut dibandingkan mana yang lebih optimal dan mendapatkan akurasi terbaik dari klasifikasi orang perokok dan bukan perokok. Penelitian yang dilakukan menggunakan dataset yang bersumber dari Kaggle yaitu dataset berupa data gambar perokok dan bukan perokok dengan jumlah gambar sebanyak 1120 gambar, dibagi menjadi dua kelas yaitu 560 untuk kelas perokok dan 560 untuk kelas bukan perokok. Hasil percobaan membandingkan empat arsitektur dari metode CNN menunjukkan bahwa arsitektur InceptionNet dan MobileNet memiliki nilai akurasi yang paling optimal dibandingkan arsitektur ResNet50 dan VGG16. Nilai accuracy yang didapat dari arsitektur Inception Net dan MobileNet yaitu sebesar 91%, sedangkan pada arsitektur ResNet50 nilai accuracy sebesar 50% dan pada arsitektur VGG16 nilai accuracy sebesar 85%.
Prediction Of Clay Mining Production Value Using Linear Regression Model With Multi-Swarm Particle Swarm Optimization Yuliastuti, Gusti Eka; Kurniawan, Muchamad; Pratikto, Dimas; Moneter, Mochamad Rizky
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.3443

Abstract

The progress of a nation or a country can be recognized from its income through various industries inside. Mining refers to one of the most advanced industries in Indonesia. The majority of mining in Indonesia is open-pit mining which is exposed directly to the sky. This study focuses on modeling data from rainfall, working hours, and production yields. It employed the Multi-Swarm Particle Swarm Optimization (MSPSO) algorithm to find multiple linear regression modeling by minimizing the Mean Squared Error (MSE) value. The value for the production results was then predicted using the existing multiple linear regression model. In terms of testing, the best model having an MSE of 288.0656 occurred at the parameters of Npop 180, acceleration coefficient 1 by 0.7, acceleration coefficient 2 by 0.7, acceleration coefficient 3 by 0.7, wmin 4, wmax 9 within 100 iterations.
Penerapan Metode CNN (Convolutional Neural Network) dalam Mengklasifikasi Uang Kertas dan Uang Logam Rewina, Anggita Eka; Sulistyowati, Sulistyowati; Kurniawan, Muchamad; N, Muhammad Dinarta; Yunanda, Sita Fara
TIN: Terapan Informatika Nusantara Vol 4 No 12 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i12.5128

Abstract

Banknotes and coins are valuable assets that are used as legal means of payment in everyday life. The value of these two types of money has been determined and is printed on each piece of banknote when used in transactions and trade. Even though currently banknotes can be recognized using technology such as ATM machines, these machines are only able to recognize the value of the largest currency owned by a country. Computers require digital images as input to display the information contained therein because computers do not have the ability of the human eye to directly recognize or calculate the objects they see. Therefore, techniques or methods are needed that aim to obtain information from digital images to facilitate human interpretation. This research aims to design a system for detecting banknotes in images using the Convolutional Neural Network (CNN) architecture, which is a form of deep learning. . The system also integrates image pre-processing using user-based manual annotation techniques in Python program code. Using the CNN method, a test was carried out to detect the nominal amount of money in the input image. Test results using 29 banknote dataset samples and 31 coin money dataset samples show that the two types of money are divided into two classes, namely paper and coins. From the training carried out on banknotes and coins, an average accuracy of 98% was obtained, showing good results. Repetition of the detection process also shows consistent output probabilities. However, there are several denominations of money that show high accuracy values, so it can be concluded that the labeling annotation method is thought to be less effective.
Co-Authors Abdullah, Ryan Gading Andy Rachman Ar, Nanda Hafiz Arinal Haq, Fatahillah Arum Indah Sari Bagus S, Dadang Bamahri, Fakhirah Budi, Adib Pakar Fahrezi Kusuma, Andra Fanani, Yazid Farida Farida Farida Farida Faruq, Umar Al Fawaz, Ahmad Gusti Eka Yuliastuti Habibah, Maryam Ummul Hadimarta, Tommy Ferdian Hendro Nugroho, Hendro Ilmi, Hilmi Maulana Istighfariansyah, Risaldi Maftahatul Hakimah, Maftahatul Misbahul Munir Moch. Kalam Mollah Moneter, Mochamad Rizky Muhammad Aditya Kushardiawan Muhima, Rani Rotul N, Muhammad Dinarta Nabila Dayu Mega Anjani Naili Saidatin Nanik Suciati Nurlaily, Firdausiyah O.T., Pambudi Pakarbudi, Adib Pambudi, Oktavian Tegar Pratikto, Dimas Priska Amelia de Jong Putri, Chatarina Natassya Qornain, Wafi Dzul Rewina, Anggita Eka Ritonga, Mario Franko Ezra Hasiholan Rosetya Wardhana, Septiyawan Sandi Alala, Pratama Setyawati, Indah Siti Agustini, Siti Sulistyowati Sulistyowati Ubaidillah, M. Yahya Wachid, Aldi Wardhana, Septiyawan Rosetya Wicaksono, Mukhlis Adi Yunanda, Sita Fara Zaqiyah, Hafida Nur