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All Journal Journal of Information System, Applied, Management, Accounting and Research Jurnal Teknologi Informasi dan Komunikasi
Carkiman, Carkiman
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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PENGALAMAN PELANGGAN MEMBELI TIKET KONSER COLDPLAY: MENAMBANG ULASAN ONLINE BERDASARKAN PEMODELAN TOPIK DAN ANALISIS SENTIMEN Zahra, Denada Fatimah; Carkiman, Carkiman
Journal of Information System, Applied, Management, Accounting and Research Vol 8 No 2 (2024): JISAMAR (March-May 2024)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v8i2.1426

Abstract

This study aims to analyze customer experience in buying tickets for the Coldplay Concert in Indonesia using sentiment analysis and topic modelling. Data is collected from online customer reviews about concert ticket purchases via social media platforms such as Twitter. The stages of the research include data collection, data labelling, data pre-processing, topic modelling using Latent Dirichlet Allocation (LDA), sentiment analysis, and interpretation of the results. The results of the sentiment analysis show that most reviews are positive, with customers expressing satisfaction with the ticket-buying process, experience at the concert, Coldplay's performance, and customer service. Several primary topics frequently appearing in reviews have been identified through topic modelling, including ticket-buying, concert experience, ticket prices, customer service, concert performance, concert location, togetherness with fans, accessibility, concert facilities, and supporting events. The interpretation of each topic provides insight into customer preferences and expectations. Recommendations for concert organizers include improving customer service, ensuring performance quality, choosing a convenient concert location, and paying attention to accessibility and the atmosphere around the concert venue. This research provides an in-depth understanding of customer experience and can serve as a guide for concert organizers to improve customer experience in the future.
Studi Literatur Pemanfaatan Artificial Intelligence untuk Prediksi Bencana Banjir Zahra, Denada Fatimah; Carkiman, Carkiman
Jurnal Teknologi Informasi dan Komunikasi Vol 18 No 1 (2025): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v18i1.281

Abstract

Floods are disasters that cause losses in the form of material and human casualties if not controlled. The Bekasi flood in 2025 was a flood event that was proven to paralyze economic activities and inundate crucial economic zones and settlements in the Bekasi area. Basically, floods can be categorized as fluvial, pluvial, rob, and flash. There are various factors that cause floods that cause diversity in types and levels of flood destruction. Therefore, previous studies have attempted to predict floods from a physical perspective, but still experience various obstacles, so this study aims to explain the use of artificial intelligence for flood disaster prediction. The research method used is a literature study in order to represent the use of artificial intelligence in various areas and techniques. The data used is in the form of scientific literature consisting of journals and scientific proceedings. The results of the study show that most of the AI used is based on machine learning algorithms, such as random forest, logistic regression, support vector machine, and KNN. Random forest and logistic regression have proven to have the highest performance and accuracy when compared to other algorithms. However, it needs to be combined with data augmentation techniques and consider time when used for real-time prediction needs.
Machine Learning Penyortiran Buah Naga Menggunakan Algoritma K-Means Berbasis Internet of Things Menggunakan Platform Blynks Ramadan, Wanda; Abidin, Aa Zezen Zenal; Suryadi, Usep Tatang; Murdianingsih, Yuli; Faizal, Muhammad; Suhendri, Suhendri; Carkiman, Carkiman
Jurnal Teknologi Informasi dan Komunikasi Vol 18 No 1 (2025): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v18i1.285

Abstract

Salah satu tahapan dalam proses pengelolaan hasil pertanian dan perkebunan ialah dengan melakukan pembagian terstruktur mengenai produk untuk menentukan kualitas hasil panen. Penyortiran dilakukan dengan melihat kualitas rona kulit, berat buah serta mengetahui jumlah satu kali panen. Kualitas buah naga ditentukan oleh berbagai parameter, antara lain umur dan kematangan (indeks warna), ukuran, dan berat buah. Sebagai salah satu komoditas yang disukai banyak orang, buah naga memerlukan proses sortasi (seleksi), karena pasar membutuhkan kondisi keseragaman buah naga. Seleksi biasanya dilakukan menurut prinsip pemisahan, seperti: bobot yang berbeda, bentuk yang berbeda, sifat permukaan yang berbeda, berat jenis yang berbeda, tekstur warna yang berbeda dan kematangan yang berbeda. Dalam proses penyortiran manual, manusia memiliki kelemahan dalam melakukan tugas sensorik dengan kapasitas besar dan jam kerja yang Panjang. Berangkat dari permasalahan tersebut penulis tertarik untuk membuat alat yaitu Machine Learning Penyortiran Buah Naga Berbasis Internet of Things Menggunakan Algoritma K- Means Pada Platform Blynk. Metodologi yang digunakan penulis diantaranya Studi pustaka, dokumentasi, data mining, analisa sistem, perancangan sistem, pembuatan sistem, pengujian sistem. Machine Learning Penyortiran Buah Naga Berbasis Internet of Things Menggunakan Algoritma K- Means Pada Platform Blynk yang penulis kerjakan dapat berhasil terealisasikan menggunakan sensor Load Cell untuk menghitung berat dan sensor TCS230 untuk menentukan warna. Serta sensor TCS3200 dapat mendeteksi warna dengan baik. Data yang didapat oleh alat dapat diklasterisasi menggunakan Algoritmaa K-Means dengan benar sebanyak 7 iterasi dengan nilai BCV=2096,84, WCV=442563,35, Rasio=211.
Optimalisasi Sistem Pemilu Melalui Implementasi E-Voting Berbasis Blockchain Dengan Keamanan Kriptografi AES-128 Suryadi, Usep Tatang; Permana , Ardi; Abidin, Aa Zezen Zaenal; Murdianingsih, Yuli; Carkiman, Carkiman; Faizal, Muhammad
Jurnal Teknologi Informasi dan Komunikasi Vol 18 No 2 (2025): October
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v18i2.343

Abstract

The general election (Pemilu) is a fundamental element of a democratic system. This study develops and evaluates a blockchain-based e-voting system implementing AES-128 encryption to ensure the confidentiality, integrity, and availability of voting data. The system integrates AES-128 symmetric encryption for data at-rest and SHA-256 hashing at the blockchain layer. Testing was conducted on a simulated dataset containing 100,000 voting records to measure processing time, storage efficiency, and cryptographic resilience against brute-force and data manipulation attacks. Experimental results show an average read/processing time of 24 seconds for 100,000 records under the test server configuration, and theoretical security analysis indicates that brute-forcing AES-128 is impractical with current computational capabilities. The contribution of this research lies in the integrated design of an e-voting system that combines data encryption and distributed storage models with verification mechanisms, thereby enhancing the transparency and auditability of the election process.
SISTEM IRIGASI CERDAS TERINTEGRASI AI BERBASIS IoT UNTUK PERTANIAN MODERN MENGGUNAKAN ALGORITMA C 4.5 DI DESA XYZ Suryadi, Usep Tatang; Dwiana, Fazrian; Zaenal Abidin, Aa Zezen; Murdianingsih, Yuli; Faizal, Muhammad; Carkiman, Carkiman; Muhajir, Akrom
Jurnal Teknologi Informasi dan Komunikasi Vol 19 No 1 (2026): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v19i1.385

Abstract

The current irrigation system is still manual, resulting in suboptimal water use and water distribution that does not meet land requirements, causing a lot of water to be wasted. Irrigation control is also ineffective because Internet of Things technology is only capable of monitoring without automatic decision-making. This situation causes social problems related to water scarcity and slows down the progress of sustainable agriculture. The purpose of this study is to create an Internet of Things-based Sistem Irigasi cerdas system that can monitor agricultural environmental conditions in real time and use the C4.5 algorithm to classify irrigation needs. The research was conducted in the rice fields of Jabong Village with direct observation of agricultural land. Data was collected through DHT22, capacitive soil moisture, and raindrop water sensors with a total of 100 records. The analysis stages included determining the root node of all attributes, calculating entropy, information gain, and gain ratio. The attribute with the highest gain ratio was used as the root node, then the data was split to form leaf nodes. After the tree was formed, pruning was performed to avoid overfitting. The test results using RapidMiner tools showed an accuracy of 90.00%, which is classified as “good,” so this system can be a breakthrough from conventional agriculture to modern agriculture. This study is still limited to one user, three parameters, and the C4.5 algorithm.
Co-Authors Aa Zezen Zaenal Abidin, Aa Zezen Zaenal Abidin, Aa Zezen Zenal Dwiana, Fazrian Muhajir, Akrom Muhammad Faizal Permana , Ardi Ramadan, Wanda Suhendri Suhendri Usep Tatang Suryadi, Usep Tatang Yuli Murdianingsih, Yuli Zaenal Abidin, Aa Zezen Zahra, Denada Fatimah