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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Teknologi dan Manajemen Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding SNATIF Sistem : Jurnal Ilmu-Ilmu Teknik JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) Conference SENATIK STT Adisutjipto Yogyakarta Management and Economics Journal (MEC-J) JTAM (Jurnal Teori dan Aplikasi Matematika) CYCLOTRON Jurnal Abadimas Adi Buana Jiko (Jurnal Informatika dan komputer) Jurnal Teknik Elektro dan Komputer TRIAC Jurnal Riset Informatika JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering) JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) bit-Tech Jurnal Sistem informasi dan informatika (SIMIKA) JATI (Jurnal Mahasiswa Teknik Informatika) CIVITAS (JURNAL PEMBELAJARAN DAN ILMU CIVIC) International Journal of Advances in Data and Information Systems Journal of Computer Networks, Architecture and High Performance Computing Darmabakti : Junal Pengabdian dan Pemberdayaan Masyarakat JAREE (Journal on Advanced Research in Electrical Engineering) Jurnal Teknik Informatika (JUTIF) International Journal of Robotics and Control Systems Jurnal Teknologi dan Manajemen SinarFe7 Jurnal Penelitian Journal of Information Systems and Technology Research JAPI: Jurnal Akses Pengabdian Indonesia Internet of Things and Artificial Intelligence Journal JEECS (Journal of Electrical Engineering and Computer Sciences) TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi ITIJ Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal ilmiah teknologi informasi Asia
Dwi Arman Prasetya
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Analisis Sentimen Tiktok Shop Menggunakan Metode Multinomial Naïve Bayes Dan BM25 Yasin, Andrew Arjunanda; Prasetya, Dwi Arman; Fahrudin, Tresna Maulana
Jurnal Ilmiah Teknologi Informasi Asia Vol 18 No 2 (2024): Volume 18 nomor 2 2024 (8)
Publisher : LP2M Institut Teknologi dan Bisnis ASIA Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the current digital era, TikTok has emerged as a popular application among internet users. One prominent feature is the TikTok Shop, which allows users to shop directly through the platform. However, on October 4, 2023, TikTok Shop was temporarily suspended by the government due to online trade regulation policies. After reopening on December 12, 2023, various responses from the public emerged in reaction to this phenomenon. This research conducted sentiment analysis on TikTok Shop by observing public responses on Twitter using the Multinomial Naïve Bayes classification method with word weighting using the BM25 and TF-IDF methods. The analysis results showed a majority of positive sentiment regarding TikTok Shop, indicating disapproval of the previous closure policy. In testing with a 10% test sample size, BM25 showed slightly better performance than TF-IDF.
System Quality dan Information Quality terhadap Kinerja Pegawai melalui User Satisfaction menggunakan SIPD di Dinas Ketahanan Pangan dan Pertanian Kota Madiun Kusuma, Firdaus Miftakh; Ardianto, Yusaq Tomo; Prasetya, Dwi Arman
Jurnal Teknologi dan Manajemen Informatika Vol. 8 No. 1 (2022): Juni 2022
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v8i1.6739

Abstract

The Regional Government Information System (SIPD in Bahasa) is a management information system that is used to administer, document, and process regional development data into information. It serves to make decisions, and policies and build a unified database. The data is integrated from district/city, provincial and national levels. This study uses path analysis with a total sample of 43 employees. In the research, the coefficient value of the System Quality variable on User Satisfaction has a direct effect of 0.414. The Information Quality variable on User Satisfaction has a direct effect of 0.352. The System Quality variable on Employee Performance has a direct influence of 0.229. The variable Information Quality on Employee Performance has a direct effect of 0.449. Furthermore, the influence of System Quality on Employee Performance through User Satisfaction has an indirect effect of 0.186 with a total amount of 0.415. The influence of Information Quality on Employee Performance through User Satisfaction has an indirect effect of 0.158 with a total amount of 0.610.
Pengaruh Kualitas Sistem Informasi Sumber Daya Manusia, Pelatihan dan Pengembangan terhadap Kinerja Karyawan melalui Disiplin Kerja pada PT. Era Mulia Abadi Sejahtera Sholikah, Hesti; Ardianto, Yusaq Tomo; Prasetya, Dwi Arman
Jurnal Teknologi dan Manajemen Informatika Vol. 8 No. 2 (2022): Desember 2022
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v8i2.8239

Abstract

The aims of this study is to analyze the effect of the quality of human resource information systems, training and development, and work discipline on employee performance. The technique of analysis uses a linear regression analysis. The population of this sample was 116 workers. The findings have shown the quality of human resource information systems and training and development will enhance the discipline of work. This ensures that the quality of human resource systems accompanied by the seriousness of the workers in training and development will strengthen work discipline. Therefore, the quality of human resource information systems and training & development will enhance the employee performance. Moreover, the work discipline mediates the impact of the quality of human resources information system as well as training and development on employee performance.
Implementing GCV and mGCV to Determine Optimal Knot in Spline Regression for East Java Life Expectancy Lestari, Amanda Ayu Dewi; Damaliana, Aviolla Terza; Prasetya, Dwi Arman
International Journal of Advances in Data and Information Systems Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i2.1379

Abstract

Life Expectancy is a vital indicator for evaluating population’s overall welfare and health status within a specific region. According to data published by Badan Pusat Statistik (BPS) National, East Java Province ranks 10th nationally in terms of life expectancy in 2024, with male life expectancy recorded at 70.39 years and female life expectancy at 74.4 years. This research focuses on examining four key factors that are believed to influence life expectancy in East Java during the 2024 including the Percentage of the Poor Population (X1), the Percentage of Individuals Aged 5 and Above Who Regularly Smoke Tobacco (X2), the Expected Years of Schooling (X3), and the Open Unemployment Rate (X4). To determine the optimal knot points in the nonparametric truncated spline regression model, the study utilizes Generalized Cross-Validation (GCV) and the modified Generalized Cross-Validation (mGCV) methode by minimizing their respective error values. The findings indicate that all four variables significantly impact life expectancy. Among the methods applied, the mGCV approach demonstrates good performance, achieving the lowest error value of 0.100 and a coefficient of determination of 82.91%.
Customer Transaction Clustering with K-Prototype Algorithm Using Euclidean-Hamming Distance and Elbow Method Kuswardana, Dendy Arizki; Prasetya, Dwi Arman; Trimono, Trimono; Diyasa, I Gede Susrama Mas; Awang, Wan Suryani Wan
International Journal of Advances in Data and Information Systems Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i2.1381

Abstract

This study aims to cluster customer transactions in a Japanese food stall using the K-Prototype Algorithm with a combination of Euclidean-Hamming Distance and the Elbow method. Facing intense industry competition, this study seeks to understand customer purchasing behavior to increase loyalty and sales. From 9.721 initial entries, 9.705 cleaned and transformed records were analyzed. K-Prototype was chosen because of its ability to handle numeric features (Total Sales, Product Quantity) and categorical features (Payment Method, Order Type, Day Category and Time Category). The combination of Euclidean-Hamming distances was used for distance measurement. The optimal number of clusters was determined using the Elbow method, with the results recommending three clusters as the most optimal number. A Silhouette score of 0.6191 indicates a Good Structure clustering result, effectively identifying three distinct customer grouping: "Loyal Regulars" (49.5%), "Casual Shoppers" (42.3%), and "Premium Shoppers" (8.2%). Statistical validity was also tested using ANOVA and Chi-Square, the results showed significant differences between the clusters in numerical and categorical variables with a p-value <0.0001. The clusters are statistically valid in both numerical and categorical aspects. These insights provide an understanding of customer characteristics and reveal a strategically valuable cluster for targeted marketing.
PROTOTYPE OF INTERNET OF THINGS (IOT) IMPLEMENTATION IN WASTE MANAGEMENT TO SUPPORT SMART CITY MONITORING WITH ANDROID-BASED MOBILE APPLICATION USING FORWARD CHAINING METHOD Mohammad, Bawazir Fadhil; Dody Pintarko; Farhans, Muhammad Izzudin; Andre Leto; Ninis Herawati; Dwi Arman Prasetya; Anggraini Puspita Sari
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.5977

Abstract

Efficient waste management is one of the main challenges in supporting the implementation of the smart city concept. This research aims to develop a prototype of an Internet of Things (IoT)-based waste management system capable of monitoring the condition of waste bins in real-time through an Android-based mobile application. The system uses the forward chaining method to perform inference processes in decision making, such as identifying the status of the bin (empty, almost full, or full) based on integrated sensor data. The results show that the system is able to detect the volume of waste with high accuracy, send automatic notifications to operators or users when the bin reaches a certain condition, and provide practical solutions to optimise the waste collection process. With these features, the system not only improves operational efficiency but also supports cost reduction and environmental impact. The resulting prototype is expected to be the first step in the application of IoT technology in urban waste management to support the realisation of smart cities.
FUZZY LOGIC-CONTROLLED IOT SYSTEM FOR SMART PUBLIC TOILETS: DESIGN, IMPLEMENTATION, AND EVALUATION Arifani, Kahpi Baiquni; Irsyadi, Muhamad Haidir; Prakoso, Akbar Tri; Amrullah, Ahmad Wildan; Alam, Fajar Indra Nur; Prasetya, Dwi Arman; Sari, Anggraini Puspita
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6045

Abstract

Efficient energy management in public facilities such as public toilets has become an important challenge in the modern era, especially with the increasing demand for environmental sustainability. In this research, we developed a smart toilet system based on the Internet of Things (IoT) using the ESP32 as the main microcontroller and fuzzy logic methods for intelligent decision-making. This system is equipped with temperature (DHT22), humidity, and distance (HC-SR04) sensors to detect environmental conditions and user presence. Based on this data, the toilet fan and light are automatically controlled to minimize energy consumption. To facilitate real-time monitoring and threshold control, this system is integrated with a Flutter-based application, which provides an intuitive user interface for viewing environmental data and setting temperature, humidity, and distance thresholds. Fuzzy logic is used to determine the fan speed based on temperature and humidity inputs, with the output being a gradual fan speed control. (PWM). The test results show that the system can reduce energy consumption by up to 30% compared to the manual method, especially by reducing the unnecessary device idle time. Additionally, the system has an average response time of 200 ms to send sensor data to the application and receive threshold updates from the user. With this approach, the research shows that the integration of IoT with fuzzy logic provides significant energy efficiency and enhances the user experience. This research also opens up opportunities for further development, such as the integration of machine learning technology for predicting facility usage patterns or the implementation of additional sensors for air quality detection. These findings support the implementation of IoT-based automated systems in public facilities to achieve energy efficiency and environmental sustainability.
Design of Smart Green House Using pH and Water Temperature Optimization in Lettuce, Hydraulic Plant Media based on Arduino Uno Weisrawei, Yosef; Prasetya, Dwi Arman; Setiawan, Aries Boedi
Internet of Things and Artificial Intelligence Journal Vol. 1 No. 1 (2021): Volume 1 Issue 1, 2021 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (741.574 KB) | DOI: 10.31763/iota.v1i1.356

Abstract

In terms of cultivating lettuce using hydroponic media there are several things that mustbe considered such as pH levels, water temperature and sufficient light requirements.Manually checking is done so badly by the farmer that it takes a lot of time, therefore an automation system is needed in this case to overcome routine checks. This system is an alternative to modern control systems to optimize the control of pH levels, water temperature of Arduino-based lettuce plants, and the addition of a 40 watt LED lamp, pH measurement using the SEN0161 pH sensor, for measuring water temperature using the Ds18b20 sensor. Control of pH and water temperature is carried out automatically, using a peltier as a coolant and a selenoid valve as a dropping liquid pH until it reaches the required value, i.e., a pH level of 6.0-7.0, a water temperature <27 ° C and a 40 watt LED lamp as an addition to light intake in plants The stability of water temperature and pH levels that are always maintained by this tool can save time for farmers in routine checking of pH and water temperature, this tool also produces better growth of lettuce compared to the usual method.
PREDIKSI HARGA SAHAM SEKTOR ENERGI MENGGUNAKAN METODE SPATIAL TEMPORAL ATTENTION-BASED CONVOLUTIONAL NETWORK BERDASARKAN DATA TEKS DAN NUMERIK Anggraini, Novita; Arman Prasetya, Dwi; Trimono, Trimono
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13443

Abstract

Perubahan harga saham dipengaruhi oleh berbagai faktor, termasuk data historis harga saham dan sentimen yang terkandung dalam berita keuangan. Penelitian ini bertujuan untuk mengembangkan model prediksi harga saham yang lebih akurat dengan memanfaatkan Spatial-Temporal Attention-Based Convolutional Network (STACN). Model ini dirancang untuk menggali hubungan kompleks antara data historis harga saham dan informasi dari berita finansial. Metode yang digunakan melibatkan integrasi Convolutional Neural Network (CNN) untuk mengekstraksi fitur dari thought vectors berita, Long Short-Term Memory (LSTM) untuk menangkap pola temporal dari data harga saham, dan Spatial-Temporal Attention Network (STAN) untuk memberikan perhatian pada fitur-fitur yang relevan. Studi kasus dilakukan pada saham sektor energi yang terdaftar di Bursa Efek Indonesia, dengan menggunakan data historis harga saham dan berita dari portal bisnis Indonesia. Hasil eksperimen menunjukkan bahwa model STACN Bi-LSTM menghasilkan akurasi yang lebih tinggi dibandingkan dengan model-model lain seperti LSTM dan Bi-LSTM konvensional, dengan nilai MAE sebesar 24.2776, RMSE 32.9127, dan R² 0.9365. Temuan ini membuktikan bahwa integrasi analisis spasial-temporal dan mekanisme perhatian efektif dalam meningkatkan akurasi prediksi harga saham.
KLASIFIKASI PERULANGAN KANKER TIROID MENGGUNAKAN STACK ENSEMBLE DAN SMOTE Rahmanda Putri, Endin; Arman Prasetya, Dwi; Junaidi, Achmad
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13616

Abstract

Kanker tiroid berdiferensiasi (Differentiated Thyroid Cancer/DTC) memiliki tingkat perulangan sekitar 20%, sehingga identifikasi sejak dini menjadi krusial untuk intervensi dan rencana perawatan terhadap kekambuhan. Penelitian ini menggunakan dataset dari UCI Machine Learning Repository yang berisi 17 atribut klinis pasien dengan proporsi data latih dan uji 80:20. Untuk menangani ketidakseimbangan kelas, diterapkan Synthetic Minority Over-sampling Technique (SMOTE). Model Decision Tree, Support Vector Machine (SVM), dan Logistic Regression digunakan sebagai base learner, sementara meta learner dipilih dari salah satu algoritma tersebut untuk membentuk Stack Ensemble Learning. Decision Tree adalah model paling stabil, dengan akurasi 97% baik sebagai model tunggal, dengan SMOTE, maupun sebagai meta learner dalam Stack Ensemble. SVM memiliki akurasi 83% pada dataset asli, yang meningkat menjadi 94% setelah diterapkan SMOTE. Logistic Regression menunjukkan akurasi 96% di semua skenario. Stack Ensemble dengan meta learning Decision Tree dan Logistic Regression mempertahankan akurasi 97%, sedangkan SVM sebagai meta learner menunjukkan penurunan AUC. Analisis kurva ROC (Receiver Operating Characteristics) menunjukkan bahwa Stack Ensemble dan SMOTE meningkatkan AUC untuk Logistic Regression dan Decision Tree, namun SVM sebagai meta learner dengan dataset SMOTE mengalami penurunan performa dengan nilai terendah 0,94. Hasil ini membuktikan bahwa kombinasi Stack Ensemble dan SMOTE efektif dalam menangani ketidakseimbangan data pada dataset Differentiated Thyroid Cancer Recurrence.
Co-Authors ', Nachrowie ., Humaidi A. A. Ngurah Gunawan Aan Nehru Awanto Achmad Junaidi Aditya, Wigananda Firdaus Putra Agustina, Fadlila Akio Kitagawa Alam, Fajar Indra Nur Ali, Munawar Amrullah, Ahmad Wildan Andre Leto Andrew Arjunanda Yasin Anggraini Puspita Sari Anindha Lazuardi Aries Boedi Setiawan Arifani, Kahpi Baiquni Arifuddin, Rahman Arum Puspita Ayu Atiana Sofia Kaci Awang, Wan Suryani Wan Azizah, Alisa Jihan Aziziyah, Luqna Baidowi Baidowi Baidowi Baidowi Bambang Nurdewanto Barus, Indra Basitha F Hidayatulail Cahyani Kuswardhani, Hajjar Ayu cahyono, wahyu eko Candra Laksana Damai Arbaus, Damai Damaliana, Aviolla Terza Danang - Destiawan Danang Destiawan Desyderius Minggu Dicky Kurniawan Diyasa, I Gede Susrama Mas Dody Pintarko Dwi Agung Ayubi E, Nachrowie Ekawati, Anies Eko Wahyu Prasetyo Elta Sonalitha Sonalitha Erik Roma Hurmuzi Fahrudin, Tresna Maulana Farhans, Muhammad Izzudin Febriyanti, Alvi Yuana Firdaus Firdaus Firza Prima Aditiawan Gatut Yulisusianto Halim, Christina Hari Fitria Windi Hendry Yudha Pratama Hesti Sholikah, Hesti Hidayatulail, Basitha F Hindrayani, Kartika Maulida Hiroshi Suzuki Hurmuzi, Erik Roma Ibrahim, Mohd Zamri Bin Iffadah, Adhisa Shilfadianis Indra Barus Irsyadi, Muhamad Haidir Ismail, Jefri Abdurrozak Januar, Teddy Jariyah Jeki Saputra Junita Junita Kartika Maulida Hindrayani Kassim, Anuar bin Mohamed Kholid, Fajar Kukuh Yudhistiro, Kukuh Kurniawan, Dicky Kusuma, Dwi Febri Chandra Kusuma, Firdaus Miftakh Kuswardana, Dendy Arizki Laksana, Candra Lestari, Amanda Ayu Dewi Lisanthoni, Angela Maldini, Andry Syva Mas Diyasa, I Gede Susrama Maulidiyyah, Nova Auliyatul Mohammad Ansori Mohammad, Bawazir Fadhil Muhaimin, Amri Muhammad Ansori Muhammad Muharrom Al Haromainy Mulyadi Mulyadi Nachrowie Nachrowie Nachrowie, Nachrowie Nambo Hidetaka Ningrum, Imelda Widya Ninik Sisharini Ninis Herawati Norma Windiyanti Novita Anggraini Nur Rachman Nur Rachman Supatmana Muda Nur Rochman Nur Rochman Nurhalizah, Cesaria Deby Prakoso, Akbar Tri Puput Dani Prasetyo Adi Putri, Irma Amanda Rabi, Abd. Rahman Arifuddin Rahmanda Putri, Endin Rahmawati, Adinda Aulia Respati Respati Rosariawari, Firra Rudi Wilson Sagita Rochman Salim, Hotimah Masdan Santika, Surya Saputra, Wahyu Syaifullah Jauharis Sari, Andina Paramita Siswanto Siswanto Siti Nuurlaily Rukmana, Siti Nuurlaily Stanislaus Yoseph Subairi Subairi Sumartono Sumartono Sumartono Suprayogi Suprayogi Suprayogi Suprayogi Surya Nanda Santika, Surya Takahiro Kitajima Takashi Yasuno Tresna Maulana Fahrudin Trimono Trimono, Trimono Wahyu Dirgantara Wahyuni, Dinar H S wangge, ferdinandus Weisrawei, Yosef Yasin, Andrew Arjunanda Yohanes U D Sipul Yosef Weisrawei Yosua Satria Bara Harmoni Yunia Dwie Nurchayanie Yusaq Tomo Ardianto