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All Journal Jurnal Simetris Jurnal Mantik Penusa Zero : Jurnal Sains, Matematika, dan Terapan Jurnal Mantik RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Jurnal Dialektika Informatika (Detika) KLIK: Kajian Ilmiah Informatika dan Komputer Muria Jurnal Layanan Masyarakat Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA)
Sugiharto, Wibowo Harry
Universitas Muria Kudus
Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences

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Pengembangan Sistem Sortir Otomatis untuk Jeruk Citrus: Integrasi Teknologi Sensor dan Algoritma Rule-Based Muhammad Imam Ghozali; Aditya Akbar Riadi; Dwyan Akbar Putra; Wibowo Harry Sugiharto
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 3 (2024): RESOLUSI January 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i3.1649

Abstract

This study aims to develop an orange harvest revenue prediction system that integrates color-based sorting technology and rule-based data analysis. With the increasing demand for oranges in Indonesia, efficiency and accuracy in the sorting process and revenue prediction are of utmost importance. The developed system utilizes the TCS34725 color sensor to classify oranges based on maturity level and employs a rule-based method to predict harvest revenue based on sorting data and external factors such as weather conditions and market prices. Field testing results indicate that this system significantly improves sorting accuracy and provides accurate revenue predictions. The implementation of this technology in the orange industry offers potential enhancements in operational efficiency and profitability. This research contributes importantly to the application of sensor technology and data analysis in agriculture, demonstrating how technological innovation can help address challenges in the orange industry and the broader agricultural sector.
Analisis Sentimen Pinjaman Online Di Media Sosial Twitter Menggunakan Metode Naive Bayes Muhammad Imam Ghozali; Wibowo Harry Sugiharto; Ary Fajar Iskandar
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.936

Abstract

Sentiment analysis is conducted to measure public opinion tendencies towards ongoing or past events. One of the cases analyzed in this study is Online Loans, commonly known as "Pinjol" in Indonesian. The research data regarding Online Loans was collected from the Twitter social media platform using the keyword "Pinjaman Online." The analysis method employed in this study is Naïve Bayes. Prior to the sentiment analysis process, text data was obtained through crawling from the Twitter API using the Rapidminer application. The data was then subjected to text pre-processing. Subsequently, the data underwent TF-IDF weighting. The results of this research demonstrate the tendencies of positive and negative sentiment conflicts within each tweet discussed by Twitter users regarding Online Loans. The conclusion drawn from the sentiment analysis using the Naïve Bayes classification algorithm with data obtained from Twitter concerning Online Loans is as follows: Out of the 2931 data used, after undergoing text pre-processing, a total of 2912 data were available. Among them, negative sentiment accounted for 68.61% with 1998 data, while positive sentiment accounted for 31.39% with 914 data. The sentiment analysis of Twitter users regarding Online Loans achieved an accuracy rate of 80%.
Performance Comparison of WSN Topologies in IoT-Based Water Quality Monitoring Systems Ghozali, Muhammad Imam; Murti, Alif Catur; Sugiharto, Wibowo Harry; Roder, Klaus
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 2 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i2.25706

Abstract

This study, we quantify how WSN topology shapes QoS for IoT water-quality monitoring and derive deployment rules. Five topologies (Hybrid Star-Mesh, Cluster Tree, Full Mesh, Ring, ZigBee Star; 20 nodes) were simulated in NS-3 for 10 independent runs with random seeds. Our mathematical contribution is a compact QoS model set-latency LLL, packet-loss PlossP_{\text{loss}} Ploss, bandwidth usage UBU_BUB, and throughput TTT-used to compare topologies and compute relative/absolute improvements. Statistics report mean±SD with 95% confidence intervals from Student's t-distribution; pairwise Mann-Whitney tests with Benjamini-Hochberg FDR control (α=0.05) yield compact-letter displays; Cliff's δ quantifies effect sizes. Results: Hybrid Star-Mesh minimizes latency/loss while maximizing throughput; Ring is consistently inferior; Cluster Tree and ZigBee Star are mid-range; Full Mesh trades redundancy for delay and bandwidth. These models produce actionable guidance for aquaculture (real-time dissolved-oxygen) and urban drinking-water safety, and motivate multi-objective optimization (latency-throughput-energy) toward Pareto-optimal designs.
Penilaian Kualitas Air Secara Real-Time Menggunakan IoTWQI dan Internet of Things Wibowo Harry Sugiharto; Ali Bardadi; Eric Alfonsius
Jurnal Ilmiah Sistem Informasi Akuntansi Vol. 5 No. 1 (2025): Volume 5, Nomor 1, June 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jimasia.v5i1.489

Abstract

Pemantauan kualitas air sangat penting dalam pengelolaan lingkungan, namun metode tradisional yang melibatkan pengambilan sampel secara manual dan analisis laboratorium memerlukan waktu lama, biaya tinggi, serta rentan terhadap keterlambatan, sehingga membatasi pengambilan keputusan secara tepat waktu. Penelitian ini mengatasi tantangan tersebut dengan mengimplementasikan sistem pemantauan kualitas air secara real-time yang memanfaatkan sensor berbasis IoT dan kerangka kerja Internet of Things Water Quality Index (IOTWQI). Sistem ini mengintegrasikan berbagai sensor, termasuk pH, TDS, suhu, kekeruhan, dissolved oxygen (DO), dan electrical conductivity (EC), untuk mengumpulkan data secara kontinu. Data tersebut diproses oleh mikrokontroler dan dikirimkan ke server cloud untuk divisualisasikan melalui dashboard daring. Sistem ini memungkinkan deteksi dini terhadap pencemaran dan mendukung pengelolaan sumber daya air secara proaktif. Pengujian dilakukan pada skala laboratorium dan menunjukkan akurasi tinggi pada berbagai parameter. Sensor suhu (DS18B20) mencatat rata-rata galat sebesar 1,46% dengan akurasi 98,54%, sementara sensor pH mencapai akurasi 96,85% dengan galat 3,15%. Sensor EC menunjukkan kinerja tertinggi dengan akurasi 99,81% dan galat 0,189%, sedangkan sensor DO mencapai akurasi 98,14% dengan galat 1,86%. Hasil ini memvalidasi keandalan sistem untuk pemantauan secara real-time. Pekerjaan selanjutnya akan difokuskan pada uji lapangan dan integrasi dengan kerangka kerja pengelolaan air yang lebih luas guna meningkatkan skalabilitas dan penerapan praktis
Co-Authors Aditya Akbar Riadi Afifi, Zaenal Ahmad Abdul Chamid Alfonsius, Eric Ali Bardadi Ary Fajar Iskandar Dandy Wibowo Dwyan Akbar Putra Ehwan, Rif'an Zaenal M. Bachrul Ulum Firmansyah Muhammad Imam Ghozali Murti, Alif Catur Rizal Baihaqi Roder, Klaus RR. Ella Evrita Hestiandari Thoyyibul Al Fit