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All Journal ILKOM Jurnal Ilmiah Tematik : Jurnal Teknologi Informasi Komunikasi Djtechno: Jurnal Teknologi Informasi International Journal Software Engineering and Computer Science (IJSECS)
Budi Sutomo
Universitas Dharma Wacana
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Data Visualization of Kemplang Sales Using Looker Studio at Arion Souvenir Shop Yuda Restu Fauzi; Budi Sutomo
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3486

Abstract

Arion Souvenir Shop, located in Metro City, offers grilled kemplang snacks, a traditional Indonesian delicacy. The shop encounters several challenges, including the difficulty in revealing actual monthly sales trends, identifying the most popular kemplang variants, and detecting the annual sales cycle. Grilled kemplang is available in three variants: jumbo, medium, and small. To address these challenges, this study visualizes kemplang sales data for the years 2022–2024 using Google Looker Studio. The visualization includes various graphical formats such as bar charts, pie charts, pivot tables, and line charts. The results of the analysis show that sales were consistently highest in January across the three years, indicating a strong seasonal trend. Additionally, the small kemplang variant emerged as the most popular choice, consistently outperforming the other variants in monthly sales. The study also observed a slight decline in overall sales over the three-year period. This research contributes significantly to the analysis of local product sales data by leveraging Looker Studio for interactive trend visualization. It provides practical recommendations for local business owners and empirical evidence on the application of data visualization tools in strategic decision-making. The insights gained from this study can help businesses optimize their sales strategies, improve inventory management, and enhance customer engagement
Utilizing IoT Technology for Soil Moisture Management through Integration of pH and Moisture Sensors in an Android Application for Rice Farming Budi Sutomo; Tri Aristi Saputri; Ilham Wahyu Satria
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3538

Abstract

In this study, to help address the challenges involved in rice production (especially optimizing soil and crops in dryland areas that are prone to water scarcity and variable soil pH), we leveraged IoT technology. An IoT soil moisture and pH monitoring system to track soil moisture status in real time using ESP8266 microcontroller along with dedicated sensors coupled with Blynk as a user interface. The system provides instant alerts to farmers on mobile devices about irrigation and soil pH modifications, thereby minimizing the direct dependence on time-consuming maintenance of vegetation monitoring. The results from a trial of 28 upland rice plots in dryland agricultural areas showed that the irrigation alert system provided timely irrigation alerts, improved water use efficiency by up to 30% and increased yield by 15–20% compared to conventional techniques. The significance of these findings in terms of practical applications are water resource management, optimal soil conditions for rice farming and to promote sustainable agricultural practices on the other hand. Furthermore, the system can be applied to other crops in a similar manner to enhance food security at national and local scales despite climate change and resource constraints.
Forecasting New Student Admissions at Muhammadiyah Elementary School Metro Using the Weighted Moving Average Method Clara Tintan Melati; Budi Sutomo
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3541

Abstract

SD Muhammadiyah Metro Lampung was established in 1968 with the Decree of the Muhammadiyah Education, Teaching, and Culture Council Number 664/I-057/LP-68/1977. Since then, this institution has emphasized the importance of providing quality education and creating an environment that supports the development of students. The purpose of this study is to predict the acceptance of new students in the coming period, so that it can be the basis for compiling a more appropriate educational planning strategy that is in accordance with real needs. To realize all of this, the main analysis tool is the Weighted Moving Average (WMA). This method is different from other modeling methods such as exponential smoothing and ARIMA because this method provides greater weight based on current data, so that estimates are more sensitive to current trends and more credible as a decision-making tool. The results of the WMA forecast provide schools with the opportunity to estimate the need for resources needed (including teaching staff, supporting facilities, and classroom allocation) to ensure that the education process is running well and correctly. In addition, this technique is a way to assess developing or abolishing admission policies. However, forecasts are only as good as historical data and cannot predict the presence of external factors that affect outcomes
Analisis Sentimen Publik Terhadap Program Makan Bergizi Gratis Di Media Sosial Berbasis Transfer Learning Andriyas Ariya Firmansyah; Budi Sutomo
TEMATIK Vol. 13 No. 1 (2026): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2026
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v13i1.2960

Abstract

Program Makan Bergizi Gratis menjadi salah satu kebijakan yang banyak dibicarakan di media sosial karena berkaitan langsung dengan isu gizi, distribusi bantuan, dan pelaksanaan program pemerintah. Penelitian ini bertujuan menganalisis sentimen masyarakat terhadap Program Makan Bergizi Gratis berdasarkan percakapan di Twitter sekaligus menguji kinerja model RoBERTa dalam klasifikasi sentimen. Data penelitian diperoleh melalui teknik scraping Twitter pada periode Januari 2025 sampai Maret 2026 dan menghasilkan 3.566 tweet yang disimpan dalam format CSV. Data selanjutnya diproses melalui tahap pre-processing yang meliputi cleaning, case folding, normalisasi kata, tokenisasi, dan stopword removal. Setelah itu, teks diterjemahkan ke dalam bahasa Inggris dan diberi label sentimen menggunakan metode VADER berdasarkan nilai compound score yang dikategorikan menjadi tiga kelas: yaitu positif, negatif, dan netral. Model RoBERTa dikembangkan dengan Hugging Face dan PyTorch, dengan pembagian dataset untuk 70% data pelatihan dan 30% untuk pengujian, serta menerapkan early stopping dengan patience 5 dan maksimum 30 epoch. Temuan penelitian mengungkap bahwa sentimen positif mendominasi dengan 70,27%, diikuti sentimen negatif 22,04%, dan netral 7,68%. Dari sisi performa model, RoBERTa menghasilkan accuracy 0,8709 serta macro F1-score 0,7970, menunjukkan efektivitas RoBERTa sekaligus menyoroti kendala pada kelas netral yang sulit diklasifikasikan. Pencapaian ini membuktikan bahwa RoBERTa cukup andal untuk analisis sentimen pada data Twitter, meskipun klasifikasi sentimen netral masih perlu ditingkatkan.
IMPLEMENTATION OF A WEB-BASED NETWORK PERFORMANCE MONITORING SYSTEM USING THE QUALITY OF SERVICE (QOS) METHOD ON MIKROTIK ROUTER INFRASTRUCTURE Alingga Rayhan Pratama; Budi Sutomo
Djtechno: Jurnal Teknologi Informasi Vol 7, No 2 (2026): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v7i2.8797

Abstract

This study implements a web-based network performance monitoring system integrated with a MikroTik router using Quality of Service (QoS) parameters. The system uses PHP, MySQL, and the RouterOS API to acquire interface traffic and ping results. The measured parameters include throughput, latency, jitter, and packet loss. Measurement records are stored in a database and displayed as current and historical monitoring data. The test results show that the system can read router resources, calculate QoS values, display real-time traffic, and help administrators monitor network quality in a centralized manner.
Optimization of Intelligent Traffic Control Based on iot and Reinforcement Learning for Congestion Reduction in Smart Cities Tri Aristi Saputri; Budi Sutomo; Dimas Akbar Maulana; Hendika Purnomo
ILKOM Jurnal Ilmiah Vol 18, No 2 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i2.3260.320-332

Abstract

Traffic congestion has become a major challenge in Indonesian urban areas due to rapid vehicle growth and the limited adaptability of conventional traffic signal control systems. Most existing Deep Reinforcement Learning (DRL)-based traffic signal control studies adopt a free-phase selection approach, which assumes full agent freedom in determining signal phases — an assumption fundamentally incompatible with fixed phase-sequence regulations in Indonesian urban infrastructure — and rely on synthetic traffic data that fails to represent motorcycle-dominated traffic conditions. Furthermore, existing DQN-based approaches treat all traffic density conditions uniformly, without utilizing IoT-derived density categories for context-aware decision-making. To address these gaps, this study proposes a manual phase rotation mechanism with constrained actions (15, 30, and 60 seconds) compatible with existing fixed-phase infrastructure without hardware modifications, real-world IoT CCTV data from four intersections in Metro City processed using the YOLOv11 model to generate Low, Medium, and High traffic density categories as a representative training foundation for Indonesian urban traffic conditions, and a category-based action bias mechanism that adjusts DQN Q-value estimates according to IoT-derived traffic density, enabling context-aware signal duration selection. The DQN agent interacts with the SUMO simulation environment through the TraCI interface, receiving real-time traffic states comprising vehicle count, queue length, waiting time, average speed, density category, and delta queue, and selecting optimal green signal durations based on an epsilon-greedy exploration strategy and experience replay mechanism over 1,100 training episodes. Training yielded a 39.2% improvement in total reward and a 6.6% reduction in average waiting time. The best-performing model, obtained at episode 1050, achieved an 8.6% reduction in average waiting time and an 11.7% increase in traffic throughput compared to the fixed-time baseline. These results demonstrate that the proposed framework contributes three concrete advances for adaptive traffic signal control, a constrained-action DQN that is fully compatible with real-world fixed-phase infrastructure, a real-world IoT CCTV dataset as a representative data foundation for Indonesian traffic conditions, and a category-based bias mechanism for context-aware control — collectively offering a deployable, infrastructure-compatible, and replicable solution for traffic authorities and local governments advancing the smart city agenda in Indonesia.
Co-Authors Alingga Rayhan Pratama Andriyas Ariya Firmansyah Clara Tintan Melati Dimas Akbar Maulana Hendika Purnomo Ilham Wahyu Satria Tri Aristi Saputri Yuda Restu Fauzi