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All Journal JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Jurnal Media Informatika Futures in Agro-Food Economics and Logistics Analytics Journal Inovbiz : Jurnal Inovasi Bisnis
Mas’ud Hermansyah
Politeknik Negeri Jember
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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SMART ENVIRONMENTAL HEALTH MONITORING SYSTEM BERBASIS IOT UNTUK MENINGKATKAN KESADARAN KESEHATAN MASYARAKAT Rizki Prasetyo Tulodo; Lukmanul Khakim; Mas’ud Hermansyah; Irfan Nurdiansyah
PENDIDIKAN SAINS DAN TEKNOLOGI Vol 12 No 4 (2025)
Publisher : STKIP PGRI Situbondo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47668/edusaintek.v12i4.2069

Abstract

Kesehatan lingkungan merupakan faktor penting dalam mendukung kesejahteraan masyarakat. Namun, di Kabupaten Tegal masih ditemukan berbagai permasalahan seperti tingginya angka kematian ibu, bayi, dan prevalensi stunting yang berpotensi diperparah oleh kondisi lingkungan yang kurang sehat. Salah satu solusi yang dapat diterapkan adalah penggunaan teknologi Internet of Things (IoT) untuk memantau kondisi lingkungan secara real-time. Penelitian ini bertujuan untuk mengembangkan sistem pemantauan kesehatan lingkungan berbasis IoT menggunakan mikrokontroler ESP32 yang terhubung dengan sensor DHT22 (untuk suhu dan kelembaban) serta MQ-135 (untuk kualitas udara). Data yang diperoleh dikirim ke platform cloud ThingSpeak untuk ditampilkan dalam bentuk grafik pemantauan digital. Metode penelitian ini menggunakan pendekatan eksperimental dengan pengujian sensor terhadap alat ukur pembanding untuk mengetahui tingkat akurasi sistem. Hasil pengujian menunjukkan bahwa nilai galat rata-rata pengukuran suhu adalah 2–4%, kelembaban 3–5%, dan kualitas udara sekitar 4%. Nilai tersebut masih dalam batas toleransi akurasi sensor, sehingga sistem mampu bekerja dengan baik dalam memantau kondisi lingkungan. Kesimpulan dari penelitian ini menunjukkan bahwa sistem pemantauan berbasis IoT ini dapat menjadi solusi inovatif yang aplikatif dan edukatif untuk meningkatkan kesadaran serta literasi masyarakat terhadap kesehatan lingkungan. Pengembangan lanjutan disarankan untuk menambah parameter lingkungan lain serta integrasi notifikasi otomatis agar lebih responsif terhadap perubahan kondisi lingkungan
Smart Reminder: Sistem Pengingat Tugas Berbasis ReactJS dan Google Apps Script untuk Manajemen Proyek Tim: No Akas Bagus Setiawan; Mas’ud Hermansyah
Jurnal Media Informatika Vol. 6 No. 6 (2025): Edisi Desember 2025
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jumin.v6i6.7461

Abstract

Manajemen tugas yang efisien merupakan tantangan utama dalam organisasi modern, terutama dalam mengelola tenggat waktu serta memastikan kolaborasi yang optimal antaranggota tim. Penelitian ini bertujuan mengembangkan sistem otomatisasi penjadwalan dan pengingat tugas berbasis cloud dengan mengintegrasikan ReactJS sebagai frontend untuk input data, serta Google Apps Script dan Google Calendar sebagai backend. Melalui sistem ini, data tugas yang dimasukkan melalui formulir ReactJS dikirim secara real-time ke endpoint Google Apps Script, kemudian dijadwalkan secara otomatis ke Google Calendar lengkap dengan notifikasi pengingat sebelum batas waktu penyelesaian. Metodologi penelitian mencakup perancangan antarmuka pengguna berbasis prinsip UI/UX, pengembangan skrip pemrosesan otomatis di Apps Script, serta pengujian sistem dalam lingkungan kerja nyata. Hasil pengujian menunjukkan adanya peningkatan signifikan dalam kepatuhan terhadap tenggat waktu dan efisiensi pemantauan tugas, disertai penurunan beban administratif dan potensi human error pada proses penjadwalan manual. Berdasarkan hasil survei kepuasan pengguna, 87% responden menyatakan sistem ini mempermudah pengelolaan tugas dan membantu dalam mengingat deadline. Sebagian besar responden juga menilai bahwa formulir input berbasis ReactJS mudah digunakan dan validasi datanya berjalan efektif dalam meminimalkan kesalahan input. Dengan hasil tersebut, sistem berbasis ReactJS dan Apps Script ini dapat dijadikan solusi inovatif dan skalabel untuk mendukung manajemen tugas dan kolaborasi tim berbasis cloud di berbagai lingkungan organisasi.
Environmental Characterization of Vanilla Processing Facilities Using IoT Monitoring for Material Design Considerations Shabrina Choirunnisa; Wendy Triadji Nugroho; Mas’ud Hermansyah; Bagus Putu Yudhia Kurniawan; Andarula Galushasti; Khafidurrohman Agustianto
Futures in Agro-Food Economics and Logistics Analytics Journal Vol. 1 No. 2 (2025): June
Publisher : PT Litera Integra Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67580/fafela.v1i2.40

Abstract

This study aims to characterize the environmental conditions (temperature and relative humidity) in vanilla processing facilities using an Internet of Things (IoT)-based monitoring system. Monitoring was conducted in three main rooms: Boiling Room, Fermentation Room, and Drying Room. Temperature and humidity data were collected continuously and analyzed using descriptive and inferential statistics (One-Way ANOVA and Kruskal-Wallis) along with data visualization (boxplots). The results showed that the Boiling Room had the highest average temperature (43.75°C) with the largest fluctuation (CV = 46.42%). Meanwhile, the Fermentation Room recorded the highest average relative humidity (71.05%). Statistical tests indicated significant differences in temperature between rooms (p < 0.001). Based on these environmental characteristics, this study developed Material Design Considerations that recommend appropriate materials for each operational condition: high thermal stability and thermal fatigue resistance for the Boiling Room, and moisture resistance and corrosion resistance for the Fermentation Room. This approach bridges IoT data with engineering material selection to improve the reliability of vanilla processing facilities. The study provides practical contributions to integrating IoT technology with material design considerations in the vanilla agroindustry.
IoT-Based Environmental Characterization of Vanilla Processing Facilities Using a Rule-Based Approach Shabrina Choirunnisa; Bagus Putu Yudhia Kurniawan; Andarula Galushasti; Khafidurrohman Agustianto; Mas’ud Hermansyah
Futures in Agro-Food Economics and Logistics Analytics Journal Vol. 2 No. 1 (2025): December
Publisher : PT Litera Integra Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67580/fafela.v2i1.41

Abstract

Vanilla (Vanilla planifolia) is a high value plantation commodity whose quality after harvesting is highly dependent on the environment during processing. Temperature and relative humidity (RH) are particularly important as they influence moisture transfer, drying stability, microbial risk and processing duration. The study developed and evaluated an IoT-based environmental characterization system employing a rule-based control approach for a vanilla processing environment located in Rembangan, Jember, East Java, Indonesia. The research was designed as a field-oriented experimental study with distributed temperature and RH sensors connected to an IoT gateway and a local rule-based controller. For methodological validation, a synthetic pilot dataset was created, consisting of 336 observations over 14 consecutive days at hourly intervals from three monitoring zones. The environmental variables were characterized in space and time and then were controlled by predefined rules for the ventilation system. The results show that the mean temperature and mean RH of the baseline condition were 23.99 ± 1.86 °C and 82.63 ± 6.90%, respectively. After the rule-based control strategy was implemented, the mean temperature was maintained relatively stable at 23.96 ± 1.47 °C, and the mean RH decreased to 80.30 ± 4.79%.The percentage of observations within the pre-specified operating range of 22–28 °C and 70–85% RH increased from 57.7% during the baseline phase to 76.2% during the rule-based phase. The paired comparison of daily observations showed a significant reduction in RH (p < 0.001) while the difference in temperature was not statistically significant (p = 0.593). These results demonstrate that a lightweight rule-based IoT architecture can improve environmental stability without the need for computationally intensive artificial intelligence. The proposed framework provides a practical basis for the development of a field-validated environmental management system for vanilla post-harvest processing in highland agricultural environments
Early Detection of Financial Distress at PT. Garudafood Putra Putri Jaya Tbk Using Machine Learning Algorithms Muhammad Bahanan; Mas’ud Hermansyah; Lukman Hakim; Hardian Dwi Utomo
Inovbiz: Jurnal Inovasi Bisnis Vol 14 No 1 (2026): Edition June 2026
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/inovbiz.v14.i1.1560

Abstract

This study aims to develop an early warning system to detect potential financial distress at PT Garudafood Putra Putri Jaya Tbk using Machine Learning (ML) algorithms. A quantitative case study approach was applied using the company’s publicly available quarterly financial reports from 2019 to 2024. Five ML algorithms were tested: Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The Random Forest algorithm achieved the highest accuracy of 85.71%, with a precision of 100%, recall of 66.67%, and an F1-score of 80%. Operating Profit Margin and Debt to Asset Ratio were identified as the most significant indicators in detecting financial distress. The proposed model can serve as a decision-support tool for management, investors, and regulators to proactively anticipate financial problems and reduce bankruptcy risk through early intervention. Keywords: Abstract, aim, scope, result
Co-Authors Andarula Galushasti Bagus Putu Yudhia Kurniawan Hardian Dwi Utomo Irfan Nurdiansyah Khafidurrohman Agustianto Lukman Hakim Lukmanul Khakim Muhammad Bahanan Rizki Prasetyo Tulodo Setiawan, Akas Bagus Wendy Triadji Nugroho