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The Determination of Electronic Goods Inventory at Rahmah Store Using the Fuzzy Tsukamoto Method Jannah, Ghina Raodatul; Bittara, Andi Ghizzania Sirih; Udin, Alvin Mas; Nasrullah, Asmaul Husna; Adiba, Fhatiah
Media of Computer Science Vol. 1 No. 2 (2024): December 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i2.204

Abstract

Toko Rahmah is faced with the challenge of determining the optimal inventory of electronic goods to avoid excess or shortage of inventory. The uncertainty of demand and large sales often leads to inefficient inventory management. This study aims to apply the Tsukamoto fuzzy method in determining the optimal inventory of electronic goods at Toko Rahmah. Using this method will increase the accuracy of managing inventory and reduce the risk of excess or shortage of inventory. Therefore, in this study, the Tsukamoto fuzzy method is used to model and overcome the uncertainty of electronic goods inventory. Sales and demand data serve as output to the fuzzy system. The steps taken include forming a fuzzy set, applying fuzzy rules, and performing defuzzification to get an output value that is used as an inventory quantity recommendation. The results of this study were tested using 2 ways, namely using the Netbeans application system and using excel. These two ways are done to see how accurate or suitable the results obtained are. The accuracy results show that the average accuracy is 0.41 from 22 existing data, which is where the system is able to provide fairly accurate recommendations in determining the inventory of goods at Toko Rahmah. This method reduces the risk of excess or shortage of inventory and increases efficiency in managing inventory.
Implementation of Smart Farming for Oyster Mushroom Cultivation Based on Wireless Sensor Network Using ESP8266 Wahid, Abdul; Syahbani, Dimas; Adiba, Fhatiah
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 2 (2023): Volume 3 Issue 2, 2023 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i2.610

Abstract

Internet of Things (IoT) technology can facilitate daily work in various fields. This study aims to implement smart farming for oyster mushroom cultivation based on Wireless Sensor Network (WSN) and ESP8266. The sensors used are temperature and humidity sensors with NodeMCU ESP8266 as a microcontroller so that they can take advantage of the Internet of Things (IoT) concept. The design of the prototype tool is designed in the form of a prototype box. The prototype box has 2 rooms that aim to apply the Wireless Sensor Network (WSN) method, so that data in each different room can be retrieved and then sent the data to the website. Tests were carried out to measure the comparison of temperature and humidity sensors with manual measurement tools. The results of this study show an absolute error average of 0.606% for temperature data and an absolute error of 0.627% for humidity data. This shows that the overall system is good and responsive.
Hybrid Electrical Interchange System in IoT-Based Egg-Hatching Equipment Parenreng, Jumadi Mabe; Wahyuni , Maya Sari; Lia, Resky Amalia; Muliadi, Muliadi; Adiba, Fhatiah
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i2.730

Abstract

Manual egg hatching still requires time and human labor every day to regulate temperature, adjust humidity, and turn the eggs. This egg hatcher works using solar panels as an alternative energy source. This study aims to design and determine the results of the effectiveness of testing the hybrid electrical interchange system on IoT-based egg hatchers. The research method used is the R&D method. Based on the results of the research, switching energy sources is declared valid because the tools and applications are integrated. The average voltage difference in the battery in charging condition by turning on the tool is -0.01 Volts, proving that even though it is in charging condition when the tool is turned on, the voltage in the battery will still decrease. The measurement results of the average daily energy demand on the hatchery by applying a hybrid electrical interchange system is 0.142 kWh and without applying the system 0.163 kWh, proving by applying a hybrid electrical interchange system device more efficient use of PLN electricity due to assistance from PLTS. On-off automation of lights and fans can keep the temperature at an ideal state of 37°C-39°C, thus affecting the egg-hatching process. On-off automation using a relay connected to a mist maker also affects keeping humidity at 55%-65% humidity, humidity also affects the egg-hatching process, where the success rate in hatching eggs is maximized. Based on the results of tests carried out by the hybrid electrical interchange system on IoT-based egg hatchers, it can be concluded that this tool can maintain the stability of temperature and humidity automatically in egg hatchers well until the eggs hatch.
Internet-based Design of Hydroponic Plants Monitoring and Automation Control Systems Parenreng, Jumadi Mabe; Andani, Andi Ferry Adlian Tri; Yahya, Muhammad; Adiba, Fhatiah
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i2.744

Abstract

Melons are one of the fruit types widely favored in the market due to their high content of vitamins, minerals, and water. Melon plants are challenging to cultivate when environmental conditions such as soil and air do not align with their characteristics. One way to address this is through hydroponic cultivation, which reduces the interaction of melon fruits with the air and environment. However, this method has a drawback in that the nutrient solution and water circulation of the plants must be continuously monitored. Therefore, a system is needed to automatically monitor and control the conditions of hydroponic plant growth with the assistance of IoT technology. This research proposes the Design and Implementation of a Monitoring and Automation System for Hydroponic Plant Control Based on the Internet of Things. The hydroponic system, specially designed for melon plants, is equipped with various sensors that can monitor soil nutrients in real time through mobile devices. Based on the test results, the TDS sensor yielded a result of 1313 PPM, the pH Water sensor showed 50.1, and the system also measured air temperature and humidity using DHT22, with air temperature at 29.5°C and humidity at 71.2%.
Aturan Asosiasi Berbasis Algoritma Apriori Pada Penjualan Retail Online Risal, Andi Akram Nur; Adiba, Fhatiah; Nurfitri, Andi Aisyah
Jurnal MediaTIK Volume 6 Issue 2, Mei (2023)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v6i2.1394

Abstract

Penjualan Retail pada data penelitian ini adalah hasil transaksi penjualan tokoh retail non tokoh di Inggris. Untuk meningkatkan penjualan salah satu cara yang harus dilakukan adalah dengan menganalisis arsip dari transaksi penjual untuk melihat produk yang paling sering dibeli oleh pelanggan menggunakan teknik data mining dengan algoritma apriori. Tujuan dari penelitian ini adalah untuk mendapatkan suatu aturan asosiasi produk apa saja yang selalu di beli oleh pelanggang dengan membandingkan aturan min support 10% dengan confidance 70%, min support 10% dengan confidance 50%, dan min support 10 dengan confidance 30%. Hasil min support 10% dengan confidance 70% adalah (Knitted Union Flag Hot Water Bottle) (White Hanging Heart T-Light Holder) min support 11% dengan confidance 100%, hasil dari min support 10% dengan confidance 30% dan 50% (Knitted Union Flag Hot Water Bottle) (White Hanging Heart T-Light Holder) dengan nilai min support 11% dengan confidance 100%. Berdasarkan hasil perbandingan diatas terbentuk sebuah aturan yaitu Jika membeli Knitted Union Flag Hot Water Bottle, maka akan membeli White Hanging Heart T-Light Holder
Implementasi Algoritma Backpropagation untuk Klasifikasi Kualitasi Susu Sapi Adiba, Fhatiah; Risal, Andi Akram Nur; Tahir, Muhlis
Jurnal MediaTIK Volume 6 Issue 2, Mei (2023)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v6i2.1395

Abstract

Susu sapi memiliki manfaat yang penting bagi kesehatan manusia karena mengandung banyak nutrisi yang dibutuhkan tubuh. Beberapa manfaatnya antara lain meningkatkan kekuatan tulang, meningkatkan system kekebalan tubuh, serta berperan dalam pertumbuhan dan perkembangan. Produsen susu sapi memiliki peran penting dalam menghasilkan susu yang berkualitas. Untuk membantu produsen susu sapi untuk mendapatkan kualitas susu yang baik maka dibutuhkan system untuk melakukan klasifikasi penentuan kualitas susu dengan menggunakan algoritme Bakcpropagation. Data yang digunakan dalam penelitian ini sebanyak 1059 data dengan dengan hasil jenis kualitas susu yaitu tinggi, standar, dan rendah. Penentuan kualitas susu berdasarkan 7 parameter yaitu pH, Suhu, Rasa, Bau, Lemak, Kekeruhan, dan Warna. Tahapan penelitian yang dilakukan memiliki tiga tahapan, yakni pertama adalah pemilihan data yang optimal, tahap kedua pemilihan parameter optimal yang akan digunakan dalam implementasi algoritme Backpropagation, dan tahap ketiga pengujian implementasi algoritme. Hasil akurasi dengan menggunakan metode pengujian k-fold dengan nilai k=3, learning rate=0,5, jumlah iterasi (epoch)=750, dan jumlah hidden layer=7 mendapatkan akurasi tinggi sebesar 97.923%. Hal ini dapat membantu produsen susu sapi untuk mendapatkan kualitas susu yang baik dan memberikan kontribusi dalam pengembangan teknologi klasifikasi menggunakan algoritme pembelajaran mesin di industri susu sapi.
Identifying Rice Plant Damage Due to Pest Attacks Using Convolutional Neural Networks Tenriola, Andi; Azis, Putri Alysia; Kaswar, Andi Baso; Adiba, Fhatiah; Andayani, Dyah Darma
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 1 (2025): February 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i1.6125

Abstract

Rice (Oryza Sativa) is an important crop for meeting global food needs; however, one of the main challenges in its cultivation is the attack of stem borer pests, which can cause significant damage. This study aims to identify the damage caused by these pest attacks using Convolutional Neural Networks (CNN) methods. We developed and trained several CNN architectures, including the proposed architecture, MobileNet, and EfficientNetB0, to detect pest attacks on rice. The dataset used consists of 700 images per class taken directly from the field, where the images depict rice plants that have been peeled or opened to inspect for the presence of pests, specifically stem borer pests. To enhance the quality and diversity of the dataset, we applied a rigorous selection process, ensuring that only high-quality images were used. Additionally, augmentation techniques such as rotation were employed to expand the dataset to 2000 images per class. Labeling was carried out carefully to ensure that each image accurately reflected the condition of the pest attack. The results of the study indicate that the proposed CNN model can identify damage with high accuracy, thereby contributing to efforts to increase rice production through early detection of pest attacks using computer vision technology.
Penerapan Data Science sebagai Upaya Meningkatkan Kompetensi Mahasiswa di Era Industri Modern Rivai, Andi Tenri Ola; Risal, Andi Akram Nur; Edy, Marwan Ramdhany; Adiba, Fhatiah; Kaswar, Andi Baso
TEKNOVOKASI : Jurnal Pengabdian Masyarakat Volume 3: Issue 2 (May 2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/teknovokasi.v3i2.8450

Abstract

Data Science adalah bidang multidisipliner yang menggabungkan statistik, analitik data, dan machine learning untuk mengolah data besar menjadi informasi yang bermakna berbasis Data. Program Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan pemahaman mahasiswa terhadap konsep dan penerapan Data Science melalui workshop berbasis praktik. Kegiatan dilaksanakan dalam bentuk workshop satu hari yang mencakup materi eksplorasi data, visualisasi, dan penerapan algoritma sederhana menggunakan Python dan Google Colab. Peserta yang terdiri dari mahasiswa program studi Teknologi Informasi Universitas Bosowa menunjukkan peningkatan pemahaman terkait Data Science dan keberhasilan dalam mengerjakan mini-proyek berbasis data. Keberhasilan kegiatan ini didukung oleh antusiasme peserta, fasilitas yang memadai, serta pendekatan pembelajaran yang aplikatif dan interaktif. Namun, terdapat beberapa hambatan seperti keterbatasan waktu, variasi tingkat kemampuan peserta, dan kendala koneksi internet saat pelatihan. Secara keseluruhan, pelatihan ini memberikan kontribusi nyata terhadap peningkatan literasi data dan keterampilan digital mahasiswa serta relevan untuk diterapkan secara berkelanjutan di institusi pendidikan tinggi.
Beyond Advice: Training Mentors in Ethics, Boundaries, and Trustworthy Mentoring Surianto, Dewi Fatmarani; Nasrullah, Asmaul Husnah; Hasnining, Ayu; Adiba, Fhatiah; Wardani, Ayu Tri
Jurnal Sipakatau: Inovasi Pengabdian Masyarakat Volume 2 Issue 4 June 2025: Jurnal Sipakatau
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/jsipakatau.v2i4.2525

Abstract

The Community Service Program aims to improve ethical competency among student mentors through a structured training program that focuses on five key areas: confidentiality, ethical communication, communication style, professional boundaries, and respecting mentee diversity. A total of 31 mentors participated in pre- and post-test assessments, allowing for a measurable analysis of knowledge development. The training was delivered online using Zoom and included interactive discussions, scenario analysis, and self-reflection sessions. Results showed significant improvements in all five indicators, particularly in understanding ethical communication (from 32.3% to 77.4% selecting the highest score), and appropriate communication style (from 41.9% to 80.6%). Even dimensions with high baseline scores, such as confidentiality (74.2%), experienced positive growth. The findings confirm that the training successfully improved participants’ ethical sensitivity, practical communication skills, and preparedness for real-world mentoring situations. This initiative contributed to the development of a responsible mentoring culture that aligns with the values ​​of empathy, professionalism, and inclusion. Future programs should consider expanding to include peer mentors from other faculties and provide ongoing support mechanisms to strengthen ethical mentoring practices.
Pelatihan Manajemen Waktu Untuk Meningkatkan Efektivitas Profesionalisme Mahasiswa Dalam Peran Mentoring Hasnining, Ayu; Nida Rifqi, Ainun; Febriansyah Ramadhan, Haekal; Baso, Fadhlirrahman; Adiba, Fhatiah
Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Volume 2 Issue No. 2: January 2025
Publisher : Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/kreativa.v2i2.20261

Abstract

Pengabdian ini bertujuan meningkatkan efektivitas pengelolaan waktu mahasiswa mentor melalui pelatihan berbasis analisis kebutuhan lapangan, mengintegrasikan pendekatan Eisenhower Matrix dan Teknik Pomodoro. Metode pelaksanaan meliputi survei awal, workshop interaktif, implementasi dalam skenario mentoring nyata, evaluasi kuantitatif dan kualitatif, serta pendampingan lanjutan. Temuan utama menunjukkan adanya peningkatan pemahaman konsep manajemen waktu dan kemampuan membedakan tugas penting-mendesak pasca-pelatihan. Meskipun demikian, masih ditemukan kesenjangan antara pemahaman dan konsistensi penerapan teknik dalam praktik sehari-hari, diperparah oleh tantangan mood dan beban organisasi. Pemanfaatan teknologi digital dalam manajemen waktu juga belum optimal. Pelatihan ini berkontribusi pada pemahaman bahwa efektivitas manajemen waktu tidak hanya bergantung pada pengetahuan teknis, tetapi juga pada kemampuan internalisasi dan adaptasi. Secara praktis, diperlukan pendampingan berkelanjutan untuk membentuk kebiasaan. Secara teoretis, hasil ini mendukung pembelajaran berbasis pengalaman. Disarankan untuk pengabdian selanjutnya adalah mentoring the mentors dan evaluasi dampak jangka panjang untuk memperkuat keberlanjutan praktik.