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All Journal TEKNIK INFORMATIKA JURNAL AKUNTANSI DAN AUDITING Jurnal Simetris PROSIDING SENATEK FAKULTAS TEKNIK UMP JOIV : International Journal on Informatics Visualization INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JMM (Jurnal Masyarakat Mandiri) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System bit-Tech Journal of Computer Networks, Architecture and High Performance Computing GANESHA: Jurnal Pengabdian Masyarakat MOVE: Journal of Community Service and Engagement Brilliance: Research of Artificial Intelligence SinarFe7 Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Indonesian Journal of Islamic Law (IJIL)
Angga Prasetyo
Universitas Diponegoro
Religion Agriculture, Biological Sciences & Forestry Humanities 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 Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Social Sciences Transportation Other

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Prediksi Harga Bawang Merah dengan Regresi Linear Berbasis Website di Ponorogo farisi, salman al; Buntoro, Ghulam Asrofi; Prasetyo, Angga
JATISI Vol 12 No 3 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i3.13234

Abstract

Predicting the price of shallots in Ponorogo Regency is crucial due to significant price fluctuations that impact farmers, traders, and consumers. This study aims to implement the Simple Linear Regression method to forecast shallot prices through a web-based system, assisting stakeholders in decision-making. Price data was obtained from the Basic Commodity Availability and Price Development Information System (SISKAPERBABO) for the period June 2024–May 2025. The analysis resulted in the regression equation Y = 20,466 + 1,393X, where Y represents the predicted price and X is the time variable. Accuracy evaluation using the Mean Absolute Percentage Error (MAPE) yielded a value of 21.7%, indicating a reasonably accurate prediction. User Acceptance Testing (UAT) scored 88.2%, demonstrating strong user approval. The website was developed using PHP, Laravel, and MySQL, featuring monthly price predictions and data visualization. This research is expected to serve as an effective price prediction tool for shallot farmers and traders in Ponorogo. Future improvements may include enhancing prediction models with machine learning algorithms and expanding to mobile platforms for broader accessibility.
Bussiness Management System Of Catfish Cultivation Using Fuzzy Inference System Tsukamoto Methods Sugianti, Sugianti; Prasetyo, Angga; Triananda, Agnes
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3619

Abstract

Catfish is a type of freshwater fish that is in great demand among people because it has high nutritional value. The high demand for catfish on the market is a promising business opportunity. The relatively fast maintenance period makes this cultivation much in demand. Management of a catfish farming business requires good strategy and planning so that the business process can provide optimal profits. Appropriate management practices, good planning can predict crop yields with minimal error rates. Based on past data from catfish farming businesses, catfish pond production results are influenced by several factors including pond area, number of seeds, and amount of feed. The catfish cultivation management system produces predictions of catfish harvest but ignores weather conditions, natural disasters and infectious diseases. The method used in crop yield prediction management is the Tsukamoto Fuzzy inference system. The Tsukamoto method applies monotonous reasoning and rules are built using expert knowledge, enabling the system to be able to conclude and manage predictions of catfish harvest based on data regarding pond size, number of seeds and amount of feed. System testing using 10 data shows prediction results obtained through manual calculations and system calculations, resulting in identical results. Further testing uses the white box method to ensure that the data implemented in the Tsukamoto fuzzy management system accurately produces logical decisions. Hence, it can be concluded that the management system using the Tsukamoto method is able to show effective performance in predicting harvest results based on data on pond area, number of seeds and amount of feed consumption. This management system is expected to be able to provide recommendations for catfish cultivation business planning for the community.
Yolo-Drone: Detection Paddy Crop Infected Using Object Detection Algorithm Yolo and Drone Image Masykur, Fauzan; Prasetyo, Angga; Zulkarnain, Ismail Abdurrozaq; Kumalasari, Ellisia; Utomo, Pradityo
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3472

Abstract

Crop failure is an undesirable result of rice planting for every farmer because it disrupts the economic stability of the family. One of the factors of crop failure in the rice planting process is the disease attack factor, which causes infection. Infected plants will interfere with the growth of rice, not optimally, because the green leaf substance, which is key to processing sunlight's nutrients, is unable to function. After all, it is covered by infection. Infection in the leaves covers the green leaf substance, or chlorophyll, so that the leaves are unable to absorb nutrients from sunlight. This problem is a separate concern in overcoming rice plant infections, which will result in crop failure. This paper discusses the detection of infected rice plants, particularly leaf infections, using drone camera images. Unmanned aircraft, also known as drones, fly above rice fields to capture images of rice plants, which are then used as datasets in training models to detect infected and healthy rice plants. The detection of disease presence in rice leaves is carried out using the You Only Look Once version 8 (YOLOv8) object detection algorithm, with a model trained using Google Colab Pro+. The results of training the model to detect healthy and infected plant leaves are the primary objectives of this study. The YOLOv8 object detection model, when applied to detect rice plants with two classes (healthy and infected), shows quite good results. This is indicated by the recall, precision, and F1-score values (0.99, 0.814, 0.90) approaching 1 in all classes.
Implementation of Fuzzy Logic for Chili Irrigation Integrated with Internet of Things Prasetyo, Angga; Yusuf, Arief Rahman; Litanianda, Yovi; Sugianti; Masykur, Fauzan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2518

Abstract

Chili, mustard greens, and tomatoes have always been farmers' favored crops, despite their high water and labor demands. Adapt to these conditions by utilizing smart agriculture systems (SAS) agricultural techniques that involve technology such as automatic irrigation that regulates watering based solely on routine, regardless of land conditions. This type of control during the transitional season can lead to root rot and fungisarium disease on chile plants. In the form of an embedded system with internet of things (IoT) monitoring, a system incorporating artificial intelligence such as fuzzy logic is proposed as a solution. Fuzzy logic will regulate irrigation based on the land's humidity and temperature using computational mathematics. Beginning with the fuzzyification stage to map the sensor's temperature and humidity input values, fuzzy logic is applied. The creation of an inference engine in the NodeMcu 8266 microcontroller to interpret fuzzy rule statements in the form of aggregation of minimum conditions with the AND operator, followed by the combination of a single set value of 0 and 1 in the fuzzy system to produce an appropriate actuator response After the entire system has been prototyped, testing is conducted to determine the responsiveness of the fuzzy program code to changes in the simulated agricultural cultivation land ecosystem. This study found that the fuzzy logic program code embedded in the nodeMCU8266 microcontroller effectively controls the spraying duration of the pump in response to various simulated environmental conditions within 3.6 seconds.
The Perancangan Sistem Penjadwalan Pengambilan Obat Pasien TBC Menggunakan Algoritma FIFO (FIRST IN FIRST OUT) karsih, Rista; Prasetyo, Angga; Karaman, Jamilah
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Abstract

Tuberkulosis (TB) merupakan masalah kesehatan global yang masih terus berlanjut, khususnya di Indonesia yang menempati peringkat kedua beban TB secara global. Keberhasilan pengobatan sangat bergantung pada kepatuhan pasien terhadap jadwal minum obat jangka panjang, namun sistem pemantauan manual dan keterbatasan tenaga kesehatan sering kali menghambat efektivitas pengawasan. Penelitian ini sebuah sistem penjadwalan dan pengingat berbasis web yang dikembangkan menggunakan metodologi Design Science Research. Sistem ini menerapkan algoritma FIFO (First In, First Out) untuk mengatur pengiriman pengingat otomatis melalui WhatsApp berdasarkan data pasien. Fitur konfirmasi memungkinkan pasien memberikan respon, sehingga tenaga kesehatan dapat memantau kepatuhan secara real time. Sistem ini diimplementasikan di Puskesmas Sumberagung dan menunjukkan peningkatan signifikan dalam pengorganisasian jadwal pengobatan, membantu memantau kedisiplinan pengobatan di Puskesmas Sumberagung. Dari hasil penggunaan perancangan sistem pada penelitian ini menunjukkan bahwa kedisiplinan mencapai 95,83% adapun sisanya tidak disiplin karena kendala teknis tidak memiliki teknologi yang mendukung, tidak diarahkan keluarga, menunjukkan bahwa sistem berjalan efektif. Hal ini menunjukkan bahwa sistem dapat meningkatkan kedisiplinan pengambilan obat pasien TBC di Puskesmas Sumberagung.
Penerapan Algoritma Naive Bayes Pada Pemilihan Jenis Pelatihan Kerja (Studi Kasus: Upt Blk Ponorogo): Naive Bayes, Pelatihan Kerja, Sistem Rekomendasi, UPT BLK, Ketenagakerjaan Arya Giri Pangestu; Fajaryanto C, Adi; Prasetyo, Angga
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Abstract

Ketenagakerjaan merupakan elemen penting dalam pembangunan suatu wilayah. Tingkat produktivitas dan daya serap tenaga kerja menjadi indikator kesejahteraan penduduk dan kemajuan suatu daerah. Pemerintah Kabupaten Ponorogo melalui UPT Balai Latihan Kerja (BLK) menyelenggarakan pelatihan berbasis kompetensi untuk meningkatkan kualitas tenaga kerja dan mengurangi angka pengangguran. Namun, proses pemilihan jenis pelatihan kerja sering kali belum berbasis data dan cenderung subjektif. Penelitian ini bertujuan untuk merancang sistem rekomendasi pelatihan kerja berbasis web dengan menerapkan teknik data mining menggunakan Algoritma Naive Bayes. Data yang digunakan diperoleh dari 1300 peserta pelatihan tahun 2021 dan 2022 di UPT BLK Ponorogo. Atribut yang digunakan mencakup jenis kelamin, pendidikan, jurusan, dan status pekerjaan. Sistem ini dibangun menggunakan framework Laravel dengan database MySQL. Hasil pengujian menunjukkan bahwa sistem mampu merekomendasikan jenis pelatihan secara tepat, seperti pelatihan Bahasa Jepang, Otomotif Roda Dua, dan lain-lain, sesuai dengan karakteristik peserta. Dengan demikian, sistem ini dapat dijadikan alat bantu pengambilan keputusan dalam menentukan jenis pelatihan kerja yang lebih efektif dan tepat sasaran.
Rancang Bangun Sistem Penjadwalan Imunisasi Anak Menggunakan Algoritma Greedy Pada Polindes Desa Gabel Dian Anisa Agustina; Prasetyo, Angga; Karaman, Jamilah
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Abstract

Pelayanan imunisasi anak yang tepat waktu sangat penting untuk mencegah penyakit berbahaya. Di Polindes Desa Gabel, imunisasi masih dilakukan serentak satu kali setiap bulan sehingga menimbulkan penumpukan peserta. Penelitian ini merancang sistem informasi penjadwalan imunisasi berbasis web dengan metode Waterfall dan algoritma Greedy, yang diterapkan sebagai teknik optimasi heuristik dalam Kecerdasan Buatan (Artificial Intelligence/AI). Algoritma Greedy digunakan untuk memprioritaskan jadwal imunisasi secara otomatis berdasarkan usia ideal tiap jenis imunisasi dan usia anak, sehingga pembagian waktu lebih adil dan efisien. Hasil penelitian menunjukkan bahwa algoritma ini mampu mengoptimalkan jadwal dengan interval 5 menit mulai pukul 08.00 WIB, menempatkan imunisasi yang lebih mendesak pada waktu lebih awal. Pendekatan ini meningkatkan keteraturan pelayanan imunisasi di Polindes Desa Gabel. Selain itu, sistem mengintegrasikan penjadwalan berbasis AI dengan notifikasi otomatis melalui WhatsApp, sehingga informasi jadwal tersampaikan secara efektif. Ke depan, sistem dapat dikembangkan dengan machine learning untuk menganalisis pola keterlambatan dan menghasilkan rekomendasi jadwal yang lebih adaptif.
Introduction of Generative AI to Improve Digital Literacy of Sanggar Bimbingan AMI Penang Malaysia Children Yusuf, Arief Rahman; Asmaroini, Ambiro Puji; Prasetyo, Angga; Wijaya, Etistika Yuni; Suhendar, Uki; Ramadhani, Desi Dwi; Sugiantoro, Erfan; Juppenny, Ryan
MOVE: Journal of Community Service and Engagement Vol. 5 No. 2 (2025): November 2025
Publisher : EQUATOR SINAR AKADEMIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54408/move.v5i2.538

Abstract

Indonesian migrant workers' children (PMI) in Malaysia often face structural challenges in accessing formal education, thus relying on non-formal education services such as Sanggar Bimbingan (SB). SB AMI Penang, like most other SBs, operates with limited resources, which contributes to the digital literacy gap. However, digital literacy is a crucial competency for social and economic participation in the era of the Industrial Revolution 4.0. This international community service program aims to design and implement a Generative Artificial Intelligence (GenAI) introduction program as a pedagogical tool to improve the digital literacy competencies of children at SB AMI Penang. The community service methods include workshops and practical training. The results of structured and ethically oriented GenAI introduction activities proved effective in improving digital literacy in marginalized communities. The conclusion of this community service is that GenAI has the potential to be an equalizing tool to bridge the digital divide faced by Indonesian diaspora children.
Fuzzy Method Design for IoT-Based Mushroom Greenhouse Controlling Prasetyo, Angga; Setyawan, Moh. Bhanu; Litanianda, Yovi; Sugianti, Sugianti; Masykur, Fauzan
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 6 No 1 (2022): February 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (490.632 KB) | DOI: 10.29407/intensif.v6i1.16786

Abstract

The ideal conditions for the oyster mushrooms growth are at a humidity of 65-75% and 29-31C during incubation, while the growth of stems should be at a humidity of 70-90% 29-32C. This ideal ecosystem is maintained by aeration and manual watering. Still, the results are not optimal in preventing damage to the mycelium during the incubation period, resulting in a decrease in crop yields. Automatic control has not created ideal conditions because air temperature and humidity regulation are only based on fans and sprayers that do not directly affect air conditions. Therefore, we need a method to manipulate the mushroom greenhouse space ecosystem, namely fuzzy logic, the application of fuzzy logic integrated with sensors, actuators, and microcontrollers with the Internet of Things to solve this problem. The results of the installation of fuzzy logic in the mushroom's greenhouse in this system can be seen from the fan's modulation response and the pump's duration. The test results of this control feature can manipulate temperature and humidity. Therefore, the oyster mushroom greenhouse produces an ideal state of 29.8C, the humidity of 68.97% RH, and the production has been proven to be optimal with an average daily harvest of 3.8kg.
Pengendalian Suhu dan Kelembapan Kumbung Jamur Dengan Metode Fuzzy Terintegrasi Internet of Things Prasetyo, Angga; Litanianda, Yovi; Setyawan, Moh. Bhanu; Masykur, Fauzan; Sugianti, Sugianti; Sumaji, Sumaji
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 5 No. 1 (2021): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v5i1.841

Abstract

Jamur tiram atau dalam bahasa latin volvariella volvacea budidaya jamur tiram ini, membutuhkan akurasi dan toleransi kepresisian dalam mengendalikan suhu serta kelembapan yang menyerupai ekosistem habitat jamur tiram sebenarnya, fase inkubasi yang membutuhkan suhu udara 23-28C dengan kelembapan 60- 70%, Fase pembentukan Tubuh dan buah membutuhkan suhu udara 28-32C dengan kelembapan 70-90%. Pengelolaan suhu udara dan kelembapan oleh pembudidaya jamur tiram dilakukan dengan cara penyemprotan serta aerasi kumbung yang masih manual, sehingga pada tahapan fase inkubasi dan fase pembentukan tubuh jamur, belum optimal. Akibatnya hasil panen jamur menurun karena banyak miselium yang rusak saat fase inkubasi. perancangan system akan dilakukan dalam dua tahapan, fase pertama pembuatan wiring perangkat keras, kemudian fase kedua pengintegrasian logika fuzzy di perangkat lunak yang secara keseluruhan akan berupa internet of things (IoT) guna memudahkan dalam proses monitoring. Kinerja logika fuzzy pada sistem ini dilihat dari respon PWM kipas, durasi pompa dan kualitas jaringan pada koneksi internetnya. Hasil pengujian menunjukkan nilai PWM kipas berhasil merespon berbagai kondisi suhu. Durasi penyalan pompa juga bisa merespon perubahan kelembaban ruangan jamur. Sedangkan kualitas jaringan dari hasil percobaan diperoleh nilai konektifitas berupa nilai jitter buffering data 0,72 ms, nilai ping jaringan saat kondisi transmitter(Tx) dan received (Rx) 0,29 ms, dan delay sebesar 0,97 ms atau secara keseluruhan rata-ratanya kurang dari 1ms merupakan kondisi yang termasuk baik untuk penyelenggaraan sistem IoT.
Co-Authors Abdurrozaq Zulkarnain, Ismail Abdurrozzaq, Ismail April Riyanto, David Arya Giri Pangestu Asmaroini, Ambiro Puji Astuti, Arin Yuli Cobantoro, Adi Fajaryanto Dian Anisa Agustina DWI RAHMAWATI Ellisia Kumalasari Fajaryanto C, Adi Fajaryanto Cobantoro, Adi Fauzan Masykur Ghulam Asrofi Buntoro Juppenny, Ryan Karaman, Jamilah karsih, Rista Marsono Marsono Masykur , Fauzan Mohammad Bhanu Setyawan Nunung Rohmatun, Nunung Pradityo Utomo Purnamasari, Sari Rahman Yusuf, Arief Ramadhani, Desi Dwi Rizal Bachtiar Purnama, Rizal Bachtiar Salman Al Farisi, Salman Al Setyawan, Moh. Bhanu Sugianti Sugianti, Sugianti Sugiantoro, Erfan suhendar, uki Sumaji Triananda, Agnes Wijaya, Etistika Yuni Yovi Litanianda, Yovi Yuli Astuti , Arin Yusuf, Arief Rahman Zulkarnain, Ismail Abdurrozaq