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All Journal Jurnal Teknologi Industri Pertanian J@TI (TEKNIK INDUSTRI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Industrial and Systems Engineering Assessment Journal (INASEA) Agrointek JURNAL PASTI (PENELITIAN DAN APLIKASI SISTEM DAN TEKNIK INDUSTRI) Prosiding Semnastek JIEMS (Journal of Industrial Engineering and Management Systems) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Jurnal Pemberdayaan Masyarakat Universitas Al Azhar Indonesia JURNAL TEKNIK INDUSTRI SEMNASTERA (Seminar Nasional Teknologi dan Riset Terapan) Jurnal Taguchi : Jurnal Ilmiah Teknik dan Manajemen Industri Proceeding Mercu Buana Conference on Industrial Engineering Metris: Jurnal Sains dan Teknologi Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) Journal of Scientific Insights Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Exhibition and Seminar on Science and Creative Technology – Al Azhar Proceeding
Budi Aribowo
Universitas Al Azhar Indonesia
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Transportation Other

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IMPLEMENTATION OF SOFT SYSTEM METHODOLOGY DEVELOPMENT OF A DECISION SUPPORT SYSTEM BASED ON THE INTERNET OF THINGS INTHE SUNFLOWER AGRO-INDUSTRY SUPPLY CHAIN Nurhasanah, Nunung; Wajdi, Muhammad Raihan; Mudrikah, Isna Ibnah; Adhipramana, Ivan; Samijayani, Octarina; Adlina, Ginang Natilla; Muthohar, Akhmad; Alfathsyah, Arrasyid; Aribowo, Budi; Haryadi, Dody
Jurnal Teknologi Industri Pertanian Vol. 34 No. 2 (2024): Jurnal Teknologi Industri Pertanian
Publisher : Department of Agroindustrial Technology, Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24961/j.tek.ind.pert.2024.34.2.149

Abstract

Sunflower (Helianthus annuus L.) has the potential for high added economic value to be developed. Indonesia has the opportunity to develop a sunflower agro-industry which is processed into cooking oil. There has not been much research related to the sunflower agro-industry supply chain. A plan for improvements to the supply chain cannot yet be carried out, because the situation in the supply chain has not been comprehensively elaborated. Therefore, this research aimed to analyse the situational supply chain of the sunflower agribusiness. The method used was soft system methodology developed by Checkland. This research has succeeded in designing a conceptual model that produces two human activities, namely: 1) Development of production devices for the drying process of sunflower seeds based on the Internet of Things, (2) Utilization of the Blynk application to support the decisions on the sunflower agro-industry supply chain network, and (3) Development of the prototype digital platform decision support system on the production device based on internet of things. These three activities are also recommendations given as corrective actions to increase the productivity of the sunflower agro-industry. Recommended actions have also been successfully assessed through RE3IS. Future development of this research is to build a digital prototype of an internet of thongs-based decision support system platform that can be easily accessed by sunflower agro-industry managers. The stages in this research are still limited to the recommendation stage for corrective action. The implementation stage can be used as research development in the future. Apart from that, situational analysis is still limited to upstream and intermediate supply chain networks. Therefore, situational analysis of the downstream supply chain network can be carried out in the future. Keywords: cooking oil, internet of things, soft system methodology, sunflower seed, sunflower agro-industry supply chain
Light-Based Positioning System Using Arduino Assidqi, Nurul Imam; Astharini, Dwi; Hamid, Sofian; Hermawan, Denny; Aribowo, Budi
EXSACT-A Vol 1, No 1 (2023)
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/exc.v1i1.2286

Abstract

The Light Positioning System (LPS) represents an innovative technology employed for precise object localization by utilizing light as a positional reference. This method encompasses the utilization of light sources, such as LED lights or other visible light emitters, which can be strategically positioned at various orientations and angles. This research centers on the practical implementation of the LPS paradigm through the application of Arduino. Additionally, the study involves the integration of the Kalman filter algorithm within the Arduino framework to enhance the accuracy of sensor data estimations. The LPS implementation employs distinct sensors, namely the Photoresistor LM393, Photodiode LM393, and TF-Luna Lidar. The programming is accomplished using the Arduino Integrated Development Environment (IDE), while the hardware framework is based on the Arduino Mega 2560 microcontroller. In this research, the ESP32 module plays a pivotal role as it establishes a seamless connection between the sensor data and the Blynk platform. This integration empowers effective and comprehensive data monitoring and analysis, facilitating real-time tracking and evaluation of the LPS system's performance. The photoresistor exhibits better reading accuracy compared to the photodiode, as evident from the obtained RMSE values. The KF PR with 16 LEDs has the smallest RMSE value, which is 0,03. The TF-Luna LiDAR sensor readings are more accurate and effective under well-lit conditions as opposed to low-light conditions. The RMSE value at lux 160 is 1,28 , while the RMSE value at lux 2 is 3,32
FPGA Implementation of Kalman Filter for Visible Light Wahyudi, Imam; Astharini, Dwi; Gandana, Danny M; Hamid, Sofian; Hermawan, Denny; Aribowo, Budi
EXSACT-A Vol 1, No 1 (2023)
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/exc.v1i1.2280

Abstract

Visible Light (VL) has received significant attention due to its benefits in energy efficiency, wide bandwidth availability, and resistance to electromagnetic interference. This final project discusses VL utilizing the Kalman Filter (KF) to predict and estimate the position of related data. The development of the VL method is carried out using Xilinx FPGA Arty A7 hardware, and the KF implementation is carried out in a two-dimensional framework with the Linear KF approach. The main objective of this Final Project is to implement VL using Photodetectors (Photodiode and Photoresistor LM393) on FPGA. The use of Xilinx FPGA Arty A7 hardware and Xilinx SDK software provides the flexibility and reliability required for system implementation. The results indicate that the implementation of Xilinx FPGA Arty A7-35T with KF and the use of 16 LED and 8 LED configurations yield relatively accurate estimations. While the Photodiode LM393 (PD LM393) sensor does not exhibit superior results compared to the Photoresistor LM393 (PR LM393) sensor, this research effectively optimizes light measurements by utilizing the sensor and KF algorithm. The Root Mean Squared Error (RMSE) results show that for the system with 16 LEDs, KF with PR LM393 has an RMSE of approximately ). This RMSE value indicates that KF with PR LM393 can provide relatively more accurate estimations. Similarly, for the system with 8 LEDs, KF with PR LM393 has an RMSE of around ). In this case, KF with PR LM393 again provides relatively more accurate estimations. Meanwhile, the RMSE result for 2D KF in this system is approximately ), indicating that the KF estimation has a relatively small error value compared to the actual measurement value. This demonstrates that KF effectively reduces noise and measurement data fluctuations in the LM393 Photodetector system with 16 LEDs.
Pendekatan Lean Manufacturing Dengan Menggunakan Value Stream Mapping Untuk Mengeliminasi Pemborosan Pada Proses Produksi Celana Jeans Narandana, Rifqi Fauzan; Aribowo, Budi
Proceeding Mercu Buana Conference on Industrial Engineering Vol 2 (2020): ARAH PENGEMBANGAN RISET ENGINEERING DI ERA REVOLUSI INDUSTRI 4.0
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Added value to a product becomes very important for the company or industry so that the product produced can compete with the competition. Providing added value to products can be done by designing more effective and efficient production processes. One way is to minimize and eliminate waste or waste in the production process. If this can be achieved, the company can meet the added value desired by consumers with minimal resources.The main purpose of the paper is to know how value stream mapping (VSM) is a powerful tool in lean implementation and to tackle the improvement areas from the current state & purpose the future state which helps in reducing the lead time, manufacturing cost and delivery in time without compromising for the quality of the product. VSM helps firms to understand and to improve continuously to work towards becoming lean enterprise. CV. X is a jeans convection company, this company has seven work stations found in the production section namely patterning, cutting, sewing, pairs of buttons, pairs of rivets, irons, packing, and shipping. The proposed recommendations for improvement are to carry out continuos flow at the work station of the button pairs up to the work station of packing and to change the delivery schedule of raw materials and to plan appropriate safety stock for CV.X. after the proposed recommendations for improvement, the final step is to draw future state mao and analyze the changes that occur so that the results obtained are reduced process lead time to 4.34, decrease in total inventory to 1345, decrease in total travel time to 25.3 and the last is Travel distance decreased to 3.9.
Prediksi Kadar Gula Pereduksi Berdasarkan Nilai Brix Menggunakan Jaringan Syaraf Tiruan Naufal, Muhammad Bintang; Aribowo, Budi
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 10, No 1 (2026): SEMNAS RISTEK 2026
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v10i1.8901

Abstract

Kadar gula pereduksi merupakan indikator penting dalam penilaian mutu madu sebagaimana tercantum pada Standar Nasional Indonesia (SNI) 8664:2018. Namun, pengujian laboratorium membutuhkan biaya, waktu, dan peralatan khusus sehingga kurang sesuai untuk produsen skala kecil. Penelitian ini bertujuan mengembangkan sistem pakar berbasis web untuk memprediksi kadar gula pereduksi madu menggunakan nilai Brix sebagai input. Model dibangun dengan Jaringan Syaraf Tiruan (JST) tipe Perceptron Lapis Tunggal dan diimplementasikan melalui Streamlit, kemudian dihosting di Hugging Face Spaces agar mudah diakses secara daring. Dataset penelitian terdiri dari 15 data nilai Brix dan 5 data gula pereduksi, yang dilengkapi menjadi 20 pasangan data melalui interpolasi linier. Data dinormalisasi menggunakan metode Min-Max sebelum dilakukan pelatihan dengan validasi silang 5-Fold Cross Validation dan evaluasi menggunakan Mean Squared Error (MSE). Hasil terbaik dicapai pada epoch ke-300 dengan MSE sebesar 0,0676, sedangkan pelatihan hingga 800 epoch menghasilkan MSE akhir 0,1330. Sistem memungkinkan pengguna melakukan pelatihan dan prediksi secara langsung serta menampilkan hasil berupa visualisasi, nilai bobot dan bias, serta validasi terhadap standar SNI. Penelitian ini menunjukkan potensi penggunaan nilai Brix dan JST untuk prediksi mutu madu, meskipun masih terbatas oleh ukuran dataset dan penggunaan interpolasi.
Rekomendasi implementasi keberlanjutan agroindustri serat kenaf pada jaringan rantai pasok hulu Nurhasanah, Nunung; Wibowo, Dhia Puti Andini; Noriko, Nita; Riyana, Tharra Azzahra; Hidayat, Syarif; Aribowo, Budi; Haryadi, Dody
AGROINTEK Vol 18, No 2 (2024)
Publisher : Agroindustrial Technology, University of Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/agrointek.v18i2.17420

Abstract

Environmental issues are a priority in the development of the kenaf fiber industry globally, because kenaf fiber is considered an environmentally friendly vegetable fiber when used as a raw material. This is revealed from the retting process which is the main process in processing the kenaf plant into kenaf dry fiber. The purpose of this study was to determine the green productivity index on the upstream side of the kenaf fiber agro-industry network by mapping green value stream mapping. Based on the research that has been done, it can be concluded that there are 6 alternatives to clean production, 4 of which can add value to the waste and 2 of them are routine activities of the kenaf fiber agroindustry. Then the results of the GVSM Current State mapping on energy of 12,753.6 Joules, water as much as 32,810.1l, material as much as 14,340 kg, waste as much as 14,860 kg, emissions of 1,584 kg, and biodiversity as much as 4,000 kg. After the alternative production is carried out, the results of the GVSM Future State mapping are 11,159.4 Joules of energy, 32,810.1l of water, 14,340 kg of materials, 1,584 kg of emissions, and 4,000 kg of biodiversity. There was a reduction in energy in the form of human power of 1,594.2 Joules which was replaced by the use of machines. The GPI Current State value in the kenaf fiber agroindustry is 0.000759 and the GPI Future State value obtained is 0.001234. This means that the production alternatives given affect the increase in IE value and decrease in EI value from the kenaf fiber agroindustry so that the GPI Future State value produced is getting better so that the impact on the environment in the kenaf fiber agroindustry is decreasing.
Co-Authors Adhipramana, Ivan Adlina, Ginang Natilla Afranissa Firdausiyah Ahmad Juang Pratama Ahmad Raafi Alfathsyah, Arrasyid Alhafizh Ramadhan Alif Fadillah Aliza Sabrina Ramadita Amalia, Nadia Rizky Aprilia Tri Purwandari Aprilia Tri Purwandari Aprilia, Aisyah Sabrina Assidqi, Nurul Imam Ayu Lestari Ningtiyas Belia Perwitasari Maharani Belia Perwitasari Maharani, Belia Perwitasari Bianda Mayfiani Tiartanaya Budi Tjahjono Chirzun, Ahmad Cut Shity Dautama Ryzza Putra Dede Ardi Rajab Denny Hermawan Dhia Puti Andini Wibowo Dicky Sumantri Dody Haryadi Dwi Astharini Fairuz, Salsa Frans Dory Gandana, Danny M Gerry Firmansyah Ghunyatullaami’ah Ghunyatullaami’ah Hafidz, Fahmi Hamid, Sofian Hanny Nurlatifah Hartanto, Nadiya Hasna Fakhirah Haryadi, Dody Hidayat Yorianta Sasaerila Hilda Yuliani Ilmi Ramanda Sitorus Ilsa Nuri Pabo Imam Wahyudi Indrawan, Imam Wahyudi Khoirunisa, Amanda Kian Aryadi Kushandayati Kushandayati Miftah Arifin Moza Aisyah Yasmin Mudrikah, Isna Ibnah Muh Asrul Irawan, Andi Muhammad Farhad Shoulthon Indrawan Muhammad Hafidh Al Fathoni Mujadin, Anwar Muthohar, Akhmad Nabila Ramadhany Barley Nadya Rinaldy Narandana, Rifqi Fauzan Natasari - Naufal, Muhammad Bintang Nita Noriko Noviyanti, Anissa Nunung Nurhasanah Nurhasanah, Nunung Nurhasanah Purwandari, Aprilia Tri Putri Yasmin Martsela Putri, Hani Adinda Raghdawulan Raghdawulan Raharjo, Fabian Trama Rakhmaputri, Septalia Reudinta Zesha Ridho Octavia Pernando Riyana, Tharra Azzahra Rizqi Maulida Amalia Rully Ardi Setyadi Rydhoni, Rydhoni Safira Tri Handayani Samijayani, Octarina Sarah Giovani Sopian Maulana Sukarman Sukarman Suryo Tondo Lukito Syafira Ihsani Syarif Hidayat Syarif Hidayat Syarif Hidayat Tharra Azzahra Riyana Tri Purwandari, Aprilia Tsabitah, Nimah Wajdi, Muhammad Raihan Wibowo, Dhia Puti Andini Widodo, Agung Mulyo Widya Astuti Wiwik Sudarwati Yadi Heryadi Yasmin, Moza Aisyah Yusuf, Andi Mukramin