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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Innovation and Applied Technology Jurnal Agroindustri Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Sistem Cerdas Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Tekper: Jurnal Teknologi dan Manajemen Industri Pertanian Jurnal Pengabdian Masyarakat Asia Community Empowerment International Journal of Artificial Intelligence and Robotics (IJAIR) Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Andalasian International Journal of Agricultural and Natural Sciences Journal of Food Engineering Malcom: Indonesian Journal of Machine Learning and Computer Science National Multidisciplinary Sciences AGRIC
Muhammad Arwani
Universitas Nahdlatul Ulama Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Other

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Risk Mitigation Analysis of the Apple Juice Drink Supply Chain Arwani, Muhammad; Choirun, Annisa'u; Firdausyi, Izzati Ardhan; Bisma, Auditya
Tekper : Jurnal Teknologi dan Manajemen Industri Pertanian Vol 4, No 3 (2023):
Publisher : Jurusan Ilmu dan Teknologi Pangan, Fakultas Pertanian,

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/tekper.v4i3.44863

Abstract

The problem is that apple productivity in Batu City decreases every year, while the demand for apple juice is increasing along with the increase in tourists and destinations in Batu City. The level of dependence and complexity in the supply chain makes the supply chain as a whole more vulnerable to disruption. Therefore, risk mitigation is needed so that it can reduce and overcome various risks that occur in supply chain institutions. This research aims to identify risk factors and formulate appropriate strategies so that they can be implemented by apple cider supply chain actors. Data analysis uses Fuzzy FMEA (Failure Mode and Effect Analysis) to identify problems or causes of failures that occur. The research results show that the highest risk for farmers is the risk of apples being damaged during the planting process due to pests and climate, with an FRPN value of 5.228; Meanwhile, for the middleman, it can be seen that the highest risk is the risk of late delivery to the factory with an FRPN value of 4.986; and the highest risk in the processing industry is the risk that the quality of the fruit juice product does not comply with the FRPN value of 6.047. Alternative risk mitigation strategies for farmers include increasing harvest area, increasing farmer awareness of good planting methods, using organic fertilizer, and scheduling deliveries. Alternative risk mitigation strategies for middlemen include production scheduling, sorting, grading, using safe transportation packaging, and GHP training. On the part of the processing industry, alternative strategies that can be implemented are increasing the availability of raw materials, reducing the occurrence of product defects, repairing and replacing machine components, and consistent implementation of SOPs.
Filter Feature Selection for Detecting Mixture, Total Phenol, and pH of Civet Coffee Widyaningtyas, Shinta; Arwani, Muhammad; Sucipto, Sucipto; Hendrawan, Yusuf
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 6 No. 2 (2024): November 2024
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v6i2.9010

Abstract

Civet coffee, a highly valued specialty coffee, is susceptible to adulteration with regular coffee, resulting in economic losses and consumer fraud. This study investigates the potential of electrical spectroscopy as a non-destructive technique for detecting civet coffee adulteration. We analyzed the bioelectrical properties of civet coffee beans and their mixtures with regular coffee, focusing on impedance parameters (Z, Lp, Ls, Rp, Rs) as potential indicators of adulteration. Two machine learning models, Artificial Neural Network (ANN) and Random Forest, were trained and evaluated using Mean Squared Error (MSE) validation to identify the most informative features for predicting mixture composition, total phenol content, and pH. The findings demonstrate that impedance parameters, particularly Z, consistently exhibited high feature importance scores across different attribute evaluators and search methods. The optimal model, an ANN with a correlation attribute evaluator and ranker search method, achieved an MSE validation of 0.0479, indicating strong predictive accuracy. These results suggest that electrical spectroscopy, coupled with machine learning, offers a promising approach for developing automated, non-invasive methods for detecting civet coffee adulteration, thereby protecting consumers and ensuring the integrity of the specialty coffee market.
Adaptive Nutrient Management for Vegetable Cultivation: A Fuzzy Rule-Based Approach Pohan, Sry Dhina; Arwani, Muhammad
Jurnal Sistem Cerdas Vol. 7 No. 3 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i3.471

Abstract

The availability of foodstuffs, especially vegetables in Indonesia, is highly dependent on seasonal changes, making it necessary to implement precision agriculture to improve the efficiency of vegetable cultivation. The accuracy in fulfilling plant nutrient requirements is a key factor in the effectiveness of vegetable cultivation, hence a nutrient solution irrigation control system is essential. The main challenge in developing such a control system is the variation in the duration of nutrient solution irrigation, which is highly dependent on soil fertility levels and the environmental conditions of the vegetable cultivation area. This research proposes a fuzzy rule-based algorithm to determine irrigation duration based on temperature, air humidity, soil moisture, and light intensity. The fuzzy algorithm is implemented in the nutrient solution irrigation control system through a wireless sensor network (WSN). This research resulted in the design of an application for the nutrient solution irrigation control system in vegetable plant growth, capable of determining irrigation duration accurately and clearly with the implementation of the fuzzy rule-based algorithm, resulting in an irrigation duration of 48 seconds/500ml categorized as long for nutrient solution irrigation. The fuzzy rule-based algorithm was tested using Mean Square Error (MAPE) based on the irrigation duration results, yielding an error percentage of 0.25%, which is considered highly accurate in conducting nutrient solution irrigation for vegetable plants. This automated control system has the potential to increase vegetable crop productivity by minimizing fertilizer and water wastage.
CHARACTERIZATION OF CELLULOSE FIBER ISOLATION FROM KAPOK RANDU (Ceiba pentandra) ON NaOH CONCENTRATION AND DELIGNIFICATION PROCESS TIME Robbani, Syifa; Ichsan, Onne Akbar Nur; Sa'adah, Laila Mu'arifatus; Nanda, Ririn Fatma; Arwani, Muhammad
Agric Vol. 36 No. 2 (2024)
Publisher : Fakultas Pertanian dan Bisnis, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/agric.2024.v36.i2.p267-282

Abstract

Kapok range is a natural fiber that has considerable potential in the form of cellulose and can be enhanced by its physical and mechanical value cellulose. This study aims to analyze the character of cellulose produced from kapok and isolation. The cellulose isolation method used a factorial complete randomized design, namely the first factor of NaOH concentration (4%, 6%, and 8%) and the second factor of extraction time (40, 50, and 60 minutes). The cellulose isolation process showed that the method did not significantly affect the yield of randu kapok cellulose. The highest yield and degree of whiteness resulted from the treatment of 4% NaOH concentration and 40 minutes of extraction time with a yield of 6.54 ± 0.82%. The following result showed that the treatment had a significant effect on the results of the degree of whiteness. The highest degree of whiteness resulted from the treatment of 8% NaOH concentration and 60 minute extraction time of 30 ± 0.7. The cellulose isolation results of kapok resulted in cellulose content of 90.15 ± 0.81%, hemicellulose content of 3.6 ± 0.52%, and lignin content of 0.91 ± 0.03%. The analyzed properties provide a strong basis for considering the potential use of such cellulose nanofibers in various industrial applications, such as the manufacture of sustainable composite materials or other valueadded products.
OPTIMASI EKSTRAKSI MINYAK BSFL (HERMETIA ILLUCENS) DENGAN METODE MICROWAVE ASSISTED EXTRACTION (MAE) SEBAGAI BAHAN BAKU BIODIESEL Rohmanna, Novianti Adi; Deoranto, Panji; Arwani, Muhammad; Majid, Zuliyan Agus Nur Muchlis
Jurnal Agroindustri Vol. 14 No. 1 (2024): May 2024
Publisher : BPFP Faperta UNIB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31186/jagroindustri.14.1.11-25

Abstract

Black soldier fly (BSF) is an insect to reduces organic matter and produces biomass insects with crude fat of 20.09% -28.89%. BSF larvae have a high lipid content compared to other flies as raw material for making biodiesel. This research aimed to determine the optimum condition of BSF’s lipid extraction process using MAE. The method was the response surface method (RSM) central composite design (CCD) with two factors and three response variables. The research factors were extraction temperature (60, 75, and 90 0C) and extraction time (20, 30, and 40 minutes). Identification of the response variables measured were oil yield, free fatty acids (%FFA), and acid number of black soldier fly (BSF) larvae oil with limits according to SNI 7182:2015. The optimal solution resulted from the treatment level with an extraction temperature of 60 0C with an extraction time of 37.69 minutes. The higher temperature treatment significantly increased the oil yield, but on the other hand, it also increased the free fatty acid content and acid number in the larvae oil. The longer extraction time significantly increased the resulting oil yield but could also significantly increase the free fatty acid content and acid number. The predicted results for the optimal solution response to oil yield was 30.22%, free fatty acid was 3.26%, and the acid number was 6.48 mgKOH/g. The results generated from the data validation of each oil yield response was 29.28%, free fatty acid was 3.29% and the acid number was 6.54 mgKOH/g.
Decision Support System by using Multiple Attribute Decision making with Simple Additive Weighting Method (Madm-Saw) Method in Selecting the Best Bromelain Ririn Fatma Nanda; Anwar Kasim; Rini Rini; Daimon Syukri; Muhammad Arwani
Andalasian International Journal of Agriculture and Natural Sciences (AIJANS) Vol. 3 No. 02 (2022)
Publisher : Lembaga Penelitian dan Pengabdian, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/aijans.v3.i02.114-119.2022

Abstract

Bromelain is a protease enzyme obtained from pineapple. In choosing bromelain only pay attention to its chemical analysis and there is no rank yet. Therefore, research has been carried out in making the best bromelain decision using the Multiple Attribute Decision Making with Simple Additive Weighting Method (MADM-SAW) method based on the shelf life of pineapples. The basic concept of this method is to find the weighted sum of the performance branches for each alternative (treatment) of all attributes so that the best alternative will be obtained in the selection of crude bromelain enzymes based on pineapple storage. The results showed that the best pineapple fruit was with storage of day 0 as rank 1, with a total value was 0.9025.
Performance of K-Nearest Neighbors and Advanced Metaheuristic Algorithms for Feature Selection in Classifying the Purity of Civet Coffee Widyaningtyas, Shinta; Arwani, Muhammad; Nanda, Ririn Fatma
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 1 (2026): MALCOM January 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i1.2345

Abstract

Various studies have shown that feature selection can improve classification accuracy, particularly in agriculture. However, most of these studies still use conventional metaheuristic algorithms, which have certain limitations, including a tendency to get stuck in local optima. Therefore, this study explores the potential of advanced metaheuristic algorithms for selecting colour and texture features to classify the purity of civet coffee. This study used k-Nearest Neighbour (K-NN) model optimized with several advanced metaheuristic algorithms, i.e. Bare Bones Particle Swarm Optimisation (BBPSO), Modified Generalised Flower Pollination Algorithm (MGFPA), Enhanced Salp Swarm Algorithm (ESSA), Improved Salp Swarm Algorithm (ISSA), and Two-Stage Modified Grey Wolf Optimizer (TMGWO). The results show that feature selection can improve model accuracy. The best model was obtained from a combination of K-NN and TMGWO with an accuracy of 0.981, precision of 0.982, recall of 0.981, F1-Score of 0.981, and Area Under Curve (AUC) close to 1 with three selected features, i.e. blue correlation, s_hsl_correlation, and s_hsv_correlation. Furthermore, the results of this study indicate that the development of advanced metaheuristic algorithms can overcome the weaknesses of conventional algorithms, as demonstrated by improvements in classification model accuracy and the number of selected features.
Manajemen Risiko Rantai Pasok Proaktif pada Bakery Skala Menengah: Integrasi SCOR–HOR dengan Validasi Inter-Rater Reliability: Proactive Supply Chain Risk Management in a Medium-Scale Bakery: A SCOR–HOR Integration with Inter-Rater Reliability Validation Arwani, Muhammad; Andira, Risma Ayu; Widyaningtyas, Shinta; Robbani, Syifa’
Journal of Food Engineering Vol. 5 No. 2 (2026): April
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jofe.v5i2.7025

Abstract

Penelitian ini bertujuan mengidentifikasi kejadian risiko dan agen risiko pada rantai pasok bakery skala menengah serta menetapkan prioritas strategi mitigasi yang paling efektif dan feasible. Studi kasus tunggal menggunakan kerangka Supply Chain Operations Reference (SCOR) untuk pemetaan proses rantai pasok dan metode House of Risk (HOR) Fase 1 dan Fase 2 untuk identifikasi serta pemrioritasan risiko secara proaktif. Prosedur inter-rater reliability (IRR) diterapkan melalui Cohen's Kappa (κ) dengan dua rater independen menilai severity kejadian risiko dan occurrence agen risiko untuk menjamin objektivitas penilaian. Hasil penelitian menunjukkan 18 kejadian risiko dan 18 agen risiko teridentifikasi pada seluruh proses rantai pasok. Nilai κ rata-rata sebesar 0,871 (Almost Perfect) mengkonfirmasi validitas penilaian. Berdasarkan analisis Pareto, 10 agen risiko prioritas menyumbang 80% dari total Aggregate Risk Potential (ARP), dengan ARP tertinggi pada A13 (kurangnya ketelitian pekerja, ARP = 2.023). HOR Fase 2 menghasilkan 10 strategi mitigasi dengan pembentukan divisi Quality Control sebagai prioritas tertinggi (ETD = 6.069). Penelitian ini menyimpulkan bahwa integrasi SCOR, HOR, dan validasi IRR berbasis Cohen's Kappa menghasilkan kerangka manajemen risiko rantai pasok proaktif yang lebih valid dan operasional bagi UMKM bakery, sekaligus mengisi celah metodologis pada studi HOR sebelumnya.
Co-Authors Abdul Hakim Agus Budiarto Agus Somantri Alan Dwi Wibowo Amelia Amelia Andira, Risma Ayu Anwar Kasim Apriani, Rila Rahma Arief RM Akbar Arya Nugraha Hananto Asma Naili Salsabila Aulia Bayu Yushila Azwar Lahusin Baimy Alexander Bambang Susilo Bisma, Auditya Chatarina Umbul Wahyuni Choirun, Annisa'u Daimon Syukri Danang Yugo Pratomo Dessy Maulidya Maharani Dimas F Al Riza Djatmiko Bagus Wibowo Ellya, Hikma Essa Noer Bhakty Mulia Fahmi Akbar Yuliansyah Firdausyi, Izzati Ardhan Gatot Ciptadi Hartoni Hartoni I Kadek Olin Adi Wiguna Ichsan, Onne Akbar Nur Imam Santoso Iqlima Khoirun Nufus Irwan Bempah KIKI FIBRIANTO Linda Rahmawati Maffudhotul Anna Majid, Zuliyan Agus Nur Muchlis Muhammad Bagaskara Wiratirta Mulyawan, Ronny Nuria Rahmatin Panji Deoranto Pohan, Sry Dhina Puspa Ayu Indah Prameswari Rini Rini Ririn Fatma Nanda Riska Ayu Lestari Rizki Putra Samudra Robbani, Syifa Rohmanna, Novianti Adi Sa'adah, Laila Mu'arifatus Sari, Nukhak Nufita Setyawan, Hendrix Yulis Shinta Widaningtyas Shinta Widyaningtyas Simping Yuliatun Sucipto, Sucipto Sunaryo Sunaryo Supriyanto Supriyanto Wafa Nida Faida Azra Widyaningtyas, Shinta Yudin Yudiawan Maksum Yudit Oktanella, Yudit Yusuf Hendrawan