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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 Entrepreneur : Jurnal Bisnis Manajemen dan Kewirausahaan Jurnal Ilmiah Wahana Pendidikan Andalasian International Journal of Agricultural and Natural Sciences National Multidisciplinary Sciences AGRIC MANGGALI AL-MANSYUR
Muhammad Arwani
Universitas Nahdlatul Ulama Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering 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 Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Other

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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

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Fuzzy sequential model for strategic planning of small and medium scale industries Imam Santoso; Puspa Ayu Indah Prameswari; Aulia Bayu Yushila; Muhammad Arwani
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 3: June 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i3.12239

Abstract

The use of strategic planning can be an alternative solution to improve industrial performance. In small and medium scale industries especially in apple chips industries, strategic planning helps to know the current industry situation and the steps that must be taken to overcome the existing problems. This study aimed to develop an improvement strategies using Fuzzy Sequential Modeling (FSM) model. FSM model was consisted a SWOT analysis, Root Cause Analysis (RCA), Bolden’s Taxonomy and fuzzy AHP. Based on SWOT analysis, the external factors of threats was the similar business competition and low purchasing power. RCA described the issues that needed to be fixed using Bolden’s Taxonomy as the reference for determining the action plans and produce four OIA (Open Improvement Area) there are old technology machines and equipment, difficulty of enterprise development, ineffective marketing media and low market share. The strategic planning was determined using Fuzzy AHP based on OIA and ABC enterprise needs to improve the low market share and ineffective marketing strategy.
A rapid classification of wheat flour protein content using artificial neural network model based on bioelectrical properties Sucipto Sucipto; Maffudhotul Anna; Muhammad Arwani; Yusuf Hendrawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.9450

Abstract

A conventional technique of protein analysis is laborious and costly. One rapid method used to estimate protein content is near infrared spectroscopy (NIRS), but the cost is relatively expensive. Therefore, it is necessary to find a cheaper alternative measurement such as measuring the bioelectrical properties. This preliminary study is a new rapid method for classified modeling of wheat flour protein content based on the bioelectrical properties. A backpropagation artificial neural network (ANN) was developed to classify the protein content of wheat flour. ANN input were bioelectrical properties, namely capacitance, and resistance and output was a type of the flour, namely hard, medium and soft flour. The result showed that the ANN model could classify the various type of flour. The best ANN model produces a mean square error (MSE) and regression correlation (R) of 0.0399 and 0.9774 respectively. This ANN model could classify the protein content of wheat flour based on the bioelectrical properties and have the potential to be used as a basic instrument to estimate the protein content.
Co-Authors Abdul Hakim Agus Budiarto Agus Somantri Alan Dwi Wibowo Amelia Amelia 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 Fadilah, Fitri Ayu Nur 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 Khofsah, Sholihatin KIKI FIBRIANTO Layyinah, Layyinah Lili Karmela Fitriani Linda Rahmawati Maffudhotul Anna Majid, Zuliyan Agus Nur Muchlis Muhammad Bagaskara Wiratirta Mulyawan, Ronny Namira, Fadia Nuria Rahmatin Panji Deoranto Pohan, Sry Dhina Puspa Ayu Indah Prameswari Rahmantya, Yanneri Elfa Kiswara Rini Rini Ririn Fatma Nanda Riska Ayu Lestari Rizki Putra Samudra Robbani, Syifa Rohmanna, Novianti Adi Sa'adah, Laila Mu'arifatus Salzabila, Aulya Sari, Nukhak Nufita Setyawan, Hendrix Yulis Shinta Widaningtyas Shinta Widyaningtyas Simping Yuliatun Sucipto, Sucipto Sunaryo Sunaryo Supriyanto Supriyanto Suwati, Suwati Via Yustitia Wafa Nida Faida Azra Widyaningtyas, Shinta Yudin Yudiawan Maksum Yudit Oktanella, Yudit Yusuf Hendrawan