Monitoring and Controlling System of Shed Tobacco Dryer With Fuzzy Logic Method(Sistem Monitoring dan Controlling Pengering Tembakau Rajangan dengan Metode Fuzzy Logic)Bagus Budi Prayogo1), Fachrudin Hunaini2), Mohammad Muhsin3)1,2,3 Department of Electrical Engineering, Faculty of Engineering, Widyagama University Malang, Indonesia324231012954000Email: sugabidub1994@gmail.com[1], fachrudin_h@widyagama.ac.id[2], 07.muhsin@gmail.com [3]Abstract Technological developments in post-harvest on the tobacco drying system which is a process of evaporation of water using heat energy or hot air flow aims to inhibit the growth of fungi and bacteria. The method of processing tobacco using the hot air flow method in the oven currently uses a temperature setting that is done manually and strict supervision must be carried out so that the results of the tobacco oven are not damaged. An automatic tobacco drying system can be an option so that the drying process can produce quality tobacco. By embedding the Fuzzy Logic Controller (FLC) method in the tobacco drying system, the temperature can be controlled by controlling the PWM output on the SSR which aims to turn the heater on and off. The tobacco drying oven system controls the oven to adjust and maintain the set-point temperature of 30, 40, and 50 with an average error of 0.03, 0.02, and 0.01.Keywords: Tobacco Dryer; Controlling; Fuzzy; Matlab; TobaccoAbstrak Perkembangan teknologi pada pasca panen pada sistem pengeringan Tembakau yang merupakan proses penguapan air menggunakan energi panas atau aliran udara panas bertujuan untuk menghambat pertumbuhan jamur dan bakteri. Cara pengolahan tembakau dengan menggunakan metode aliran udara panas di dalam oven saat ini menggunakan pengaturan suhu yang di lakukan secara manual dan pengawasan yang ketat harus dilakukan agar hasil pengovenan tembakau tidak mengalami kerusakan. Suatu sistem pengeringan tembakau secara otomatis dapat menjadi pilihan agar proses pengeringan dapat menghasilkan tembakau yang berkualitas. Dengan cara menanamkan metode Fuzzy Logic Controller (FLC) pada sistem pengering tembakau suhu dapat di kontrol dengan cara mengendalikan output PWM pada SSR yang bertujuan untuk menyalakan dan mematikan pemanas. Sistem oven pengeringan tembakau melakukan kontrol pada oven untuk menyesuaikan dan mempertahankan suhu sesuai Set-point sebesar 30, 40, dan 50 dengan rata-rata error sebesar 0,03, 0.02, dan 0.01.Kata Kunci: Pengering Tembakau; Controlling; Fuzzy; Matlab; TembakauPENDAHULUANTembakau merupakan salah satu bahan baku yang dapat memberikan manfaat ekonomi dan sosial yang dirasakan oleh berbagai kalangan. Peran tembakau dalam perekonomian Indonesia ditinjau dari tingkatan cukai yang dibayarkan terhadap pemerintah dan banyaknya tenaga kerja yang terlibat baik dalam ekspor tembakau maupun budidaya dan pengolahan tembakau maupun pra-pengolahan Tahap pembuatan tembakau [1]. Karena bentuk fisiknya, tembakau dijual di Indonesia dalam dua bentuk: tembakau cincang. Tembakau ini dijual dalam bentuk cincang dan dicincang terlebih dahulu kemudian dijual. Setelah itu dilakukan proses pengeringan dengan menggunakan sinar matahari (sun). Ada juga tembakau hitam yang dijual dalam bentuk daun utuh (dikeraskan), dan setelah proses pengeringan [2]. Salah satu hal yang dapat dilakukan saat ini untuk perkembangan teknologi pada pasca panen adalah pada system pengeringan.Pengeringan merupakan proses pemindahan air menggunakan panas atau aliran udara untuk menghambat pertumbuhan jamur dan bakteri. Permasalahan yang terjadi saat ini yaitu pengolahan tembakau di pedesaan masih menggunakan metode pengeringan secara tradisional dengan mengandalkan sinar matahari. Proses penggunaan sumber panas matahari untuk mengeringkan tembakau dapat berkembang, tetapi tingkat penerimaan masih terhambat oleh fluktuasi musiman sinar matahari [3]. Penelitian sebelumnya tentang pengeringan tembakau juga telah dilakukan dengan tujuan untuk merancang dan menguji kombinasi panel surya di atap tungku dan oven untuk pengeringan tembakau. Penelitian ini didasarkan pada metode tungku konvensional umum, dan hasil penelitian dievaluasi pada aspek teknis dan ekonomi. Lokasi percobaan diemplasemen P.T. Sadhana Arif Nusa, Lombok Timur, Nusa Tenggara Barat. Penggunaan bahan bakar LPG dan kolektor surya sebagai sumber energi dapat memenuhi target suhu yang diinginkan (30-70°C) pada fase-fase pengovenan. Hasil penelitian menunjukkan bahwa menggunakan proses pengeringan sistem energi panas gabungan antara solar dan penukar panas akan lebih menguntungkan daripada pengeringan matahari saja dan pengeringan penukar panas saja. Letak keunggulannya adalah tidak tergantung pada waktu dan pada biaya yang dibutuhkan relatif murah [4]. Cara pengolahan tembakau dengan mengunakan metode aliran udara panas di dalam oven saat ini masih menggunakan cara konvensional yaitu menggunakan kompor. Pada oven konvensional pengaturan suhu dilakukan secara manual. Pengawasan yang ketat juga harus dilakukan agar hasil pengovenen tembakau tidak mengalami kerusakan. Kelemahan menggunakan cara konvensional yaitu proses pengovenan masih menggunakan bahan bakar minyak tanah, LPG atau kayu bakar. Selain itu, sekarang ada pembatasan minyak tanah bersubsidi dan sulitnya mendapatkan kayu bakar, sehingga beralih ke bahan bakar batu bara. Bahan bakar batu bara dan kayu harus dibakar secara tidak langsung karena udara panas yang dihasilkan selain kotor juga mudah menyala. Selain itu, waktu pemanggangan relatif lama dan memerlukan pengawasan [5].Melihat permasalahan yang ada sekarang bagi petani tembakau, mendesain satu teknologi pengeringan oven tembakau secara otomatis dapat menjadi pilihan. Dengan menggunakan pengering oven otomatis diharapkan dapat membantu dan memudahkan petani dalam proses pengeringan tembakau karena dapat mengatur suhu pengeringan secara otomatis. Kelebihan mengunakan oven otomatis ini yaitu alat pemanas tidak lagi menggunakan kompor, tetapi mengunakan element pemanas (heater) yang dikontrol secara otomatis [6]. Metode kendali logika fuzzy adalah suatu metode pengungkapan makna kebahasaan suatu variabel seperti variabel suhu, dan dinyatakan dalam makna kebahasaan panas, sedang, dan dingin. Metode fuzzy logic controller dipilih karena mempunyai kelebihan dibandingkan metode kontrol lain yang sering digunakan seperti Proportional Integral Derivative (PID) dan Jaringan Syaraf Tiruan (JST). FLC lebih andal daripada pengontrol PID karena mencakup area kerja yang lebih besar daripada pengontrol PID, dan FLC dapat beroperasi bahkan di lingkungan yang bising. Selain itu, FLC membuat aturan lebih mudah dipahami dan diubah. Kontroler logika fuzzy banyak digunakan dalam bidang kontrol peralatan rumah tangga, seperti lemari es, mesin cuci, penyedot debu, pendingin ruangan (AC), dan pengontrol suhu pemanas pemanas oven [7]. Berdasarkan latar belakang tersebut akan dirancang dan dibuat sistem monitoring dan controlling pengering tembakau rajangan dengan metode fuzzy logic. untuk menyelesaikan permasalahan pada petani tembakau agar proses pengeringan tidak bergantung pada cuaca dan dapat di kontrol agar suhu stabil. penyimpanan data menggunakan Micro SD untuk mengetahui data selama proses pengeringan tembakau.TINJAUAN PUSTAKATembakauTembakau merupakan produk tanaman Nicotiana tabacum L. yang daunnya merupakan bagian dari tanaman. Varietas tembakau yang diperoleh dari spesies Nicotiana tabacum L, subgenus Tabacum, genus Nicotiana dan famili Solanaceae yang tersebar luas. Tembakau telah berkembang secara signifikan dengan munculnya berbagai jenis tembakau tergantung pada bentuk, jenis, adaptasi lokal, penggunaan dan waktu budidaya, serta metode pengelolaannya. Misalnya, varietas tembakau dapat diklasifikasikan menurut adaptasi lokasi: tembakau Virginia, tembakau Burley, dan tembakau Turki. Secara umum tembakau di Indonesia dibagi menjadi tembakau Voor-Oogst dan tembakau Na-Oogst menurut musim tanam [8].Fuzzy Logic ControlLogika Fuzzy adalah suatu teknik untuk menyatakan nilai kebahasaan suatu variabel seperti variabel suhu, dan dinyatakan dalam makna kebahasaan dingin, hangat, dan panas. Kontrol Logika Fuzzy menunjukkan seberapa benar dan salah suatu nilai. Kontrol Logika Fuzzy adalah cara yang baik untuk memetakan ruang input ke ruang output. Fuzzy diekspresikan dalam tingkat kepemilikan dan tingkat kebenaran. Jadi sesuatu dapat dikatakan sebagian benar dan sebagian salah [9]. Terdapat empat komponen atau bagian utama yang sangat penting pada struktur dasar pada FLC yang terdiri dari Fuzzyfikasi, Fuzzy Rule Base, Inferensi dan Defuzzifikasi:Fuzzifikasi adalah suatu proses untuk mengubah nilai crisp input menjadi nilai fuzzy input. Proses evaluasi rule mengolah fuzzy input sehingga menghasilkan fuzzy output.Fuzzy Rule base mempunyai fungsi penting dalam pengendalian dengan logika fuzzy karena semua proses: fuzzifikasi, inferensi dan defuzzifikasi bekerja berdasarkan pengetahuan yang ada pada fuzzy rule base.Defuzzifikasi mengubah fuzzy output menjadi nilai crisp output. Sebelum defuzzifikasi, harus dilakukan proses composition, yaitu agregasi hasil clipping dari semua aturan fuzzy sehingga didapatkan satu fuzzy set tunggal [10].MikrokontrollerMikrokontroler adalah rangkaian mikro berupa sirkuit terpadu (IC) yang dapat menerima dan memproses sinyal input dan sinyal output sesuai dengan perintah yang dimuat. Nilai Masukan mikrokontroler didapatkan dari berbagai sensor yang mendapatkan informasi dari lingkungan sekitar, sedangkan keluaran diteruskan ke aktuator yang dapat mempengaruhi lingkungan. Mikrokontroler terdiri dari central processing unit (CPU), memori, modul I/O spesifik, dan blok tambahan seperti analog to digital converters (ADCs) yang sudah terintegrasi. [11].Solid State Relay (SSR)Definisi dan fungsi solid state relay (SSR) hampir identik dengan relay elektromekanis atau kontaktor magnetik (MC), dan merupakan saklar elektronik yang umumnya digunakan atau diterapkan sebagai perangkat kontrol di industri. Namun, relai elektromekanis memiliki keandalan yang terbatas dibandingkan dengan SSR seperti menempati banyak ruang, dan memiliki banyak keterbatasan seperti output titik kontak relay yang tinggi. Karena adanya keterbatasan tersebut, banyak pembuat relay menawarkan suatu perangkat SSR dengan semi konduktor modern yang mengimplementasikan SCR, TRIAC, atau output transistor. Output device tersebut adalah optikal yang di gabungkan dengan LED yang berada dalam relay. Relay akan diaktifkan dengan energi LED ini, biasanya menambahkan tegangan power DC yang rendah. Pemisah optik antara input dan output ini merupakan keunggulan SSR dibandingkan relai elektromekanis [12].Load CellLoad cell merupakan modul pengukur berat yang terdapat pada timbangan digital, sensor lini memiliki komposisi penyusun berupa strain gauge, konduktor, dan jembatan wheatstone. Secara teori sensor load cell berfungsi untuk menghitung massa atau bobot suatu benda. Sebuah load cell mengukur efek dari perubahan tekanan dalam bentuk sinyal listrik, karena menyebabkan perubahan yang efektif dalam hambatan beban kawat. Prinsip pengoperasian timbangan digital menggunakan load-cell ini adalah adanya load cell yang memberikan tegangan keluaran pada saat hambatan berubah akibat perubahan posisi penyangga beban. [13].METODE PENELITIANPerancangan KonsepTahap perencaan konsep meliputi sistem operasi secara keseluruhan, fitur yang direncanakan sekaligus desain dari Sistem Monitoring dan Controlling Pengering Tembakau Rajangan dengan Metode Fuzzy Logic. Berikut adalah desain mekanik Sistem Monitoring dan Controlling Pengering Tembakau Rajangan dengan Metode Fuzzy Logic.[figure 1 about here.] [table 1 about here.] Tahap Pembuatan SistemPada tahap ini, pengembangan perangkat keras dan perangkat lunak dimulai, yang mencakup pembuatan konsep dan fungsi yang telah direncanakan sebelumnya. Arduino UNO sebagai perangkat pengujian Sensor dan perangkat Output lain sedangkan Arduino ATMega 2560 sebagai pusat pengolahan data dari sistem yang dirancang yang di tanamkan Algoritma Fuzzy. Adapun input dalam perancangan alat adalah sensor suhu DS18B20 dan load cell. Sedangkan untuk output adalah SSR yang akan mengendalikan heater sebagai pemanas, LCD sebagai display yang akan menampilkan informasi suhu dan berat, serta Micro SD sebagai media penyimpan data/logger. Berikut merupakan diagram blok pada Sistem Monitoring dan Controlling Pengering Tembakau Rajangan dengan Metode Fuzzy Logic.[figure 2 about here.] [figure 3 about here.] Perancangan Fuzzy Logic ControlDalam sistem control dan monitoring mesin oven tembakau ini diterapkan Fuzzy Logic Controll untuk mengatur suhu pada elemen pemanas oven, dan sensor suhu DS18B20 untuk mengukur besaran suhu di dalam mesin oven yang memberikan masukan kepada Mikrokontroller (Arduino ATMega 2560) yang akan diproses untuk menjadi keluaran PWM yang berfungsi sebagai pengendali panas heater. Sistem Control yang digunakan untuk pengaturan panas heater adalah Fuzzy Logic Control dengan metode Mamdani. Pada design yang di buat terdapat 1 buah input dan 1 buah output dimana input berisi membership function dari Suhu dan dan output berisi Nilai PWM untuk menyalakan heater.[figure 4 about here.] Pada Figure 4 terdiri dari 3 buah MF yaitu Suhu Rendah dengan Keanggotaan (-7 17 23 47), Suhu Sedang dengan Keanggotaan (23 47 53 77), dan Suhu Tinggi dengan Keanggotaan (53 77 80 80).[figure 5 about here.] Pada figure 5 terdiri dari 3 buah MF yaitu ssr1 (PWM rendah) dengan Keanggotaan (0 0 12.75 114.8), ssr2 (PWM Sedang) dengan Keanggotaan (12.75 114.8 140.3 242.3), dan ssr3 (PWM Tinggi) dengan Keanggotaan (140.3 242.3 255255).[figure 6 about here.] Pada figure 6 merupakan proses kerja algoritma Fuzzy dengan Setpoint dari Sensor Suhu yang sudah di tentukan kemudian menghasilkan nilai error yang dievaluasi oleh Fuzzy sehingga menghasilkan nilai PWM untuk kendali heater.[figure 7 about here.]Figure 7 merupakan Rule kendali Fuzzy yang bertugas sebagai pengambil keputusan untuk control PWM heater. Sedangkan pada Gambar 8 merupakan Rule Viewer untuk melihat hasil input dan output pada saat sistem yang di kontrol dengan FLC, seperti pada Gambar 8 dengan Input nilai Suhu sebesar 35 dengan output Heater/PWM sebesar 108 yang menandakan relay menyalakan heater sampai mencapai Set-point.[figure 8 about here.]ANALISAParameter Umum S-Function Builder Sistem yang di buat pada Simulink Matlab terdiri dari 1 buah Blok S-Function Builder 8 buah Blok Display, dan 4 Blok Scope komponene library dari Simulink Matlab. Schematic sistem yang di buat dapat dilihat pada figure 9.[figure 9 about here.]Implementasi Fuzzy Logic Control[figure 10 about here.]Algoritma Fuzzy Logic dibuat menggunakan Fuzzy Tools yang di sediakan Matlab kemudian di rubah kedalam Bahasa C Arduino dalam sebuah Library. Dengan dinilai input dan output seperti pada Gambar 5 dan Gambar 6, penulisannya diletakkan pada tab discreate update pada S-Function.[table 2 about here.]Pada Table 2 nilai output Membership Function berupa PWM pada SSR yang akan mengaktifkan heater sesuai value yang keluar selama proses optimasi berlangsung. Penulisan Rule untuk Fuzzy mengikuti rule yang di buat pada Fuzzy Tools Matlab dengan penulisan code sebagai berikut:[table 3 about here.]Pada Table 3 terdapat 8 buah Rule Fuzzy Logic dimana masing-masing rule berperan sebagai pengambilan keputusan untuk output berupa PWM dengan input nilai suhu. Set point yang di gunakan berupa Nilai suhu sebesar 35°, berdasarkan nilai tersebut besaran nilai PWM yang keluar mempengaruhi kecepatan sistem mencapai nilai set point yang berbanding lurus dengan nilai Error yang dihasilkan dari proses optimasi.Running Sistem dengan tembakau yang akan di keringkanRunning Sistem dengan Tembakau dilakukan untuk menguji sistem dengan FLC dapat melakukan pengeringan dan mempertahankan nilai suhu sesuai Set-point yang ditentukan sebesar 30, 40, dan 50. Hasil Running Sistem di sajikan dalam bentuk Plot sebagai berikut.[figure 11 about here.]Pada figure 11 nilai error berubah secara fluktuatif dikarenakan temperature cenderung berubah sesuai suhu ruangan yang ada dan sistem akan mempertahankan nilai setpoint sebesar 30.[figure 12 about here.]Pada figure 12 penurunan nilai error dan kestabilan sistem dalam menjaga temperature seusai dengan setpoint sebesar 30 dengan rata-rata nilai error terbanyak sebesar 0.03.[figure 13 about here.] [figure 14 about here.] Pada gambar 14 Nilai PWM (V) berubah dikarenakan adanya Tembakau yang akan dikeringkan dan menandakan sistem sedang bekerja.[table 4 about here.] [figure 15 about here.]Pada figure 15 nilai error berubah secara fluktuatif dikarenakan temperature cenderung berubah sesuai suhu ruangan yang ada dan sistem akan mempertahankan nilai setpoint sebesar 40.[figure 16 about here.]Pada figure 16 penurunan nilai error dan kestabilan sistem dalam menjaga temperature seusai dengan setpoint sebesar 40 dengan rata-rata nilai error terbanyak sebesar 0.02. [figure 17 about here.] [figure 18 about here.] Pada figure 18 Nilai PWM (V) berubah dikarenakan adanya Tembakau yang akan dikeringkan dan menandakan sistem sedang bekerja.[table 5 about here.] [figure 19 about here.]Pada figure 19 nilai error berubah secara fluktuatif dikarenakan temperature cenderung berubah sesuai suhu ruangan yang ada dan sistem akan mempertahankan nilai setpoint sebesar 50. [figure 20 about here.]Pada figure 20 penurunan nilai error dan kestabilan sistem dalam menjaga temperature seusai dengan setpoint sebesar 40 dengan rata-rata nilai error terbanyak sebesar 0.01.[figure 21 about here.] [figure 22 about here.] Pada figure 22 Nilai PWM (V) berubah dikarenakan adanya Tembakau yang akan dikeringkan dan menandakan sistem sedang bekerja.[table 6 about here.] Lama waktu proses pengeringanProses pengeringan Tembakau dengan FLC pada Matlab dengan waktu yang di dapatkan berupa time series, maka untuk merubahnya menjadi waktu real time di perlukan mengetahui nilai clock dari Matlab menggunakan code program berupa tic dan toc time unit maka di dapatkan persamaan: time=simulatinttime ×360Pada percobaan Running Sistem dengan setpoint 30 di dapatkan Simulation Time sebesar 500 pada saat sistem berhenti maka:time=500×360time=150060time=25 menitDeployment HardwareDeployment Hardware dilakukan agar pengaturan Sistem dapat dilakukan tanpa adanya computer dan Mikrokontroller Arduino ATMega2560 dapat berjalan secara mandiri hanya dengan menggunakan catu daya AC dengan sistem yang tertanam Algoritma Fuzzy agar Sistem dapat diimplementasikan secara langusng oleh pengguna lain dengan melalui langkah sebagai berikut:Memasastikan tidak terdapat error pada semua komponen blok yang terhubung pada Gambar 9.Merubah extention file pada wrapper (*.c) menjadi (*.cpp) dan tambahkan code extern “C” pada bagian Void.Setelah proses berlangsung dan tidak terdapat error maka pilih menu deploy to hardware untuk Upload Program kedalam Mikrokontroller[figure 23 about here.].KESIMPULANSetelah melalui beberapa tahap pengujian keseluruhan sistem pengering tembakau menggunakan FLC dan monitoring data, maka kesimpulan yang dihasilkan adalah sebagai berikut:Sistem pengering dirancang dengan Arduino ATMega dengan sensor berat, serta sensor suhu sebagai input, 1 buah LCD sebagai output dan SD Card modul sebagai penyimpan data.Perancangan sistem oven pengering menggunakan Matlab yang di deployment ke dalam Arduino ATMega dengan input sensor suhu dan output berupa Heater yang dikontrol oleh SSR.Sistem oven pengering tembakau dengan Set-point yang ditentukan sebesar 30 mendapatkan rata-rata nilai error suhu sebesar 0,03, Set-point sebesar 40 mendapatkan rata-rata nilai error suhu sebesar 0.02, sedangkan Set-point sebesar 50 mendapatkan rata-rata nilai error suhu sebesar 0.01.Sistem oven pengering tembakau dapat melakukan controlling untuk menyesuaikan dan mempertahankan suhu sesuai Set-point.REFERENCER. 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Accessed: Dec. 08, 2021.DAFTAR TABLETabel 1 Keterangan Gambar28Tabel 2 Penulisan Code Program Fuzzy Input Output Pada S-Function28Tabel 3 Penulisan Rule Fuzzy Pada S-Function28Tabel 4 Hasil Running dengan Set-Point 3029Tabel 5 Hasil Running dengan Set-Point 4029Tabel 6 Hasil Running dengan Set-Point 5030 Tabel 1 Keterangan GambarTabel 1. Keterangan Gambar1.Timbangan4.Box Control2.Sensor suhu DS18B205.Exhaust Fan3.Heater6LCD DisplayTabel 2 Penulisan Code Program Fuzzy Input Output Pada S-FunctionCode Fuzzy Logic pada tab Discreate UpdateKeteranganPenulisan Input Suhu dengan Membership Function Rendah, Sedang, Tinggi.PenulisanOutputSsrdengan Membership Function Ssr1, Ssr2, Ssr3.Tabel 3 Penulisan Rule Fuzzy Pada S-FunctionTab Discreate Update S-FunctionRule47175443123Tabel 4 Hasil Running dengan Set-Point 30Tabel 4 Hasil Running dengan Set-point 30ErrorBeratPWMPWM (V)00000.08270841.6560.08060841.6620.07860851.6680.0746124851.6790.0726145851.6850.0685145861.6960.0625145871.7130.0565146881.7290.0484146891.7510.0383145901.7770.0302145911.7980.0181145931.8290.0060145941.8580.0060145961.8870.0161145971.9100.0302145991.9420.04441461001.9730.05651451011.9980.06451451022.015Tabel 5 Hasil Running dengan Set-Point 40Tabel 5 Hasil Running dengan Set-point 40ErrorBeratPWMPWM (V)00000.24220921,81840.24220921,81840.242241921,81840.242253921,81840.2422129921,81840.2391147931,82850.2359147931,83840.2313147941,85320.2266147951,86770.2188147961,89150.2109147971,91480.2000147991,94640.19221471001,96840.17971471022,00240.16721471032,0350.15631471052,06250.14221471062,09630.12811471082,12840.11411471102,1588 Tabel 6 Hasil Running dengan Set-Point 50Tabel 6 Hasil Running dengan Set-point 50ErrorBeratPWMPWM (V)00000.39380921,81840.39380921,81840.39380921,81840.3925149921,82350.3925146921,82350.3900146931,83350.3875146941,84340.3837146941,85810.3787146951,87730.3725146961,90090.3663146981,92390.3600146991,94640.35251461001,97270.34381461022,00240.33501461032,0310.32501461052,06250.31501461062,09260.30381461082,12490.29251461092,1555DAFTAR GAMBARFigure 1. Perancangan Alat32Figure 2. Flow Chart Arduino ATMega 2560 Pada Sistem Mesin Oven Tembakau32Figure 3. Diagram Blok Keseluruhan Sistem Monitoring Dan Controlling Pengering Tembakau32Figure 4. Membership Function Input Suhu33Figure 5. Membership Function Output Heater33Figure 6. Proses Kerja Algoritma Fuzzy33Figure 7. Rule Fuzzy34Figure 8. Rule Viewer dengan Input (35) dan Output (108)34Figure 9. Schematic Keseluruhan Sistem Pada Simulink Matlab35Figure 10. Blok Digram Keseluruhan Sistem35Figure 11. Output Nilai Error dan Temperatur selama Running dengan Setpoint sebesar 3035Figure 12. Rata-rata Penurunan nilai Error36Figure 13. Output Nilai PWM dan Berat selama Running dengan setpoint 3036Figure 14. Output Nilai PWM dalam Volt dengan setpoint 3036Figure 15. Output Nilai Error dan Temperatur selama Runing dengan Setpoint sebesar 4037Figure 16. Rata-rata Penurunan nilai Error37Figure 17. Output Nilai PWM dan Berat selama Runing dengan setpoint 4037Figure 18. Output Nilai PWM dalam Volt dengan setpoint 4038Figure 19. Output Nilai Error dan Temperatur selama Runing dengan Setpoint sebesar 5038Figure 20. Rata-rata Penurunan nilai Error38Figure 21. Output Nilai PWM dan Berat selama Runing dengan setpoint 5039Figure 22. Output Nilai PWM dalam Volt dengan setpoint 50 dengan Tembkau39Figure 23. Menu Deployment Hardware Pada Simulink 39Figure 1. Perancangan Alat3350895245745Figure 2. Flow Chart Arduino ATMega 2560 Pada Sistem Mesin Oven TembakauFigure 3. Diagram Blok Keseluruhan Sistem Monitoring Dan Controlling Pengering Tembakau197993094615Figure 4. Membership Function Input Suhu1980565184785Figure 5. Membership Function Output Heater225044064135Figure 6. Proses Kerja Algoritma Fuzzy1896110106680Figure 7. Rule Fuzzy185737516510Figure 8. Rule Viewer dengan Input (35) dan Output (108)Figure 9. Schematic Keseluruhan Sistem Pada Simulink Matlab22225004610102076450497205 Figure 10. Blok Digram Keseluruhan SistemFigure 11. Output Nilai Error dan Temperatur selama Running dengan Setpoint sebesar 30Figure 12. Rata-rata Penurunan nilai Error211137576835.Figure 13. Output Nilai PWM dan Berat selama Running dengan setpoint 30202057045085Figure 14. Output Nilai PWM dalam Volt dengan setpoint 301994789231980Figure 15. Output Nilai Error dan Temperatur selama Runing dengan Setpoint sebesar 402029460402590Figure 16. Rata-rata Penurunan nilai ErrorFigure 17. Output Nilai PWM dan Berat selama Runing dengan setpoint 4021399505080Figure 18. Output Nilai PWM dalam Volt dengan setpoint 40Figure 19. Output Nilai Error dan Temperatur selama Runing dengan Setpoint sebesar 502018029335733Figure 20. Rata-rata Penurunan nilai Error199834529845Figure 21. Output Nilai PWM dan Berat selama Runing dengan setpoint 50Figure 22. Output Nilai PWM dalam Volt dengan setpoint 50 dengan Tembkau2639060473075Figure 23. Menu Deployment Hardware Pada Simulink -2576636413500Journal of Electrical and Electronic Engineering-UMSIDAISSN 2460-9250 (print), ISSN 2540-8658 (online)Vol. 6, No. 1, April 202210.21070/jeeeu.v6i1.1631 PAGE \* MERGEFORMAT 2iVBORw0KGgoAAAANSUhEUgAAAOIAAAApCAYAAAAoP/WgAAAABmJLR0QA/wD/AP+gvaeTAAAACXBI WXMAAA7EAAAOxAGVKw4bAAAgAElEQVR4nMV9d3hU1db+e8703mcyKUMS0iskdENVRAUEpYkNxcK1 3eun14qXYq9Yrh+KiuIn2EAFQRCkSUAQCCUEEtIzybRM733O7w8454cKJIL3+9bz5Hl09Oyz99ll rfWud61NUBSFy5Grr75adM8998yrra2VuN1uSXl5eaq3t5cMh8NIpVIAAJ1OB7fbjUgkAqFQyPwe iUTgdDqRnZ2NZDKJ7u5uXHvttTY2m/3zLbfc0rB8+fJ0l8t1/cGDB9NVKhXUajXa2towYMAAJBIJ 2O12aDQaxGIxtLW1Qa/XgyRJ8Pl8WCwWqFQqsNlshEIhRKNRsNlsAEAsFgMA5r/p9XrU19dj2LBh OHnyJJRKJSwWC/Ly8jBhwoTGu+66a815hk788ssvQ957771pzc3NkMlkIEkSPp8PQqEQUqkUx48f R2lpKQKBAOx2O8RiMQwGA6LRKBwOB/h8PrhcLkKhEILBIACAx+OBz+cjlUohlUphwIAB2LlzJ4qL i6HRaNDV1QU2mw2SJMFms1FWVtY7ceLEVddee63v9x08cOCA7s0337zV6XQqdDodzGYzz+fzRUUi EQQCAZcgiJhEIuE5HI64WCwmk8kkKxqNsjIyMuByuZBKpRAMBsHlcsHj8UCSJNMviqJYACiVSiXo 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