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All Journal Jurnal Ilmiah Informatika Komputer Teknika Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Jurnal CoreIT JURNAL KAJIAN TEKNIK ELEKTRO JTAM (Jurnal Teori dan Aplikasi Matematika) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi INTECOMS: Journal of Information Technology and Computer Science KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) IJID (International Journal on Informatics for Development) JURIKOM (Jurnal Riset Komputer) Jurnal Tekno Kompak TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Indonesian Journal of Electrical Engineering and Computer Science Bubungan Tinggi: Jurnal Pengabdian Masyarakat Jurnal Manajemen Informatika Jayakarta International Journal Software Engineering and Computer Science (IJSECS) Berdikari : Jurnal Pengabdian kepada Masyarakat ABDINE Jurnal Pengabdian Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science Technology and Informatics Insight Journal KAMI MENGABDI Journal of Data Science Theory and Application Journal of Digital Business and Management Prosiding Seminar Nasional Rekayasa dan Teknologi (TAU SNAR- TEK) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Edusight International Journal of Multidisciplinary Studies (EIJOMS) International Journal of Law Social Sciences and Management Computer Journal
Tundo, Tundo
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Application of The Fuzzy Inference System Method to Predict The Number of Weaving Fabric Production Tundo, Tundo; Sela, Enny Itje
IJID (International Journal on Informatics for Development) Vol 7, No 1 (2018): IJID June
Publisher : Universitas Islam Negeri Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2018.07105

Abstract

In this study discusses the application of fuzzy logic in solving production problems using the Tsukamoto method and the Sugeno method. The problem that is solved is how to determine the production of woven fabric when using three variables as input data, namely: stock, demand and inventory of production costs. The first step is to solve the problem of woven fabric production using the Tsukamoto method which is to determine the input variables and output variables which are firm sets, the second step is to change the input variable into a fuzzy set with the fuzzification process, then the third step is processing the fuzzy set data with the maximum method. And the last or fourth step is to change the output into a firm set with the defuzzification process with a weighted average method, so that the desired results will be obtained in the output variable. The solution to the production problem using the Sugeno method is almost the same as using the Tsukamoto method, it's just that the system output is not a fuzzy set, but rather a constant or a linear equation. The difference between the Tsukamoto Method and the Sugeno Method is in consequence. The Sugeno method uses constants or mathematical functions of the input variables.
PREDIKSI PRODUKSI MINYAK KELAPA SAWIT MENGGUNAKAN METODE FUZZY TSUKAMOTO DENGAN RULE YANG TERBENTUK MENGGUNAKAN DECISION TREE REPTREE Tundo, Tundo
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol 9, No 2 (2020)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v9i2.23868

Abstract

Prediction of palm oil production using the Tsukamoto fuzzy method with the rules formed using REPTree decision tree is to speed up the making of the rules used without having to consult with experts. The results of the research analysis found the following conclusions: (1) The rule base model in this study is a decision tree that can be used for Tsukamoto's Fuzzy Inference System with an accuracy of 95.2381%, (2) Rule formed by 5 rules with a time of 0 seconds , (3) The results of direct analysis with real data in April, May, June, July, August, and September 2019 said that the error rate was 23.17% using the Average Forecasting Error Rate (AFER) error method, so the accuracy accuracy is 76.83% on the prediction of the amount of palm oil production. 
Kinerja Logika Fuzzy Sugeno dalam Menangani Prediksi Kain Tenun dengan Kombinasi Random Tree dalam Membangun Rule Tundo, Tundo
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol 10, No 2 (2021)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v10i2.29081

Abstract

This study describes the performance of Sugeno fuzzy logic in determining the amount of woven fabric production by using a combination of random tree decision trees in forming rules. The criteria used in determining the amount of production, namely, production costs, demand, and stock obtained from woven fabric entrepreneurs in Mlaki Wanarejan Utara Pemalang. The random tree decision tree is used, one of which is to automatically generate rules from the available data without consulting with experts, in addition to introducing random trees in the field of research because there are still few studies using this decision tree. The results of this study, it was found that the accuracy while the prediction results tested obtained an Average Forecasting Error Rate (AFER) of 42% with a value 58% truth after being compared with the actual production data.Keywords : Fuzzy Logic, Fuzzy Sugeno Method, Rule, Random tree, Prediction.
Penentuan Kandidat Lurah Pondok Menggunakan Metode Decision Support System Weighted Product (Studi Kasus: Pondok Pesantren Al-Munawwir Krapyak Komplek “L” Yogyakarta) Tundo Tundo
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 6, No 2 (2020): Desember 2020
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (551.421 KB) | DOI: 10.24014/coreit.v6i2.10529

Abstract

Penelitian ini menerangkan metode Decision Support System Weighted Product (WP) dalam menentukan kandidat lurah pondok di Pondok Pesantren Al-Munawwir Krapyak Komplek “L” Yogyakarta, dengan tujuan untuk mengurangi adanya pemilihan kandidat lurah pondok yang bersifat subjektif. Setelah dilakukan penelitian menghasilkan akurasi sebesar 93% mengatakan setuju dengan hasil tiga kandidat lurah pondok yang direkomendasikan yaitu, Adha Hujatu Latif menempati peringkat pertama, Ridwan Syarif menempati peringkat kedua, dan Chanif Mahfudz menempati peringkat ketiga, dari beberapa pilihan alternatif santri yang ada. Sehingga metode ini dapat digunakan dalam menentukan kandidat lurah pondok di Pondok Pesantren Al-Munawwir Krapyak Komplek “L” Yogyakarta.
Pelatihan dalam mencari jurnal publikasi sesuai dengan scope bidang penelitian kepada mahasiswa Magister Informatika UIN Sunan Kalijaga Yogyakarta Tundo Tundo; Yusuf Mufti
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 5, No 2 (2022): Juli
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v5i2.1131

Abstract

Masa pandemi Covid-19 menghentikan semua aktivitas yang mengundang keramaian, salah satunya adalah kegiatan pembelajaran di perguruan tinggi, hanya dilakukan secara daring atau bahkan ada beberapa mahasiswa yang belajar mandiri tanpa bimbingan dari dosen. Bagi Mahasiswa Magister Informatika UIN Sunan Kalijaga Yogyakarta yang sedang fokus terhadap penelitian dituntut untuk tetap menyelesaikan penelitian tersebut dan diusahakan untuk selesai tepat waktu. Salah satu cara dalam membantu mahasiswa tersebut, yaitu dengan cara memberikan pelatihan mencari jurnal publikasi sesuai dengan scope bidang penelitian dengan menggunakan SINTA. Permasalahannya adalah tidak semua mahasiswa familiar dengan SINTA, sehingga diperlukan adanya pelatihan dalam penggunaan SINTA sebagai sarana mencari jurnal publikasi. Kegiatan dilakukan dalam bentuk pelatihan dan pendampingan dalam menggunakan SINTA bagi Mahasiswa Magister Informatika dalam mulai dari akses link, kemudian tempat sarana media jurnal di SINTA, mencari jurnal publikasi sesuai scope bidang, cara mengakses jurnal publikasi yang dipilih, sampai dengan melakukan registrasi untuk dapat melakukan submission artikel dari jurnal publikasi yang dipilih. Berdasarkan hasil kuesioner menunjukkan lebih dari 88% peserta merasa SINTA mudah digunakan dan antusias untuk menjadikan SINTA sebagai media untuk mencari jurnal publikasi yang di dalamnya terdapat artikel-artikel sesuai dengan dengan scope bidang penelitian mahasiswa.  
PREDIKSI PRODUKSI MINYAK KELAPA SAWIT MENGGUNAKAN METODE FUZZY TSUKAMOTO DENGAN RULE YANG TERBENTUK MENGGUNAKAN DECISION TREE REPTREE Tundo Tundo
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 9 No. 2 (2020)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v9i2.23868

Abstract

Prediction of palm oil production using the Tsukamoto fuzzy method with the rules formed using REPTree decision tree is to speed up the making of the rules used without having to consult with experts. The results of the research analysis found the following conclusions: (1) The rule base model in this study is a decision tree that can be used for Tsukamoto's Fuzzy Inference System with an accuracy of 95.2381%, (2) Rule formed by 5 rules with a time of 0 seconds , (3) The results of direct analysis with real data in April, May, June, July, August, and September 2019 said that the error rate was 23.17% using the Average Forecasting Error Rate (AFER) error method, so the accuracy accuracy is 76.83% on the prediction of the amount of palm oil production. 
Kinerja Logika Fuzzy Sugeno dalam Menangani Prediksi Kain Tenun dengan Kombinasi Random Tree dalam Membangun Rule Tundo Tundo
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 10 No. 2 (2021)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v10i2.29081

Abstract

This study describes the performance of Sugeno fuzzy logic in determining the amount of woven fabric production by using a combination of random tree decision trees in forming rules. The criteria used in determining the amount of production, namely, production costs, demand, and stock obtained from woven fabric entrepreneurs in Mlaki Wanarejan Utara Pemalang. The random tree decision tree is used, one of which is to automatically generate rules from the available data without consulting with experts, in addition to introducing random trees in the field of research because there are still few studies using this decision tree. The results of this study, it was found that the accuracy while the prediction results tested obtained an Average Forecasting Error Rate (AFER) of 42% with a value 58% truth after being compared with the actual production data.Keywords : Fuzzy Logic, Fuzzy Sugeno Method, Rule, Random tree, Prediction.
Application of The Fuzzy Inference System Method to Predict The Number of Weaving Fabric Production Tundo Tundo; Enny Itje Sela
IJID (International Journal on Informatics for Development) Vol. 7 No. 1 (2018): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (886.158 KB) | DOI: 10.14421/ijid.2018.07105

Abstract

In this study discusses the application of fuzzy logic in solving production problems using the Tsukamoto method and the Sugeno method. The problem that is solved is how to determine the production of woven fabric when using three variables as input data, namely: stock, demand and inventory of production costs. The first step is to solve the problem of woven fabric production using the Tsukamoto method which is to determine the input variables and output variables which are firm sets, the second step is to change the input variable into a fuzzy set with the fuzzification process, then the third step is processing the fuzzy set data with the maximum method. And the last or fourth step is to change the output into a firm set with the defuzzification process with a weighted average method, so that the desired results will be obtained in the output variable. The solution to the production problem using the Sugeno method is almost the same as using the Tsukamoto method, it's just that the system output is not a fuzzy set, but rather a constant or a linear equation. The difference between the Tsukamoto Method and the Sugeno Method is in consequence. The Sugeno method uses constants or mathematical functions of the input variables. From the calculation data of the production of Mlaki Wanarejan Utara Pemalang woven fabric according to Tsukamoto's method in March 2017 using Weka's rule obtained 343 woven fabrics in meters, while using the Sugeno method obtained 371 woven fabrics in meters. While according to Tsukamoto's method in March 2017 using monotonous rules obtained 313 woven fabrics in meters, then using the Sugeno method obtained 321 woven fabrics in meters, while according to the company's production data in March 2017 produced 340 woven fabrics in meters, then from the analysis direct comparison with the original data in the company can be concluded that the method that is closest to the truth value is the production obtained by processing data using the Tsukamoto method using the Weka rules.
Analisis Perbandingan Rule Pakar dan Decision Tree J48 Dalam Menentukan Jumlah Produksi Kain Tenun Menggunakan Metode Fuzzy Tsukamoto Tundo Amri Mujahid; Enny itje Sela
JURIKOM (Jurnal Riset Komputer) Vol 6, No 5 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v6i5.1510

Abstract

This study explains the comparative analysis of expert rules and J48 decision tree using Tsukamoto fuzzy in determining the amount of woven fabric production. From the results of the research analysis, it was found that the rule base model in this study was a decision tree with 83.3333% accuracy based on the J48 decision tree algorithm that was tested using WEKA tools. The results of direct comparison analysis with actual production data that J48 decision tree rule is the closest to the actual data is with an error rate of 3.89% so that the accuracy of the truth reaches 96.11%, while using expert rules has an error rate of 14.45% so that the accuracy truth obtained reached 85.55%. Therefore, an idea was found that to make a rule without having to consult with experts, that is enough to use a decision tree with WEKA tools, because WEKA tools will display the accuracy of the truth of the rules formed.
Implementation of the Weighted Aggregated Sum Product Assessment Method in Determining the Best Rice for Serabi Cake Making Tundo Tundo; Doni Kurniawan
IJID (International Journal on Informatics for Development) Vol. 8 No. 1 (2019): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.524 KB) | DOI: 10.14421/ijid.2019.08107

Abstract

This study explains the implementation using the Weighted Aggregated Sum Product Assessment method in determining the best rice to be used for making Serabi cakes, the case was taken from a Serabi cake seller in Tegal City, Central Java with the aim of providing knowledge to Serabi cake traders to be more detailed in determining the rice that is used. suitable for use in making Serabi not just rice is cheap, but it is necessary to see the shape and characteristics of the whole rice. The steps taken to determine the best rice which will then be used as the basis for making Serabi cakes using the Weighted Aggregated Sum Product Assessment method are: (1) Prepare a matrix in which is the value of each set of criteria, (2) Normalize matrix data x becomes normalized data, (3) Calculates alternative values using Weighted Aggregated Sum Product Assessment formula so that the ranking value is found. After these steps are carried out, in this study the best rice that is right to be used as a material for making Serabi is Pelita rice with a yield of 7.12 by occupying the first rank.
Co-Authors Abdus Salam, Abdus Ahmad Satria Rizqi Maula Akbar, Rasyan Akbar, Riolandi Akbar, Yuma Alief Prima Gani Amelia, Ika Arinal, Veri Arvianto, Ramdani Aryanti, Putri Gea Aula, Raisah Fajri Aulia Nur Septiani Azhar, Anisah Nurul Betty Yel, Mesra Betty Yel, Mesra Bobby Arvian James Dadang Iskandar Mulyana` Dalail Dalail Dalail, Dalail Devia, Elmi Dewantara, Rizki Dewanti, Elsa Mayorita Dharmawan, Tio Doni Kurniawan Doni Kurniawan Eldina, Ratih Enny Itje Sela Fakhrurrofi Fakhrurrofi Fakhrurrofi, Fakhrurrofi Faldo Satria Faridatun Nisa Gatra, Rahmadhan Hadi Gunawan, Hadi Haryati Heri Mahyuzar Heri Mahyuzar James, Bobby James, Bobby Arvian Januarsyah, Firly Joko Sutopo Julianda, Rindy Junaidi Junaidi Kasiono, Roy Kastum Kastum Kastum, Kastum Kevin Arya Josaphat Sitompul Khafid Nurohman Khana, Rajes Laras Sitoayu Lutfi Nugrahaini M. A. Burhanuddin Maharani, Delia Maharani, Shinta Aulia Mahardika, Fajar Mahyuzar, Heri Marliani, Tiara Marthy, Nicola Mohd Khanapi Abd Ghani Mubarak, Zulfikar Yusya Muhammad Nurdin Muhammad Syazidan Nabilah, Laila Nandang Sutisna Nisa, Faridatun Nizar, Amin Nugraha, Pramudya Nugrahaini, Lutfi Nugroho, Agung Yuliyanto Nugroho, Wisnu Dwi Nuradi, Fahmi Nurohman, Khafid Opi Irawansah, Opi Paidi, Imam Prayogo, Fadillah Abi Priyanto, Imansyah Purnasiwi, Rona Guines Purwasih, Intan Putri Wibowo, Salsabila Qolbi, Rofika Rachmat Hidayat Insani Rachmawati, Dea Noer Raden Dewa Saktia Purnama Raffiudin, Muhammad Raihanah, Syifa Ramadhan, Abhirama Huga Ramadhani, Devika Azahra Rasiban Ridho Akbar Rizki Maulana, Rizki Romadan, Diva Putra Saidah, Andi Saifullah, Shoffan Saktia Purnama, Raden Dewa Sarimole, Frencis Matheos Setiawan, Kiki Shofwatul ‘Uyun Sodik SOPAN ADRIANTO Sopan Adrianto Sri Lestari Sugeng Sugiono Sugiono Sugiyono Sugiyono Sugiyono Suropati, Untung Sutisna, Nandang Syani, Muhammad Tampubolon, Parlindungan Tasti, Andi Thalita Tiara Ratu Alifia Tresia, Eflin Tri Wahyudi Tundo Tundo Untung Suropati Wafiqi, Achmad Ulul Azmi Wagiman, Wagiman Waloeya, Farhan Adriansyah Wijonarko, Panji Yacob, Galih Satria