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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Voice Of Informatics Abdimasku : Jurnal Pengabdian Masyarakat Journal of Computing Theories and Applications Journal of Multiscale Materials Informatics Journal of Future Artificial Intelligence and Technologies
T. Sutojo
Program Studi Teknik Informatika, Fakultas Ilmu Komputer Universitas Dian Nuswantoro
Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Social Sciences

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Tingkat Kesulitan Dinamis Menggunakan Logika Fuzzy pada Game Musik Tradisional Jawa Tengah Wisinggya, Kadhana Reya; Haryanto, Hanny; Sutojo, T.; Mulyanto, Edy; Dolphina, Erlin
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol 5 No 2 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v5i2.281

Abstract

The culture in Indonesia is very diverse, one of which is traditional songs. However, knowledge of traditional songs is still small. Digital Games can spread knowledge about traditional songs, one of which is Central Javanese traditional songs. However, the Game that is made still has static difficulties, so the Game cannot follow the player's ability, resulting in the player feeling bored and not wanting to continue the Game. To generate dynamic difficulties, methods in artificial intelligence can be applied to Games, one of which is Fuzzy. So in this study proposed the application of dynamic difficulties using Fuzzy Logic in music Games / Rhythm Games. Fuzzy Logic is built based on mathematical values and represents uncertainty, where this logic imitates the human way of thinking. Fuzzy Logic can convert crisp input values into fuzzy sets by performing fuzzification. After the input value is converted, the input will be entered into the set of rules provided. Each rule produces a different output. After the process is complete, the output value will be converted back to the crisp output value. Based on the research conducted, it is found that Fuzzy Logic can be applied to music Games where the Game can follow the player's ability based on the given rules.
Implementasi Pengolahan Citra dan Klasifikasi K-Nearest Neighbor untuk Mendeteksi Kualitas Telur Ayam Rahmadianto, Rizky; Mulyanto, Edy; Sutojo, T.
Jurnal VOI (Voice Of Informatics) Vol 8, No 1 (2019)
Publisher : STMIK Tasikmalaya

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

Abstract

Telur ayam tidak hanya mengandung protein namun dilengkapi dengan Omega-3. Omega-3 inilah yang membuat telur akan kaya manfaat dan tidak hanya protein yang didapat. Telur biasa dan telur omega tidak bisa dibedakan secara kasat mata atau berdasarkan penglihatan manusia saja. Memecahkan telur dan melihat embrio pada telur tersebut merupakan alternatif untuk mengetahui telur tersebut merupakan telur biasa atau telur omega. Kesulitan terjadi jika jumlah telur tersebut puluhan hingga ratusan. Masalah tersebut akan diselesaikan dengan metode klasifikasi menggunakan algoritma K-Nearest Neighbor (KNN).  K-Nearest Neighbor dapat mengatasi masalah dari K-Means, Otsu, Region Props dan Labelling yaitu, kurang akuratnya hasil atau nilai yang diperoleh dan juga merupakan salah satu metode klasifikasi yang mudah dan efektif.  Penelitian ini menggunakan olah citra dan menambahkan metode K-Nearest Neighbor guna mencari klasifikasi data uji, membedakan telur ayam beromega dengan telur ayam biasa dengan analisa tekstur menggunakan statistik orde pertama yaitu mean, standart deviation, skewness, dan kurtosis. Dan untuk uji akurasi menggunakan confusion matrix. Citra telur yang didapat akan dianalisa dengan statistik orde pertama terlebih dahulu. Hasil penelitian menunjukkan bahwa metode yang dipilih berhasil digunakan, dengan hasil K tertinggi yaitu K=7 dan akurasinya 86%. Kata kunci — Telur Ayam, K-Nearest Neighbor, Statistik Orde Pertama Chicken eggs do not only contain protein but are equipped with Omega-3. Omega-3 is what makes eggs will be rich in benefits and not only the protein obtained. Ordinary eggs and omega eggs cannot be distinguished by naked eye or by human vision alone. Breaking the egg and seeing the embryo on the egg is an alternative to knowing that the egg is an ordinary egg or an omega egg. Difficulties occur if the number of eggs is tens to hundreds. The problem will be solved by the classification method using the K-Nearest Neighbor (KNN) algorithm. K-Nearest Neighbor can overcome problems from K-Means, Otsu, Props Region and Labeling, namely, the lack of accurate results or values obtained and also one of the easy and effective classification methods. This study uses image processing and adds the K-Nearest Neighbor method to search for classification of test data, differentiating between Omega 3 chicken eggs and ordinary chicken eggs with texture analysis using first-order statistics, namely the mean, standard deviation, skewness, and kurtosis. And to test the accuracy using confusion matrix. The image of the eggs obtained will be analyzed with first-order statistics first. The results showed that the method chosen was successfully used, with the highest K result, namely K = 7 and its accuracy was 86%. Keywords — Chicken Eggs, K-Nearest Neighbor, First Order Statistics
MENENTUKAN HARGA MOBIL BEKAS DENGAN MENGGUNAKAN METODE FUZZY MAMDANI DAN METODE JARINGAN SYARAF TIRUAN Suria Sandi Winarto; Totok Sutojo
Techno.Com Vol 11, No 3 (2012): Agustus 2012 (Hal. 108-158)
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (415.396 KB) | DOI: 10.33633/tc.v11i3.1007

Abstract

Sejak ditemukannya mobil sebagai alat transportasi, gerak hidup manusia berubah menjadi lebih mudah dan dinamis. Dengan banyaknya keluaran mobil terbaru ditambah dengan semakin gencarnya iklan tentang mobil-mobil terbaru, membuat sebagian konsumen tertarik dan terdorong untuk dapat menukar atau menjual mobilnya dan menggantinya dengan mobil keluaran terbaru, sehingga hal ini menciptakan mobil bekas yang masih layak pakai untuk kembali diperjualbelikan kepada konsumen lainya. Dalam penentuan harga beli sebuah mobil bekas merupakan suatu hal yang bisa dikatakan tidak sulit dan juga tidak mudah bagi penjual dan pembeli.  Untuk menentukan  harga beli mobil bekas setidaknya ada dua faktor yang harus diperhatikan antara lain : harga beli mobil baru dan kondisi . Padahal dalam menentukan harga mobil bekas tersebut tidak hanya dipengaruhi oleh dua faktor itu saja, misalnya dari warna mobil, transmisi, dan tahun keluaran mobil.  Tujuan dari penelitian ini adalah membuat sistem untuk menguji kemampuan metode logika fuzzy mamdani dan metode jaringan syaraf tiruan dalam menentukan harga mobil bekas toyota avanza. Metode penelitian dalam penelitian ini menggunakan metode wawancara dengan mengambil data langsung dari sumbernya yaitu UD. Dito Motor.Dari pengujian data tersebut, diperoleh output yaitu  hasil prediksi harga mobil bekas. Kemudian hasil output dari kedua metode tersebut  akan diuji dengan menggunakan MAPE (Mean Absolute Percentage Error) sehingga akan diketahui rata – rata persentase kesalahan absolute. Kata kunci : Harga Mobil Bekas, Fuzzy Mamdani , Jaringan Syaraf Tiruan, Prediksi, MAPE
MENERAPKAN LOGIKA FUZZY MAMDANI UNTUK MENENTUKAN HARGA JUAL BATIK Andreas Widiyantoro; T. Sutojo; Sudaryanto Sudaryanto
Techno.Com Vol 13, No 2 (2014): Mei 2014 (Hal. 69-131)
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (598.18 KB) | DOI: 10.33633/tc.v13i2.544

Abstract

Indonesia adalah negara yang amat sangat kaya akan keanekaragaman budaya dan banyak yang telah diakui UNESCO (United Nations Educational, Scientific and Cultural Organization). Salah satunya adalah batik yang ditetapkan sebagai Warisan Kemanusiaan untuk Budaya Lisan dan Nonbendawi (Masterpieces of the Oral and Intangible Heritage of Humanity) sejak 2 Oktober, 2009. Hal ini menjadikan batik sebagai lahan bisnis yang menjajikan. Namun banyak orang atau pengrajin baru yang terjun kedunia bisnis ini tanpa mempelajarinya lebih dalam sehingga banyak pengusaha yang gulung tikar karena tidak mampu bersaing. Kendala utama mereka terdapat pada penetapan harga batiknya. Banyak batik yang memiliki harga tidak sesuai dengan kualitasnya dan tidak sesuai dengan harga pasar. Untuk mengatasi masalah tersebut dibutuhkan sebuah sistem yang dapat membantu menentukan harga jual batik dengan menggunakan metode Logika Fuzzy Mamdani. Hal ini memungkinkan sistem memberikan harga dengan perhitungan yang tepat dan diharapkan dengan adanya sistem ini akan memudahkan penjual atau pebisnis batik memberikan harga sesuai dengan harga pasar. Hasil dari penelitian ini adalah berupa prototype yang dapat mengolah inputan menjadi output yaitu harga jual batik.Kata Kunci : Fuzzy Mamdani, harga, jual, batik.
Tingkat Kesulitan Dinamis Menggunakan Logika Fuzzy Pada Game Musik Tradisional Jawa Tengah Wisinggya, Kadhana Reya; Haryanto, Hanny; Sutojo, T.; Mulyanto, Edy; Dolphina, Erlin
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 5 No. 2 (2021)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v5i2.281

Abstract

ABSTRACT The culture in Indonesia is very diverse, one of which is traditional songs. However, knowledge of traditional songs is still small. Digital Games can spread knowledge about traditional songs, one of which is Central Javanese traditional songs. However, the Game that is made still has static difficulties, so the Game cannot follow the player's ability, resulting in the player feeling bored and not wanting to continue the Game. To generate dynamic difficulties, methods in artificial intelligence can be applied to Games, one of which is Fuzzy. So in this study proposed the application of dynamic difficulties using Fuzzy Logic in music Games / Rhythm Games. Fuzzy Logic is built based on mathematical values and represents uncertainty, where this logic imitates the human way of thinking. Fuzzy Logic can convert crisp input values into fuzzy sets by performing fuzzification. After the input value is converted, the input will be entered into the set of rules provided. Each rule produces a different output. After the process is complete, the output value will be converted back to the crisp output value. Based on the research conducted, it is found that Fuzzy Logic can be applied to music Games where the Game can follow the player's ability based on the given rules.
Pendampingan Pembuatan Konten Youtube Bagi Siswa SMA At Thohiriyyah Semarang astuti, yani parti; Subhiyakto, Egia Rosi; Dolphina, Erlin; Sutojo, Totok; Rafrastara, Fauzi Adi; Kartikadarma, Etika
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 7, No 2 (2024): MEI 2024
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v7i2.2261

Abstract

The extraordinary use of YouTube at this time indicates that developments in the world of technology are very rapid. But it must always be aware that technological developments also affect the psychological development of children. As is the case at the age of children - teenagers who sometimes cannot control. The development of the use of technology, information and communication in the digital world has had various impacts on our lives. As happened at SMA At Thohiriyyah Semarang, which has a middle to lower economic background and is located on the outskirts of East Semarang. At that high school, the students still don't understand the correct use of YouTube. They just watch content that is sometimes not useful. With these problems, they must be given assistance on how to use YouTube properly. For this reason, they must be made active in using YouTube by having an account and being able to create useful content for other people. Apart from that, they are expected to be able to entertain other people through the content they create
Investigation of Corrosion Inhibition Efficiency of Pyridine-Quinoline Compounds through Machine Learning Herowati, Wise; Akrom, Muhamad; Hidayat, Novianto Nur; Sutojo, Totok
Journal of Multiscale Materials Informatics Vol. 1 No. 1 (2024): April
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jimat.v1i1.10448

Abstract

Corrosion in materials is a significant concern for the industrial and academic fields because corrosion causes enormous losses in various fields such as the economy, environment, society, industry, security, safety, and others. Currently, material damage control using organic compounds has become a popular field of study. Pyridine and quinoline stand out as corrosion inhibitors among a myriad of organic compounds because they are non-toxic, inexpensive, and effective in a variety of corrosive environments. Experimental investigations in developing various candidate potential inhibitor compounds are time and resource-intensive. In this work, we use a quantitative structure-property relationship (QSPR)-based machine learning (ML) approach to investigate support vector machine (SVR), random forest (RF), and k-nearest neighbors (KNN) algorithms as predictive models of inhibition performance. (Inhibition efficiency) corrosion of pyridine-quinoline derivative compounds as corrosion inhibitors on iron. We found that the RF model showed the best predictive ability based on the coefficient of determination (R2) and root mean squared error (RMSE) metrics. Overall, our study provides new insights regarding the ML model in predicting corrosion inhibition on iron surfaces.
Exploring Deep Q-Network for Autonomous Driving Simulation Across Different Driving Modes Setiawan, Marcell Adi; Setiadi, De Rosal Ignatius Moses; Astuti, Erna Zuni; Sutojo, T.; Setiyanto, Noor Ageng
Journal of Future Artificial Intelligence and Technologies Vol. 1 No. 3 (2024): December 2024
Publisher : Future Techno Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/faith.3048-3719-31

Abstract

The rapid growth in vehicle ownership has led to increased traffic congestion, making the need for autonomous driving solutions more urgent. Autonomous Vehicles (AVs) offer a promising solution to improve road safety and reduce traffic accidents by adapting to various driving conditions without human intervention. This research focuses on implementing Deep Q-Network (DQN) to enhance AV performance in different driving modes: safe, normal, and aggressive. DQN was selected for its ability to handle complex, dynamic environments through experience replay, asynchronous training, and epsilon-greedy exploration. We designed a simulation environment using the Highway-env platform and evaluated the DQN model under varying traffic densities. The performance of the AV was assessed based on two key metrics: success rate and total reward. Our findings show that the DQN model achieved a success rate of 90.75%, 94.625%, and 95.875% in safe, normal, and aggressive modes, respectively. Although the success rate increased with traffic intensity, the total reward remained lower in aggressive driving scenarios, indicating room for optimization in decision-making processes under highly dynamic conditions. This study demonstrates that DQN can adapt effectively to different driving needs, but further optimization is needed to enhance performance in more challenging environments. Future work will focus on improving the DQN algorithm to maximize both success rate and reward in high-traffic scenarios and testing the model in more diverse and complex environments.
Pemanfaatan Google Site dalam Pelatihan Pembuatan Website Sebagai Kegiatan Penunjang Edukasi Life Skills Pelajar SMA N 2 Mranggen Kabupaten Demak Herowati, Wise; Kurniawan, Achmad Wahid; Budi, Setyo; Muljono, Muljono; Rustad, Supriadi; Ignatius Moses Setiadi, De Rosal; Sutojo, T.; Trisnapradika, Gustina Alfa; Aprihartha, Moch Anjas
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 1 (2025): JANUARI 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i1.2840

Abstract

Menghadapi persaingan kemampuan dan keterampilan terutama untuk generasi sekarang harusnya dihadapi dengan mempersiapkan pengetahuan yang mumpuni terutama kemampuan-kemampuan untuk menunjang life skills . Kemampuan tersebut perlu diperkuat sedari diri terutama pada jenjang pendidikan menengah atas atau jenjang SMA. Salah satu kemampuan yang dapat diasah pada jenjang pendidikan tersebut adalah pengetahuan dan kemampuan mengenai pembuatan sebuah website. Menciptakan sebuah website sering kali dianggap sulit dan membutuhkan kemampuan pemrograman khusus, hal ini menjadi tantangan tersendiri salah satunya bagi salah satu sekolah yakni SMA N 2 Mranggen Demak. Sebagai salah satu cara menyelesaikan tantangan tersebut, kegiatan PKM yang telah terlaksana ini memperkenalkan konsep dasar pembuatan website menggunakan Google Site. Diharapkan melalui kegiatan pelatihan tersebut para pelajar dapat memiliki keterampilan tambahan untuk menambah kemampuan guna menunjang life skills mereka
Integrating Quantum, Deep, and Classic Features with Attention-Guided AdaBoost for Medical Risk Prediction Kusuma, Muh Galuh Surya Putra; Setiadi, De Rosal Ignatius Moses; Herowati, Wise; Sutojo, T.; Adi, Prajanto Wahyu; Dutta, Pushan Kumar; Nguyen, Minh T.
Journal of Computing Theories and Applications Vol. 3 No. 2 (2025): in progress
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.14873

Abstract

Chronic diseases such as chronic kidney disease (CKD), diabetes, and heart disease remain major causes of mortality worldwide, highlighting the need for accurate and interpretable diagnostic models. However, conventional machine learning methods often face challenges of limited generalization, feature redundancy, and class imbalance in medical datasets. This study proposes an integrated classification framework that unifies three complementary feature paradigms: classical tabular attributes, deep latent features extracted through an unsupervised Long Short-Term Memory (LSTM) encoder, and quantum-inspired features derived from a five-qubit circuit implemented in PennyLane. These heterogeneous features are fused using a feature-wise attention mechanism combined with an AdaBoost classifier to dynamically weight feature contributions and enhance decision boundaries. Experiments were conducted on three benchmark medical datasets—CKD, early-stage diabetes, and heart disease—under both balanced and imbalanced configurations using stratified five-fold cross-validation. All preprocessing and feature extraction steps were carefully isolated within each fold to ensure fair evaluation. The proposed hybrid model consistently outperformed conventional and ensemble baselines, achieving peak accuracies of 99.75% (CKD), 96.73% (diabetes), and 91.40% (heart disease) with corresponding ROC AUCs up to 1.00. Ablation analyses confirmed that attention-based fusion substantially improved both accuracy and recall, particularly under imbalanced conditions, while SMOTE contributed minimally once feature-level optimization was applied. Overall, the attention-guided AdaBoost framework provides a robust and interpretable approach for clinical risk prediction, demonstrating that integrating diverse quantum, deep, and classical representations can significantly enhance feature discriminability and model reliability in structured medical data.
Co-Authors Achmad Wahid Kurniawan Akrom, Muhamad Andreas Widiyantoro Astuti, Yani Parti Budi, Setyo De Rosal Ignatius Moses Setiadi Dutta, Pushan Kumar Egia Rosi Subhiyakto, Egia Rosi Erlin Dolphina Erna Zuni Astuti Etika Kartikadarma Fauzi Adi Rafrastara Hanny Haryanto Herowati, Wise Hidayat, Novianto Nur Ignatius Moses Setiadi, De Rosal Kusuma, Muh Galuh Surya Putra Minh T. Nguyen, Minh T. Moch Anjas Aprihartha Muljono Muljono Mulyanto, Edy Noor Ageng Setiyanto, Noor Ageng Prajanto Wahyu Adi, Prajanto Wahyu Rahmadianto, Rizky Setiawan, Marcell Adi Sudaryanto Sudaryanto Supriadi Rustad Suria Sandi Winarto Trisnapradika, Gustina Alfa Wisinggya, Kadhana Reya