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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JURNAL SISTEM INFORMASI BISNIS Jurnal Sistem Komputer JSI: Jurnal Sistem Informasi (E-Journal) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Desimal: Jurnal Matematika INOVTEK Polbeng - Seri Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal on Emerging Mathematics Education Jurnal ULTIMA InfoSys MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Sistem Informasi dan Aplikasi Journal of Information Technology and Computer Engineering J-SAKTI (Jurnal Sains Komputer dan Informatika) Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUKATIF : JURNAL ILMU PENDIDIKAN Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Journal of Information Systems and Informatics KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) ICIT (Innovative Creative and Information Technology) Journal Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) IAIC Transactions on Sustainable Digital Innovation (ITSDI) JOINTER : Journal of Informatics Engineering International Journal of Engineering, Science and Information Technology Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Information Technology (JIfoTech) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat JEECS (Journal of Electrical Engineering and Computer Sciences) Metris: Jurnal Sains dan Teknologi Scientific Journal of Informatics International Journal of Information Technology and Business INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal DIMASTIK
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Digital Image Object Detection with GLCM Multi-Degrees and Ensemble Learning Kurniati, Florentina Tatrin; Purnomo, Hindriyanto Dwi; Sembiring, Irwan; Iriani, Ade
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 2 (2024): April 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i2.5597

Abstract

Object detection in digital images has been implemented in various fields. Object detection faces challenges, one of which is rotation problems, causing objects to become unknown. We need a method that can extract features that do not affect rotation and reliable ensemble-based classification. The proposal uses the GLCM-MD (Gray-Level Co-occurrence Matrix Multi-Degrees) extraction method with classification using K-Nearest Neighbours (K-NN) and Random Forest (RF) learning as well as Voting Ensemble (VE) from two single classifications. The main goal is to overcome the difficulty of detecting objects when the object experiences rotation which results in significant visualization variations. In this research, the GLCM method is used to produce features that are stable against rotation. Furthermore, classification methods such as K-Nearest Neighbours (KNN), Random Forest (RF), and KNN-RF fusion using the Voting ensemble method are evaluated to improve detection accuracy. The experimental results show that the use of multi-degrees and the use of ensemble voting at all degrees can increase the accuracy value, and the highest accuracy for extraction using multi-degrees is 95.95%. Based on test results which show that the use of features of various degrees and the ensemble voting method can increase accuracy for detecting objects experiencing rotation
Metaheuristics Approach for Hyperparameter Tuning of Convolutional Neural Network Purnomo, Hindriyanto; Tad Gonsalves; Evangs Mailoa; Santoso, Fian Julio; Pribadi, Muhammad Rizky
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 3 (2024): June 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i3.5730

Abstract

Deep learning is an artificial intelligence technique that has been used for various tasks. Deep learning performance is determined by its hyperparameter, architecture, and training (connection weight and bias). Finding the right combination of these aspects is very challenging. Convolution neural networks (CNN) is a deep learning method that is commonly used for image classification. It has many hyperparameters; therefore, tuning its hyperparameter is difficult. In this research, a metaheuristic approach is proposed to optimize the hyperparameter of convolution neural networks. Three metaheuristic methods are used in this research: ant colony optimization (ACO), genetic algorithm (GA), and Harmony Search (HS). The metaheuristics methods are used to find the best combination of 8 hyperparameters with 8 options each which creates 1.6. 107 of solution space. The solution space is too large to explore using manual tuning. The Metaheuristics method will bring benefits in terms of finding solutions in the search space more effectively and efficiently. The performance of the metaheuristic methods is evaluated using MNIST datasets. The experiment results show that the accuracy of ACO, GA and HS are 99,7%, 97.7% and 89,9% respectively. The computational times for the ACO, GA and HS algorithms are 27.9 s, 22.3 s, and 56.4 s, respectively. It shows that ACO performs the best among the three algorithms in terms of accuracy, however, its computational time is slightly longer than GA. The results of the experiment reveal that the metaheuristic approach is promising for the hyperparameter tuning of CNN. Future research can be directed toward solving larger problems or improving the metaheuristics operator to improve its performance.
Optimizing Multilayer Perceptron with Cost-Sensitive Learning for Addressing Class Imbalance in Credit Card Fraud Detection Priatna, Wowon; Hindriyanto Dwi Purnomo; Ade Iriani; Irwan Sembiring; Theophilus Wellem
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5917

Abstract

The increasing use of credit cards in global financial transactions offers significant convenience for consumers and businesses. However, credit card fraud remains a major challenge due to its potential to cause substantial financial losses. Detecting credit card fraud is a top priority, but the primary challenge lies in class imbalance, where fraudulent transactions are significantly fewer than non-fraudulent ones. This imbalance often leads to machine learning algorithms overlooking fraudulent transactions, resulting in suboptimal performance. This study aims to enhance the performance of Multilayer Perceptron (MLP) in addressing class imbalance by employing cost-sensitive learning strategies. The research utilizes a credit card transaction dataset obtained from Kaggle, with additional validation using an e-commerce transaction dataset to strengthen the robustness of the findings. The dataset undergoes preprocessing with RUS and SMOTE techniques to balance the data before comparing the performance of baseline MLP models to those optimized with cost-sensitive learning. Evaluation metrics such as accuracy, recall, F1 score, and AUC indicate that the optimized MLP model significantly outperforms the baseline, achieving an AUC of 0.99 and a recall of 0.6. The model's superior performance is further validated through statistical tests, including Friedman and T-tests. These results underscore the practical implications of implementing cost-sensitive learning in MLPs, highlighting its potential to significantly enhance fraud detection accuracy and offer substantial benefits to financial institutions.
Modern Ethnomathematics Mainstreaming through Mathematics Entrepreneurship Using Mathematical Ornaments Parhusip, Hanna Arini; Purnomo, Hindriyanto Dwi; Nugroho, Didit Budi; Sri Kawuryan, Istiarsi Saptuti Sri
International Journal on Emerging Mathematics Education IJEME, Vol. 5 No. 2, September 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijeme.v5i2.15118

Abstract

Modern ethnomathematics is proposed in this article by introducing curves and surfaces to objects based on commonly used mathematics. There are 2 types of objects, batik and ornament. The object is known as Batima, which means a mathematical motif made in a batik stamp. The same design can be used to design ornaments, souvenirs, accessories or other household items such as glasses, t-shirts and other materials. The formation of ethnomathematics is driven by entrepreneurial activities. The method starts with the expansion of the circular and spherical equations based on the variation of the power form which was originally 2 in the equation to be valued at random (say p). The other used equations are parametric equations, especially the hypocycloid which is extended to both curves and surfaces with spherical coordinates. In addition, derivative operators can be applied. Product manufacturing is carried out by at least 10 household businesses around Salatiga and Jogjakarta and its surroundings. In order to sustain the mainstreaming of modern ethnomathematics, entrepreneurial activities are carried out with existing materials through exhibitions and competitions that are followed. Likewise, the use of social media and marketplaces are explored to mainstream the modern ethnomathematics into society.
Learning geometry through surface creation from the hypocycloid curves expansion with derivative operators for ornaments Parhusip, Hanna Arini; Purnomo, Hindriyanto Dwi; Nugroho, Didit Budi; Kawuryan, Istiarsi Saptuti Sri
Desimal: Jurnal Matematika Vol. 4 No. 1 (2021): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v4i1.7385

Abstract

Geometry is one of the particular problems for students. Therefore, several methods have been developed to attract students to learn geometry. For undergraduate students, learning geometry through surface visualization is introduced. One topic is studying parametric curves called the hypocycloid curve. This paper presents the generalization of the hypocycloid curve. The curve is known in calculus and usually is not studied further. Therefore, the research's novelty is introducing the spherical coordinate to the equation to obtain new surfaces. Initially, two parameters are indicating the radius of 2 circles governing the curves in the hypocycloid equations. The generalization idea here means that the physical meaning of parameters is not considered allowing any real numbers, including negative values. Hence, many new curves are observed infinitely. After implementing the spherical coordinates to the equations and varying the parameters, various surfaces had been obtained. Additionally, the differential operator was also implemented to have several other new curves and surfaces. The obtained surfaces are useful for learning by creating ornaments. Some examples of ornaments are presented in this paper.
MATHEMATICAL SILVER FOR ENTREPRENEURIAL MATHEMATICS Parhusip, Hanna Arini; Nugroho, Didit Budi; Purnomo, Hindriyanto Dwi; Kawuryan, Istiarsi Saptuti Sri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (472.285 KB) | DOI: 10.30598/barekengvol16iss4pp1175-1184

Abstract

This article shows the result of entrepreneur mathematics by creating mathematical objects from silver. The objects discussed here are accessories to introduce undergraduate students to integrating several aspects of learning mathematics. These are learning geometry modernly, mathematical art, popularizing mathematics for society, introducing entrepreneurial values using mathematics, teamwork for achieving targets, and considering local heritage in mathematics. These aspects are blended into activity by creating designs and producing products based on the obtained designs. The particular product for this activity is creating silver accessories. The used research method is initiated by creating designs with the help of software where the surface equations are known. After the designs are obtained, the designs are communicated to the silver craftsman to be a partner in design testing and manufacturing of accessories products using the given designs. The size and the similarity of perceptions to the appearance of the design are discussed because the actual design is a three-dimensional image but expressed in objects to be two- dimensional objects. After productions are obtained, the accessories are managed to be promoted to the marketplace and social media as a form of entrepreneurial activity with materials starting from mathematics.
Implementasi sistem monitoring kualitas air berbasis IoT pada penampung mata air di daerah Larier Ambon Kainama, Marchel Devid; Purnomo, Hindriyanto Dwi
AITI Vol 22 No 2 (2025)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v22i2.206-220

Abstract

Penelitian ini mengembangkan sistem monitoring kualitas air berbasis Internet of Things (IoT) di Larier, Kota Ambon. Sistem menggunakan mikrokontroler Arduino ESP32 dan platform Blynk untuk memantau parameter suhu, pH, dan Total Dissolved Solids (TDS) secara real-time. Sensor-sensor dikalibrasi untuk memastikan akurasi, dan evaluasi kinerja menggunakan Mean Absolute Percentage Error (MAPE) menunjukkan hasil baik, khususnya pada sensor pH dan TDS. Pengujian lapangan dilakukan pada kondisi cuaca hujan dan panas untuk menilai stabilitas pengukuran. Hasil menunjukkan nilai TDS lebih tinggi pada kondisi panas, pH lebih tinggi saat hujan, sedangkan suhu relatif stabil. Sistem ini memungkinkan masyarakat memantau kualitas air secara mandiri melalui aplikasi, serta mendukung pengelolaan sumber daya air yang berkelanjutan. Implementasi ini menunjukkan potensi teknologi IoT dalam meningkatkan kesadaran dan partisipasi masyarakat terhadap kualitas lingkungan lokal.
Advancing Startup Ecosystems Through AI-Driven Matchmaking: A Comprehensive Bibliometric Analysis Lutfiani, Ninda; Wijono, Sutarto; Rahardja, Untung; Purnomo, Hindriyanto Dwi
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1095

Abstract

This study investigates the integration of AI in streamlining the alignment process between startups and potential collaborators and partners, particularly in the Indonesian startup ecosystem. The motivation behind this research lies in the gaps and challenges startups face in efficiently connecting with suitable partners or investors. We employed a bibliometric analysis approach. This study sourced data from Scopus, analysing 515 articles and 59,412 citations published from 2018 to 2023. Key findings provide insights into the predominant role of AI technologies, notably machine learning methods like deep learning and data mining, and the significance of recommendation systems that incorporate collaborative filtering. Furthermore, the results underscore the increasing importance of AI as an indispensable tool in the startup landscape, enhancing the efficiency and productivity of collaborations. We assessed publications from several countries, authors, and citations through the bibliometric measures to comprehensively understand the current trends and trajectories. The study concludes by recognising the transformative potential of AI in fostering tighter and more efficient alliances within the startup ecosystem, laying the groundwork for future research into refining AI-driven collaborative processes.
Organizational Readiness and Barriers to Digital Transformation in Indonesian SMEs Lutfiani, Ninda; Wijono, Sutarto; Dwi Purnomo, Hindriyanto; Zakaria, Noor Azura
APTISI Transactions on Management (ATM) Vol 9 No 3 (2025): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v9i3.2541

Abstract

Digital transformation (DT) is essential for enhancing competitiveness, ef- ficiency, and innovation in the digital era. However, Small and Medium En- terprises (SMEs) in Indonesia face significant barriers to adopting digital tech- nologies due to limited resources, lack of digital skills, and environmental con- straints. This study aims to assess the organizational readiness and identifybarriers to DT adoption among Indonesian SMEs using the Technology Organization Environment (TOE) framework. A survey of 210 SMEs from various sectors was conducted to evaluate their readiness levels and perceived barriers. The results indicate that while SMEs show moderate technological readiness, organizational readiness remains low, primarily due to inadequate human re- source competencies, resistance to change, and limited financial capacity. Addi- tionally, environmental factors such as regulatory uncertainty and weak institu- tional support further impede progress. This study contributes to the existing literature by highlighting the specific challenges faced by SMEs in emerging economies, particularly Indonesia. Based on the findings, the study offers prac- tical recommendations for policymakers, industry associations, and SME own- ers to enhance organizational readiness and mitigate barriers, accelerating the digital transformation process for SMEs in Indonesia.
Sentiment Analysis of e-Government Service Using the Naive Bayes Algorithm purbaratri, Winny; Purnomo, Hindriyanto Dwi; Manongga, Danny; Setyawan, Iwan; Hendry, Hendry
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3272

Abstract

E-Government which involves the use of communication and information technology to provide Public services have three obstacles. One of these obstacles is the implementation of e-Government by autonomous regional governments is still carried out individually. Apart from that, implementing the website regions are also not supported by efficient management systems and work processes, this is partly the case This is largely due to the lack of preparation of regulations, procedures and limited resources man. Apart from that, many local governments consider implementing e-Government only involves developing local government websites. More precisely, the implementation of e-Government It is only limited to the maturity stage and ignores the three other important stages that need to be completed. The aim of this research is to determine the level of public approval for government application services. This research uses the Naive Bayes Classifier approach as the methodology. The data sources used in this research consist of user reviews and comments obtained from Google Play Store. The results of this investigation produce a level of precision The highest is achieving a score of 83%. Additionally it shows an accuracy rate of 83%,levelcompleteness is 100%, and F-measure is 90.7%.
Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Ade Iriani Adimas Tristan Nagara Hartono Adriyanto Juliastomo Gundo Agung Wibowo Agus Priyadi Ahmad Bayu Yadila Andre Kurniawan Andrew Aquila Chrisanto Pabendon Andry Ananda Putra Tanggu Mara Andry Tanggu Mara Angela Atik Setiyanti Ani, Nyree Anton Hermawan Anwar, Muchamad Taufiq April Firman Daru April Lia Hananto Aris Puji Widodo Arseta, Gama Astawa, I Wayan Aswin Dew Atik Setyanti, Angela Aziz Jihadian Barid Azzahra Nurwanda Bandung Pernama Baun, Sindy Cristine Budhi Kristianto Budi Kristianto Budi Kristianto, Budi C. Leuwol, Sylvie Cahyaningtyas, Christyan Cahyo Dimas K Cesna, Galih Putra Chandra Halim Charitas Fibriani Christyan Cahyaningtyas Daniel Kurniawan Daniel Kurniawan Danny Manongga Danu Satria Wiratama Deden Rustiana Dedy Prasetya Kristiadi Didit Budi Nugroho Dody Agung Saputro Dwi Hosanna Bangkalang Edwin Zusrony Eko Sediyono Eliansion Ivan eremia Silvester Sutoyo Erwien Christianto Evang Mailoa Evangs Mailoa Fajar Rahmat Faudisyah, Alfendio Alif Fauzi Ahmad Muda Feibe Lawalata Florentina Tatrin Kurniati Giner Maslebu Gladis Tri Enggiel Griya Jitri Pabutungan Gudiato, Candra Hanita Yulia Hanna Arini Parhusip Hari Purwanto Hendra Kusumah Hendra Waskita Hendradito Dwi Aprillian Hendro Steven Tampake Hendry Heni Pujiastuti Hermanto Abraham, Rendy Hery Santono HR. Wibi Bagas N Hsin Rau Huda, Baenil Hui-Ming Wee Irdha Yunianto Irwan Sembiring Istiarsi Saptuti Sri Kawuryan Istiarsih Saputri Sri Kawuryan Iwan Setiawan Iwan Setyawan Janinda Puspita Anidya Jihot Lumban Gaol Joanito Agili Lopo Jonas, Dendy Kainama, Marchel Devid Karema Sarajar, Dewita Kho, Delvian Christoper Krismiyati Kristoko Dwi Hartomo Lea Klarisa Lumban Gaol, Jihot Markus Permadi Mau, Stevanus Dwi Istiavan Maya Sari Mellyuga Errol Wicaksono Merryana Lestari Mira Mira Mira Muhammad Aufal Muhammad Rizky Pribadi Nadya Octavianna Lompoliuw Nahak, Yosef Jeffri Silvanus Nahusona, Ferry Nanle, Zeze Nina Rahayu Nina Setiyawati Ninda Lutfiani Nurrokhman, Nurrokhman Nurtino, Tio Permadi, Markus Picauly, Irma Amy Pratyaksa Ocsa Nugraha Saian Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purwanto - Purwanto Putri, Violita Eka Radius Tanone Ramos Somya Raynaldo Raynaldo Raynaldo Raynaldo, Raynaldo Richard William Kho Riko Yudistira Robert William Ruhulessin Rufina Rahma Ajeng Setyaningsih Safitri, Adila Sakalessy, Afelia Jozalin Elisa Sampoerno Santoso, Fian Julio Santoso, Fian Yulio Santoso, Joseph Teguh Setiyaji, Akhfan Sri Kawuryan, Istiarsi Saptuti Sri Sri Yulianto Joko Prasetyo Sugiman, Marcelino Maxwell Sutarto Wijono Syamsul Arifin Tad Gonsalves Tad Gonsalves Teguh Indra Bayu Teguh Wahyono Theopillus J. H. Wellem Tirsa Ninia Lina Tri Wahyuningsih Trivena Andriani Tukino, Tukino Tumbade, Marcho Oknivan Tungady, Cornelius Arvel Pratama Untung Rahardja Utama, Deffa Ferdian Alif Valentino Kevin Sitanayah Que Walangara Nau, Novriest Umbu Wibowo, Mars Caroline Widyarini, Liza Wilujeng Ayu Nawang Sari Winny purbaratri Wisnu Wibisono, Indra Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yos Richard Beeh Yos Richard Beeh Yos Richard Beeh Yudistira, Riko Yuli Agung Suprabowo, Gunawan Yusuf, Natasya Aprila Zakaria, Noor Azura