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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Pendidikan Vokasi Jurnal Sains dan Teknologi Jurnal Sarjana Teknik Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi Jurnal Pengabdian UntukMu NegeRI Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING ILKOM Jurnal Ilmiah Compiler KACANEGARA Jurnal Pengabdian pada Masyarakat Martabe : Jurnal Pengabdian Kepada Masyarakat JURTEKSI Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jambura Journal of Informatics Building of Informatics, Technology and Science JISKa (Jurnal Informatika Sunan Kalijaga) Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Informatika dan Rekayasa Perangkat Lunak International Journal of Advances in Data and Information Systems Jurnal REKSA: Rekayasa Keuangan, Syariah dan Audit Innovation in Research of Informatics (INNOVATICS) Humanism : Jurnal Pengabdian Masyarakat Jurnal Pendidikan dan Teknologi Indonesia Prima Abdika: Jurnal Pengabdian Masyarakat Bulletin of Pedagogical Research Jurnal Pengabdian Pada Masyarakat Jurnal Pengabdian Informatika (JUPITA) Bulletin of Social Informatics Theory and Application Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka Mohuyula : Jurnal Pengabdian Kepada Masyarakat Scientific Journal of Informatics
Herman Yuliansyah, Herman
Program Studi Teknik Informatika, Fakultas Teknologi Industri, Universitas Ahmad Dahlan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Pengembangan Aplikasi Web Untuk Penentuan Nutrisi Anak Dengan Metode Fuzzy C-MEANS Berdasarkan Produk Kemasan Rachmaliany, Nur; Winiarti, Sri; Yuliansyah, Herman
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 2, No 2, May-2017
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (598.173 KB) | DOI: 10.22219/kinetik.v2i2.160

Abstract

Orang tua perlu memperhatikan kualitas dan standar kesehatan produk yang dikonsumsi oleh anaknya. Orang tua juga perlu secara cermat memperhatikan komposisi penggunaan bahan baku pada produk kemasan yang beredar dipasaran. Penelitian ini bertujuan untuk mengembangkan aplikasi web untuk penentuan nutrisi anak dengan metode fuzzy c-means. Hasil penentuan diperoleh dari mempertimbangkan beberapa indikator seperti umur, berat badan (BB), tinggi badan (TB). Tahap pengembangan aplikasi adalah perancangan sistem dengan pembuatan basis pengetahuan, membuat model keputusan dengan algoritma fuzzy c-means, dan basis aturan, perancangan proses terdiri dari pembuatan proses bisnis, diagram konteks, Diagram Aliran Data (DAD), struktur menu, desain antarmuka sistem, implementasi, dan pengujian sistem dengan menggunakan metode User Acceptance Test (UAT), Usability Testing (UT), Pengujian Knowledge, dan Validasi Fuzzy C-Means. Hasil dari peneltian ini adalah aplikasi web untuk penentuan nutrisi anak usia 7 bulan sampai 6 tahun yang membantu orang tua untuk mengetahui status gizi anak, dan juga dapat merekomendasikan produk kemasan yang dapat dikonsumsi anak. Hasil dari pengujian User Acceptance Test sebesar 89 % dapat menerima, pengujian Usability Testing sebesar 74,87 % sesuai, pengujian knowledge sebesar 79 % sesuai, dan validasi penerapan fuzzy c-means sebesar 83 %.Kata kunci: Metode Fuzzy C-Means, Nutrisi, Produk Kemasan, Aplikasi Web
RANCANG BANGUN APLIKASI ANDROID POS (POINT OF SALE) KAFE UNTUK KASIR PORTABLE DAN BLUETOOTH PRINTER Pamungkas, Gilang; Yuliansyah, Herman
JST (Jurnal Sains dan Teknologi) Vol 6, No 1 (2017)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.996 KB) | DOI: 10.23887/jst-undiksha.v6i1.8828

Abstract

Kafe merupakan salah satu jenis usaha di bidang kuliner yang banyak diminati pengunjung. Beberapa permasalahan yang ada adalah sistem transaksi keuangan di kafe belum memanfaatkan kasir digital, hanya berupa mesin drawer. Sehingga terdapat batasan pada perhitungan transaksi. Tujuan dari penelitian menghasilkan aplikasi kasir tablet android untuk membantu proses transaksi penjualan dan dapat merekapitulasi laporan data transaksi di kafe. Selain itu, pada aplikasi ini ditambahkan fitur pencetakan kwitansi untuk pelanggan. Pengujian aplikasi android dilakukan dengan metode unit test dan menunjukkan sudah berjalan dengan lancar dan tidak ada method yang error, sehingga dapat dinyatakan lolos. Selain itu, pengujian black box test dapat disimpulkan bahwa aplikasi berjalan sesuai dengan yang telah dirancang.
PELATIHAN PENGELOLAAN MATERI PEMBELAJARAN DENGAN E-LEARNING BAGI SEKOLAH MUHAMMADIYAH KECAMATAN MOYUDAN KABUPATEN SLEMAN Winiarti, Sri; Astuti, Nur Rochmah Dyah Puji; Yuliansyah, Herman
Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Vol 2, No 2 (2018)
Publisher : Universitas Ahmad Dahlan, Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (751.831 KB) | DOI: 10.12928/jp.v2i2.429

Abstract

The schools in Mayodan sub-district have not used information technology with maximum to support learning and education activity. They need assistance in community service to train them to organize learning media using eLearning. The methods of implementing the training are tutorial or assistance, giving a module to participants, workshop and evaluation process. The impact of this training is improvement knowledge in information technology uses. This impact can show from training result. The result showed 74% participants agree and like with this training results.
Sistem Informasi Farmasi Berbasis Web Mobile Dengan Fitur Deteksi Kesalahan Obat Dalam Penjualan Obat Peracikan Yuliansyah, Herman; Hildayanti, Ica Kurnia
Mobile and Forensics Vol 1, No 1 (2019)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v1i1.645

Abstract

Salah satu kegiatan di apotek adalah menjual resep atau non-resep. Kesalahan pengobatan dapat terjadi selama penjualan obat. Salah satu penyebab kesalahan pengobatan adalah kesalahan dalam pemberian resep obat. Dengan demikian, Sistem Informasi Farmasi memerlukan fitur yang dapat membantu dalam meminimalkan terjadinya kesalahan pengobatan. Metodologi dalam penelitian ini adalah observasi, wawancara dan studi literatur. Sistem informasi memiliki tiga tingkat pengguna: admin, pekerja gudang dan apoteker. Sistem informasi memiliki fitur deteksi kesalahan obat untuk memproses transaksi penjualan obat peracikan. Sistem informasi dapat menentukan dosis maksimum obat-obatan untuk senyawa dan sistem informasi yang dilengkapi dengan fitur pemberitahuan untuk menyesuaikan antara dosis dokter dan dosis maksimum yang harus diberikan kepada pasien. Hasil dari penelitian ini adalah Sistem Informasi Farmasi, yang memiliki fitur deteksi kesalahan obat, dapat mencegah kesalahan pengobatan karena sistem akan memberikan pemberitahuan untuk menyesuaikan antara dosis dokter dan dosis maksimum. 
Sistem Informasi Farmasi Berbasis Web Mobile Dengan Fitur Deteksi Kesalahan Obat Dalam Penjualan Obat Peracikan Yuliansyah, Herman; Hildayanti, Ica Kurnia
Mobile and Forensics Vol. 1 No. 1 (2019)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v1i1.645

Abstract

Salah satu kegiatan di apotek adalah menjual resep atau non-resep. Kesalahan pengobatan dapat terjadi selama penjualan obat. Salah satu penyebab kesalahan pengobatan adalah kesalahan dalam pemberian resep obat. Dengan demikian, Sistem Informasi Farmasi memerlukan fitur yang dapat membantu dalam meminimalkan terjadinya kesalahan pengobatan. Metodologi dalam penelitian ini adalah observasi, wawancara dan studi literatur. Sistem informasi memiliki tiga tingkat pengguna: admin, pekerja gudang dan apoteker. Sistem informasi memiliki fitur deteksi kesalahan obat untuk memproses transaksi penjualan obat peracikan. Sistem informasi dapat menentukan dosis maksimum obat-obatan untuk senyawa dan sistem informasi yang dilengkapi dengan fitur pemberitahuan untuk menyesuaikan antara dosis dokter dan dosis maksimum yang harus diberikan kepada pasien. Hasil dari penelitian ini adalah Sistem Informasi Farmasi, yang memiliki fitur deteksi kesalahan obat, dapat mencegah kesalahan pengobatan karena sistem akan memberikan pemberitahuan untuk menyesuaikan antara dosis dokter dan dosis maksimum.
Artificial intelligence in malnutrition research: a bibliometric analysis Yuliansyah, Herman; Sulistyawati , Sulistyawati; Sukesi , Tri Wahyuni; Mulasari, Surahma Asti; Wan Ali, Wan Nur Syamilah
Bulletin of Social Informatics Theory and Application Vol. 7 No. 1 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i1.605

Abstract

Malnutrition is a nutritional imbalance in a child’s body. Currently, there have been many reviews done on malnutrition in children. However, reviews on artificial intelligence linked with malnutrition are yet to be done. Thus, this study aims to identify the implementation of artificial intelligence in predicting malnutrition using bibliometric analysis. The bibliometric analysis consists of four stages: determining the purpose and scope, selecting the analytical technique, collecting data, and presenting the findings. Data used for this analysis is sourced from the Scopus database. The investigation was conducted using VOSviewer and “Publish or Perish” software. Based on five searched words: malnutrition, artificial intelligence, machine learning, neural networks, and deep learning, it was found that machine learning is the most widely used artificial intelligence approach for malnutrition research. Deep learning techniques are reported to grow as it is introduced as a new method in artificial intelligence. Malnutrition prediction tasks are the most studied problem. The use of deep learning, reinforcement learning, and transfer learning methods are used tremendously in malnutrition prediction research. This analysis’s results help improve the quality of the review by showing the mapping areas for malnutrition research.
Development of an Integrated Electric Vehicle Learning Simulator (EVLIS) with Industry-Based Learning to Accelerate Work Readiness of Vocational School Students Sudarsono, Bambang; Arief Ghozali, Fanani; Tentama, Fatwa; Asti Mulasari, Surahma; Wahyuni Sukesi, Tri; Sulistyawati, Sulistyawati; Yuliansyah, Herman; Nafiati, Lu'lu'; Listyaningrum, Prabandari; Pratama, Wegig; R. Hafid Hardyanto, Settings; Rahmawati, Rahmawati
Bulletin of Pedagogical Research Vol. 4 No. 1 (2024): Bulletin of Pedagogical Research
Publisher : CV. Creative Tugu Pena

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51278/bpr.v4i1.1029

Abstract

Technological developments in this modern era require changes in educational approaches to ensure that students have skills that are relevant to the needs of industry, especially electric vehicles. The research aims to develop an industrial integrated electric vehicle learning tool and test its feasibility. This research design adopts Richey and Klein's research and development (R&D) stages with development and internal validation stages. The research objects were carried out at four vocational schools in the Special Region of Yogyakarta and the Automotive Jogjakarta Center (OJC) with research subjects being teachers, experts and industrial practitioners. The resulting research is the competency aspects needed by the electric vehicle industry and the design of electric vehicle learning aids/Electric Vehicle Learning Simulator (EVLIS) that are feasible and ready to be made into product prototypes. EVLIS can help improve the attitude competency, knowledge and skills of electric vehicle technology for vocational school students. Not only that, the development of EVLIS involving the electric vehicle industry can strengthen collaboration/partnership between the industrial world and vocational schools. Keywords: Electric Vehicle Learning Simulator (EVLIS), Industry Based Learning, Work Readiness, Vocational High Schools (SMK)
The Effect of Green Perceived Values and Injunctive Norms on Buying Intentions of Eco-Friendly Products Nafiati, Lu'lu'; Sukesi, Tri Wahyuni; Yuliansyah, Herman; Ghozali, Fanani Arief; Tentama, Fatwa; Sudarsono, Bambang; Sulistyawati, Sulistyawati; Mulasari, Surahma Asti; Subardjo, Subardjo
Jurnal REKSA: Rekayasa Keuangan, Syariah dan Audit Vol. 11 No. 1 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jreksa.v11i1.10240

Abstract

This study aims to utilize the multidimensional concept of green perceived value (GPV) and injunctive norms in relation to the intention to buy environmentally friendly products. This research utilized 105 questionnaires to investigate the correlation between GPV, injunctive norms, attitudes toward purchasing, and purchase intention by focusing on four components of GPV: functional value, conditional value, social value, and emotional value. Structural equation models were employed to assess the connections among the seven components. This study adds to the existing literature by exploring the nuanced relationship between green perceived value (GPV), injunctive norms, attitudes toward purchasing, and intention to buy environmentally friendly products. By focusing on four dimensions of GPV - functional value, conditional value, social value, and emotional value - the research sheds light on how these components influence consumer behavior. Using structural equation models and analysis of 105 questionnaires, the study reveals that functional and emotional values significantly impact purchase intention via attitudes toward purchasing. These findings contribute to a deeper understanding of consumer behavior and provide insights for promoting and developing eco-friendly products. This study aims to enhance comprehension of consumer behavior and the development of intentions to buy eco-friendly products.
Implementasi Bee Colony Optimization Pada Pemilihan Centroid (Klaster Pusat) Dalam Algoritma K-Means Arfiani, Ika; Yuliansyah, Herman; Suratin, Muhammad Dzikrullah
Building of Informatics, Technology and Science (BITS) Vol 3 No 4 (2022): March 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (436.104 KB) | DOI: 10.47065/bits.v3i4.1446

Abstract

Clustering is a method that is used to divide the data into several groups of parts. K-means (KM) is an algorithm that is often used in clustering, only just the result of KM often times get stuck in local optima i.e. the optimal solution (both maximum or minimal) on the candidate solution in the nearest neighbor only, not the whole of all existing solutions or what is commonly called the global optima. In this study aims to do improve the cluster determination process on the Kmeans algorithm using the Bee Colony Optimization (BCO) algorithm. BCO is an algorithm that works based on the way the bees search for food , BCO is famous for being able to escape from the local optima trap by recognizing which results are best from a series of optimal results . Combining BCO with KM begins with selecting a source of food early in random and using KM to resolve all the problems of clustering at every step BCO next and keep sources of food best in each iteration. The result of this research is that the BCOKM method has been proven to be able to solve the problem of data sharing, where the BCOKM method is able to form a good cluster, as shown by the resulting fitness value (the lowest value is 1221.53 and the highest value is 1233.28) all of which are better than the fitness value using K-means (1251.42). Likewise in terms of accuracy, where the use of BCOKM all showed better results (83.16%-83.30%) than the use of only K-means (83.09%)
Machine Translation Indonesian Bengkulu Malay Using Neural Machine Translation-LSTM Miranda, Bella Okta Sari; Yuliansyah, Herman; Biddinika, Muhammad Kunta
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 18, No 3 (2024): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.98384

Abstract

The machine translator is an application in Natural Language Processing (NLP) that focuses on translating between languages. Several previous research have used Statistical Machine Translation (SMT) with a parallel corpus of Indonesian and Bengkulu Malay totaling 3000 data points. However, SMT performs poorly when confronted with limited data and infrequent language pairs. Therefore, this study aims to build a machine translation model from Indonesian to Bengkulu Malay using an NMT approach with Long Short-Term Memory (LSTM), and to create a parallel corpus of 5261 data pairs between Indonesian and Bengkulu Malay. The research was conducted in three stages: data collection, data preprocessing, training and modeling, and evaluation. The performance of the machine translator was evaluated using the Bilingual Evaluation Understudy (BLEU). The evaluation results show that this model achieved the highest average score of 0.6016332 on BLEU-1 and the lowest average score of 0.3680788 on BLEU-4. These results indicate that considering the natural linguistic structural differences between Indonesian and Bengkulu Malay can be suggested as the best solution for translating from Indonesian to Bengkulu Malay.
Co-Authors Abdul Fadlil Adhi Prahara, Adhi Agus Setiawan, Hisyam ALYA MASITHA Anton Yudhana Apriliani, Evinda Ardiansyah, Ricy Arief Ghozali, Fanani Asti Mulasari, Surahma Ayu Laksmi Pandhita, Ayu Laksmi Bambang Sudarsono Bella Okta Sari Miranda Bidinnika, Muhammad Kunta Darmanto Darmanto Destriana, Rachmat Dewi Soyusiawaty Dewi, Ayu Intansari Donna Setiawati Eko Hari Rachmawanto Fatwa Tentama Febiyan, Rifal Firdaus, Muhammad Khysam Fitriani Mutmainah, Nur Fitriani, Isah Ghozali, Fanani Arief Habie, Khairul Fathan Hafin, Aqid Fahri Hazar, Siti Herman Herminarto Sofyan Hidayat, Muhammad Taufiq Hildayanti, Ica Kurnia Hildayanti, Ica Kurnia Ika Arfiani Imam Riadi Irfan, Syahid Al Jayawarsa, A.A. Ketut Jefree Fahana Jumaedi Nasir, Ardiansyah Khoirul Anam Dahlan Khoirunnisa, Itsnaini Irvina Kintung Prayitno, Kintung Lifa, Lifa Lina Handayani Listyaningrum, Prabandari Mahiruna, Adiyah Muhammad Abdul Aziz Muhammad Dzikrullah Suratin, Muhammad Dzikrullah Muhammad Fahmi Mubarok Nahdli Muhammad Kunta Biddinika Muhammad Ridwan Murinto Murinto Murinto Mutmainah, Nur Fitri Nafiati, Lu'lu' Nafiati, Lu’lu’ NGATIMIN, NGATIMIN Nia Ekawati, Nia Nisa Novianti, Tria Novitasari, Isda Desy Nur Rochmah Dyah Pujiastuti Pamungkas, Gilang Pamungkas, Gilang Pratama, Ridho Haikal Pratama, Wegig Putro, Aldibangun Pidekso R. Hafid Hardyanto, Settings Rachmaliany, Nur Rahmawan, Jihad Rahmawati, Rahmawati Raihan, Habib Aulia Rajunaidi, Rajunaidi Razak, Farhan Radhiansyah Rohmadi, Yusuf Eko Rusydi Umar Salji, Rinday Zildjiani Sri Winiarti Subardjo Subardjo, Subardjo Sukesi , Tri Wahyuni Sulistyawati , Sulistyawati Sulistyawati Sulistyawati Sunardi Sunardi Sunardi Surahma Asti Mulasari Tole Sutikno Tri Wahyuni Sukesi Ulumiyah, Iftitah Dwi Wahyuni Sukesi, Tri Wala, Jihan Wan Ali, Wan Nur Syamilah Yohanni Syahra Yulianto, Dinan Yulisasih, Baiq Nikum