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All Journal International Journal of Electrical and Computer Engineering Information Technology and Telematics Dinamik Jurnal Ilmiah Dinamika Teknik Bulletin of Electrical Engineering and Informatics International Journal of Advances in Intelligent Informatics Proceeding SENDI_U Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Informatika Upgris Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Jurnal Komputer Terapan IJIS - Indonesian Journal On Information System JURNAL ILMIAH INFORMATIKA JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Teknik Informatika UNIKA Santo Thomas INTECOMS: Journal of Information Technology and Computer Science J-SAKTI (Jurnal Sains Komputer dan Informatika) JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Informasi dan Komputer JURNAL MAHAJANA INFORMASI Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik JATI (Jurnal Mahasiswa Teknik Informatika) BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Intech : Information Technology Journal of UMUS Infotek : Jurnal Informatika dan Teknologi MEANS (Media Informasi Analisa dan Sistem) Journal of Applied Data Sciences Advance Sustainable Science, Engineering and Technology (ASSET) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Jurnal Rekayasa elektrika
Wiwien Hadikurniawati
Universitas Stikubank
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

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Educational Game Based Role Playing Games with Finite State Machine Method Winarno, Edy; Wijayanti, Tri Cicik; Hadikurniawati, Wiwien; EngMarkiano Solissa, Everhard
International Journal of Artificial Intelligence Research Vol 6, No 1.2 (2022)
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.2.574

Abstract

Playing games is one of the activities in great demand by the elderly, young, and children, whose use is generally only to fill spare time, get rid of boredom, and for fun. Therefore in this final project, an educational game based on Role Playing Game will be developed, which is helpful for learning by applying ten-finger typing education because, until now, learning has only been done through books. Delphi 7 is used in its manufacture. The Delphi language is a programming language that can be configured in such a way that it can work with other devices to form a control system—and apply the Finite State Machine method to process the gameplay control flow, which consists of 3 levels where the player will complete the answers for each class to be able to proceed to the next level. The results of this game can be used as learning media for children, and they can learn while playing to add knowledge in the field of typing. With these benefits, it is hoped that later games can be developed and applied among students. A game uses electronics and is entertainment in the form of multimedia that is made as attractive as possible so that players can get something that there is new satisfaction. In the Big Indonesian Dictionary, an online game is used to play goods or something that is played. The growth of the game industry is developing, especially in various types of games which include Maze Games, Board Games, Card Games, Battle Card Games, Quiz Games, Puzzle Games, Shooting Games, First Person Shooting (FPS), Side Scrolling Games, Fighting Game, Racing Game, Simulation, Strategy Game, Role Playing Game (RPG), Adventure Game, Sports Game, and Edutainment Game.
Penerapan Metode AHP dan Metode TOPSIS Dalam Menentukan Asisten Laboratorium Komputer Farih, Nia Nailil; Hadikurniawati, Wiwien
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.568

Abstract

The process of developing a decision support system for accepting computer laboratory assistants uses the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. for the criteria weighting process and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for the alternative ranking process. The results of the weighting of the criteria that have been calculated, the TOPSIS method is used for the alternative ranking process.
Penerapan Metode AHP dan Metode TOPSIS Dalam Menentukan Asisten Laboratorium Komputer Farih, Nia Nailil; Hadikurniawati, Wiwien
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.568

Abstract

The process of developing a decision support system for accepting computer laboratory assistants uses the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. for the criteria weighting process and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for the alternative ranking process. The results of the weighting of the criteria that have been calculated, the TOPSIS method is used for the alternative ranking process.
Fuzzy Inference System Diagnosa Penyakit Pada Ibu Hamil Abriyanto, Oky; Hadikurniawati, Wiwien
Jurnal Teknik Informatika UMUS Vol 4 No 01 (2022): Mei
Publisher : Universitas Muhadi Setiabudi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46772/intech.v4i01.687

Abstract

Di Indonesia kematian ibu umumnya disebabkan oleh obstetric langsung, diantanya 28% akibat perdarahan, 24% eclampsia dan sebanyak 11% akibat infeksi. Penyebab obstetric tidak langsung adalah trauma obstetric 5% dan 11% lainnya . Dari penyebab kematian ibu tersebut menunjukan bahwa eklamsia menempati urutan kedua penyebab kematian ibu pada masa kehamilan. Minimnya informasi pada ibu hamil mengenai gejala-gejala penyakit yang muncul pada masa kehamilan dan bahaya dari kehamilan resiko tinggi menyebabkan angka kematian ibu ynag tinggi pula. Penelitian ini bertujuan membuat sistem pakar yang dapat digunakan untuk mendiagnosa status resiko penyakit ibu hamil dengan menggunakan fuzzy inference system. Status resiko yag ditetapkan untuk ibu hamil yaitu preeklamsia ringan, hamil normal atau preeklamsia berat. Kriteria diagnosa menggunakan kriteria Tekanan Darah Sistolik (TDS), Tekanan Darah Diastolik (TDD), Kenaikan Berat Badan (KBB), Usia Ibu (UI). Mesin inferensi menghasilkan 81 aturan dan proses diagnosa pada ibu hamil menggunakan fuzzy dengan fungsi MIN.
IMPLEMENTASI METODE WEIGHTED MOVING AVERAGE (WMA) UNTUK PREDIKSI STOK DAGING DALAM SISTEM BERBASIS WEB Indriani, Vanyariska; Hadikurniawati, Wiwien
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 10 No 1 (2025): APRIL
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v10i1.53695

Abstract

Daging sapi merupakan sumber utama protein hewani yang sangat diminati, namun kualitasnya rentan menurun akibat kontaminasi patogen dan keterbatasan penyimpanan suhu rendah. Hal ini menjadi tantangan bagi pemasok seperti Dallas Meat di Semarang dalam mengelola stok secara efisien. Penelitian ini bertujuan untuk mengembangkan sistem prediksi stok berbasis web guna membantu pengambilan keputusan dalam pengelolaan persediaan daging. Sistem ini menerapkan metode Weighted Moving Average (WMA) dengan bobot 0,1, 0,4, dan 0,5, serta menggunakan evaluasi akurasi prediksi melalui perhitungan Mean Absolute Deviation (MAD) dan Mean Absolute Percentage Error (MAPE). Data yang digunakan adalah data stok keluar harian periode Februari 2023 hingga Januari 2024 untuk tiga jenis daging: Sirloin Lokal, Tenderloin A, dan Rump 45. Hasil prediksi menunjukkan Sirloin Lokal sebesar 215.986 kg (MAD 30.286; MAPE 13.77), Tenderloin A sebesar 214.925 kg (MAD 33.249; MAPE 18.009), dan Rump 45 sebesar 582.41 kg (MAD 127.739; MAPE 18.084). Pengujian sistem dengan metode Black Box dan validasi manual membuktikan bahwa sistem bekerja sesuai dengan fungsionalitas yang dirancang.
Pendekatan Graph-Based Community Detection dalam Social Network Analysis Jaringan Undang-Undang Republik Indonesia 2014-2024 Wibisono, Setyawan; Wahyudi, Eko Nur; Hadikurniawati, Wiwien; Lestariningsih, Endang; Cahyono, Taufik Dwi
Dinamik Vol 30 No 2 (2025)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v30i2.10218

Abstract

This study evaluates the performance of three community detection algorithms—Leiden, Infomap, and Label Propagation—on the legal network of the Republic of Indonesia spanning the period 2014–2024. The network consists of 679 nodes and 2,295 edges, constructed based on citation relationships among regulations. The evaluation employs four network topology metrics: modularity, coverage, conductance, and inter-cluster density. Results show that the Leiden algorithm achieves the highest modularity score (0.522991), indicating the formation of communities with strong internal density. Additionally, it yields the lowest conductance value (0.302455), suggesting relatively well-isolated communities. In contrast, the Label Propagation algorithm produces the highest coverage (0.835294) and inter-cluster density (0.542331), but with a lower modularity (0.431583), reflecting the formation of large communities with less distinct boundaries. Infomap exhibits moderate performance, with a modularity score of 0.508406 and inter-cluster density of 0.420803, yet records a relatively high conductance (0.410409). Network visualizations reveal three major communities for each algorithm, representing thematic clusters such as institutional governance, constitutional law, and public finance. Overall, the Leiden algorithm is considered the most optimal for detecting modular, stable, and thematically coherent community structures within the complex and interrelated network of Indonesian laws.
Sistem Pakar Diagnosa Penyakit Sapi Menggunakan Metode Case Based Reasoning (CBR) Gunawan, Doni Triyoga; Hadikurniawati, Wiwien
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 8 No. 1 : Tahun 2023
Publisher : LPPM UNIKA Santo Thomas

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Abstract

Hewan ternak merupakan salah satu potensi besar bagi Indonesia. Di berbagai daerah terutama pedesaan banyak masyarakat yang memiliki hewan ternak, salah satunya adalah sapi. Sapi banyak dipilih karena pakan yang mudah untuk didapatkan, pemanfaatan daging dan kotoran, susu, serta harga jual yang relatif tinggi. Namun demikian, meskipun banyak keuntungan yang akan didapatkan, para peternak sapi juga harus memastikan kesehatan sapi dengan lebih baik. Hal ini karena saat ini banyak kasus penyakit pada hewan ternak, baik yang dapat menular maupun tidak. Berdasarkan hal tersebut, peneliti ingin membangun sebuah sistem pakar yang dapat digunakan untuk mendiagnosa penyakit sapi berdasarkan pemilihan gejala guna mengetahui penanganan untuk penyakit tersebut. Sistem pakar yang akan dibangun menggunakan metode Case Based Reasoning (CBR) yang diimplementasikan pada sebuah website. Case Based Reasoning mengambil keputusan untuk kasus baru berdasarkan solusi kasus-kasus lampau yang pernah terjadi. Berdasarkan hasil confusion matrix terhadap hasil Sistem Pakar Diagnosa Penyakit Sapi Menggunakan Metode Case Based Reasoning (CBR) dapat ditentukan accuracy sebesar 92,11% dan misclassification (Error) rate sebesar 7,89%. Hasil akurasi dan error rate dari perhitungan ini menunjukkan bahwa metode Metode Case Based Reasoning (CBR) dapat digunakan untuk Diagnosa Penyakit Sapi dengan kualitas akurasi yang sangat baik.
AHP-COPRAS untuk Pemeringkatan Ketersediaan Fasilitas Kesehatan di Indonesia Wibisono, Setyawan; Hadikurniawati, Wiwien; Almin, Imam Husni Al
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 8 No. 1 : Tahun 2023
Publisher : LPPM UNIKA Santo Thomas

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Abstract

In handling Covid-19, health resources are one of the factors that play a very important role in reducing the death rate. For this reason, we offer a study on the topic of ranking the availability of health resources in handling the Covid-19 pandemic in provinces in Indonesia using the AHP (Analytical Hierarchy Process) and COPRAS (Complex Proportional Assessment) hybrid methods. The use of the pairwise comparison matrix as a method for testing the validity of the weights for each criterion produces a weight value of 0.363760164 for the criteria for the number of doctors per population and the criteria for the number of nurses per population, a weight value of 0.1588353 for beds per 1000 people, a weight value of 0, 075333696 for the number of hospitals per population, and a weight value of 0.038310676 when going to the hospital. This ranking system places DKI Jakarta first with a utility value of 100%, while the second rank is the Special Region of Yogyakarta with a utility value of 63.59. There is a considerable gap compared to other provinces in terms of the availability of health resources in handling the Covid-19 pandemic. The availability of health facilities in DKI Jakarta is quite far when compared to other provinces in terms of the availability of health resources in handling the Covid-19 pandemic. DKI Jakarta remains the area with the most excellent health facilities.
Social Network Analysis untuk Pemeringkatan Popularitas Makanan Cepat Saji Menggunakan Metode PSI Wibisono, Setyawan; Hadikurniawati, Wiwien; Lestariningsih, Endang; Wahyudi, Eko Nur; Cahyono, Taufiq Dwi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 9 No. 1 : Tahun 2024
Publisher : LPPM UNIKA Santo Thomas

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Abstract

This research aims to rank the popularity of fast-food brands in Indonesia based on Twitter conversations using the Preference Selection Index (PSI) method and validate the results with COPRAS and AHP-COPRAS methods. Data were obtained by crawling Twitter from April 21, 2023, to April 28, 2023. Seven well-known brands, such as KFC, MCD, PizzaHut, Hokben, Solaria, JCo, and Richeese, were evaluated as alternatives using eight criteria through Social Network Analysis. The criteria were categorized into advantageous and disadvantageous, and preference values were calculated using PSI. After normalizing the decision matrix, calculations were performed for preference variation and overall preference values. Alternatives were ranked based on the preference selection index, and the results were validated with COPRAS and AHP-COPRAS. The results revealed significant differences in rankings between the PSI method and others. The alternative that received the highest rank changed from A2 (COPRAS and AHP-COPRAS) to A3 (PSI). This emphasizes the importance of choosing the right method for brand ranking, as it can influence decision-making. Method validation through result comparison with other methods provides additional insights into the reliability of the PSI method in the context of this research.
Optimalisasi Model Klasifikasi Diabetes Menggunakan Ensemble Learning Adaboost, Gradient Boosting, dan XGBoost Wibisono, Setyawan; Hadikurniawati, Wiwien; Yulianton, Heribertus; Lestariningsih, Endang; Cahyono, Taufiq Dwi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 9 No. 2 : Tahun 2024
Publisher : LPPM UNIKA Santo Thomas

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Abstract

Diabetes mellitus adalah penyakit kronis yang memengaruhi jutaan orang secara global dan membutuhkan metode diagnosis dini untuk mencegah komplikasi. Penelitian ini bertujuan untuk mengoptimalkan prediksi diabetes dengan membandingkan tiga metode ensemble learning: AdaBoost, Gradient Boosting, dan XGBoost. Dataset yang digunakan adalah Diabetes Health Indicators, yang menggabungkan indikator kesehatan seperti tekanan darah, kolesterol, dan kebiasaan gaya hidup. Tahapan penelitian meliputi pemrosesan data, pengembangan model, serta eval_uasi performa menggunakan metrik akurasi, presisi, recall, F1-score, dan AUC (Area Under the Curve). Hasil menunjukkan bahwa Gradient Boosting unggul dalam akurasi dan AUC, menandakan kemampuan yang lebih baik dalam mendeteksi diabetes secara konsisten dibandingkan dengan dua metode lainnya. AdaBoost memperlihatkan keseimbangan yang baik antara presisi dan recall, menjadikannya cocok untuk skenario yang memerlukan pengendalian kesalahan positif dan negatif secara proporsional. Sementara itu, XGBoost menawarkan efisiensi pemrosesan yang optimal dengan performa yang kompetitif. Gradient Boosting direkomendasikan untuk aplikasi klinis yang membutuhkan akurasi tinggi, sedangkan AdaBoost dapat menjadi alternatif ketika keseimbangan prediksi menjadi prioritas. Penelitian ini berkontribusi dalam pengembangan alat prediksi diabetes yang lebih akurat, efektif, dan dapat diterapkan di sektor kesehatan untuk mendukung upaya deteksi dini.
Co-Authors Abriyanto, Oky Ade Iriani Adhi Mulya, Ananda Agung Prihandono Aji Supriyanto Almin, Imam Husni Al Alviani Setya Yuniantika Andiany, Fairuz Eka Andiany, Fairuz Eka Angga Dewandono Anindita Septiarini, Anindita Anindita Septirini Anwar, Muchamad Taufiq Arief Jananto Arthur, Christian Brian Datuesa, Egga Cahyono, Taufik Dwi Danny Manongga Eddy Nurraharjo Edy Winarno Eka Andiany, Fairuz Eka Ardhianto Eko Nur Wahyudi Endang Lestariningsih EngMarkiano Solissa, Everhard Erika Dewi Anggraini Fadhilah, Lailatul Farih, Nia Nailil Fatkhul Amin fatkhurrizqi, Maolana Galih Setiadi Gunawan, Doni Triyoga Gusti Ari Prasetyo Hamdani Hamdani Hamdani Hamdani Heribertus Yulianton Herny Februariyanti Heru Yudia Setyo Anggoro Hindriyanto Dwi Purnomo Huda, Azis Fatchul Imam Husni Al Amin Indriani, Vanyariska Irfak Lahumu Darojat Irwan Sembiring Ivannofick Adha Nugraha Khabib Mustofa Kristoko Dwi Hartomo M Arip Islahudin Mohammad Faisal Fahrul Monica Yoshe Titimeidara Muchamad Maskhur Muji Sukur Putra Ramdani, Aditya Rudi Hariyanto Sari, Lenny Estika Sarita Yuniarti Hanum Setyawan Wibisono Setyawan Wibisono Setyawan Wibisono Sidiq Eko Budiharjo Suci ananda sari Sutarto Wijono Taufiq Dwi Cahyono Tegar Prabowo, Satria Veronica Lusiana Wijayanti, Tri Cicik Zakaria, Franky Zuly Budiarso