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All Journal Jurnal Ilmiah KOMPUTASI Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL INFORMATIKA Journal of Information System, Applied, Management, Accounting and Research Jurnal Inti Talafa : Jurnal Teknik Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Indonesian Journal of Business Intelligence (IJUBI) bit-Tech Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JISA (Jurnal Informatika dan Sains) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Jurnal Ilmiah Wahana Pendidikan Bulletin of Information Technology (BIT) International Journal Software Engineering and Computer Science (IJSECS) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science Formosa Journal of Computer and Information Science Jurnal Lentera Pengabdian Jurnal Ilmiah Multidisiplin Indonesia Jurnal Elektronika dan Teknik Informatika Terapan International Journal of Applied Research and Sustainable Sciences (IJARSS) International Journal of Sustainable Applied Sciences (IJSAS) VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian JPM MOCCI : Jurnal Pengabdian Masyarakat Ekonomi, Sosial Sains dan Sosial Humaniora, Koperasi, dan Kewirausahaan SAINTEK International Journal of Integrated Science and Technology Jurnal Indonesia : Manajemen Informatika dan Komunikasi SISFOTENIKA Welfare: Jurnal Pengabdian Masyarakat
Wahyu Hadikristanto
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Social Sciences Other

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Optimasi Algoritma K- Nearest Neighbor Berbasis Particle Swarm Optimization Untuk Meningkatkan Kebutuhan Barang Taofik Safrudin; Gatot Tri Pranoto; Wahyu Hadikristanto
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.724

Abstract

Abstract− The application of the K-Nearest Neighbor algorithm can be implemented where the results also show a new insight, namely predicting the level of need. With a ratio of 90%:10%, where there are 50 data objects tested to predict the level of needs in 2 groups, namely low needs or high needs. The results of the model scenario show that there are 2 objects in the Low needs group and 1 object in the High needs group. In evaluating this model, it was obtained from 10 fold Cross Validation that the Accuracy value was 82%, then the Precision value was 87.50%, and the Recall value was 80%. By measuring the performance of the model with Cross Validation, the resulting accuracy has a standard value or standard deviation, which aims to see the distance between the average accuracy and the accuracy of each experiment. While the Test Results using PSO In the evaluation of this model, it is obtained from 10 fold Cross Validation the Accuracy value is 100%, then the Precision value is 100%, and the Recall value is 100%, the test results have increased significantly
Accuracy Comparison of Support Vector Machine, Random Forest, and K-Nearest Neighbors for Sundanese Speech Classification Laela Nur Rohmah; Abdul Halim Anshor; Wahyu Hadikristanto
JISA(Jurnal Informatika dan Sains) Vol 9, No 1 (2026): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v9i1.2757

Abstract

To support the preservation of the Sundanese language, speech recognition systems based on machine learning canbe developed. This study aims to evaluate and compare the classification performance of Support Vector Machine, Random Forest, and K-Nearest Neighbors which represent margin-based, ensemble-based, and distance-based classification approaches that have been widely applied in speech classification tasks. A secondary dataset consisting of 100 voice recordings was utilized in this research. The study followed the Knowledge Discovery in Database framework, which encompasses data selection, preprocesing, transformation, data mining, and evaluation phases. Feature extraction was performed using the Mel-Frequecy Cepstral Coefficients method. Experimental result demonstrate that the Random Foret algorithm achieved superior performance, reaching 100% accuracy and an Area Under Curve (AUC) of 100%. Meanwhile, K-Nearest Neighbors achieved 87% accuracy with an AUC of 100%, and Support Vector Machine yielded the lowest performance with  67% accuracy and an AUC of 72.89%. Although Random Forest achieved the highest metrics, futher research is required as a perfect 100% score raises concerns regarding model overfitting. To address this issue, utilizing a large dataset is recommended for future studies. Consequently, K-Nearest Neighbors can be considered a more reliable choice in this study, demonstrating robust and stable performance for MFCC based speech classification on smaller dataset.
SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN PENDAKIAN GUNUNG TERBAIK DI JAWA TENGAH MENGGUNAKAN METODE SAW (SIMPLE ADDITIVE WEIGHTING) Wahyu Hadikristanto; Gatot Tri Pranoto
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 2 (2023): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i2.3557

Abstract

The level of interest in mountain climbing activities has increased significantly, this is inseparable from the development of social media technology which exposes the charm of each mountain itself, so as to attract interest in climbing from various groups, both beginners and experienced. Because each climber has their own characteristics and needs and each mountain also has its own character, so that it will affect each climbing destination, prospective climbers must be able to determine which mountain will be chosen as the best mountain in Central Java province to be chosen. as a climbing location. This research uses secondary data, the alternative to be compared is a list of mountains in Central Java province with several criteria to be used. The method for processing data is the Simple Additive Weighting (SAW) method. This method is used to find the weighted sum and rating of each alternative and all attributes. The results of this study can be a reference for climbers in determining the best mountain to be used as a climbing location in Central Java province.
Klasifikasi Status Gizi Balita Menggunakan Algoritma KNN pada Sistem Informasi Posyandu Berbasis Web: Classification of Toddler Nutritional Status Using the KNN Algorithm in a Posyandu Information System Tiara Putri; Wahyu Hadikristanto
SISFOTENIKA Vol. 16 No. 2 (2026): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v16i2.655

Abstract

Posyandu memiliki peran penting dalam memantau pertumbuhan dan perkembangan balita, khususnya dalam penentuan status gizi. Namun, proses pencatatan dan penilaian status gizi yang masih dilakukan secara manual dapat menyebabkan keterlambatan pengolahan data dan meningkatkan risiko kesalahan. Penelitian ini bertujuan untuk merancang dan membangun Sistem Informasi Posyandu berbasis web yang terintegrasi dengan algoritma K-Nearest Neighbor (KNN) untuk membantu klasifikasi status gizi balita secara otomatis. Sistem dikembangkan menggunakan metode Waterfall yang meliputi tahap analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Algoritma KNN diterapkan menggunakan atribut umur, berat badan, tinggi badan, lingkar lengan atas (LiLA), dan lingkar kepala. Dataset yang digunakan berjumlah 340 data balita yang dibagi menjadi 272 data training (80%) dan 68 data testing (20%). Hasil pengujian menggunakan confusion matrix menunjukkan bahwa algoritma KNN memperoleh tingkat akurasi sebesar 85,29%. Sistem yang dikembangkan mampu mengelola data balita, melakukan klasifikasi status gizi secara otomatis, serta menghasilkan informasi yang lebih cepat dan terstruktur dibandingkan proses manual. Hasil penelitian menunjukkan bahwa integrasi algoritma KNN pada Sistem Informasi Posyandu dapat mendukung kader Posyandu dalam pemantauan status gizi balita secara lebih efektif dan efisien.
Integrating Kaizen Culture and Occupational Safety and Health in Enhancing Employee Productivity: A Study in the Precision Manufacturing Industry Muhamad Baharudin; Fibi Eko Putra; Wahyu Hadikristanto
Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID) Vol. 5 No. 07 (2026): Jurnal Ilmiah Multidisplin Indonesia (JIM-ID), 2026
Publisher : Sean Institute

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

Abstract

The precision component manufacturing industry faces a dual challenge in enhancing productivity while maintaining occupational safety, given that production processes involve machinery and high-risk activities. This study aims to analyze the effect of implementing kaizen culture and Occupational Safety and Health (OSH) on employee productivity, both partially and simultaneously, within the F-Line Department of PT XYZ Indonesia, a manufacturer of spinnerettes for the synthetic fiber industry. A quantitative approach with an explanatory design was applied to 64 respondents selected through saturated sampling technique. Data were collected using a five-point Likert-scale questionnaire, transformed into interval scale data using the Method of Successive Interval (MSI), and subsequently analyzed using multiple linear regression with the assistance of SPSS version 25.0, following validity, reliability, and classical assumption tests—including normality, multicollinearity, and heteroscedasticity. The results indicate that kaizen culture has a positive and significant effect on employee productivity (t = 6.456; p = 0.000), as does OSH (t = 4.642; p = 0.000). Simultaneous testing reveals that both variables significantly affect employee productivity (F = 214.236; p = 0.000), with a coefficient of determination (R2) of 0.875, indicating that 87.5% of the variation in employee productivity is explained by these two variables. Kaizen culture demonstrates a relatively more dominant contribution than OSH. These findings suggest that kaizen culture and OSH are complementary in supporting operational performance. Accordingly, precision manufacturing companies are advised to integrate both programs synergistically—rather than as standalone initiatives—to optimize employee productivity while continuously mitigating the risk of workplace accidents.
Pengelompokan Untuk Penjualan Obat Dengan Menggunakan Algoritma K-Means Holwati; Edi Widodo; Wahyu Hadikristanto
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.848

Abstract

Drug grouping is an arrangement that adjusts to the flow of placement or drug layout is more suitable for standard processes. Utilization of existing data through the clustering method approach can be applied to analyze in grouping drug data on data availability and inventory in warehouses so as to provide knowledge and information. The clustering method is processed using the K-Means algorithm where the results also show a new knowledge, namely the grouping of drug data based on 2 clusters. Cluster 1 is a high need category with availability of 71 out of 100 availability categories based on the amount of drug data tested, then cluster 2 is a drug category with moderate or low availability, namely 29 out of 100 availability categories based on the number of drug data tested. Tests using Rapid Miner tools can also produce similar insights, namely each cluster has cluster group members according to manual calculations such as Cluster_0 in Rapid Miner has 72 cluster members representing the Medium cluster, Cluster_1 has 72 cluster group members as high cluster representations, and Cluster_2 has 3 cluster members corresponding to low representation.
Perbandingan Metode Decision Tree dan Random Forest Dalam Prediksi Curah Hujan (Studi Kasus: Curah Hujan Kota Bogor Tahun 2022 – 2023) Wahyu Hadikristanto; Riska Puspa Anggraeni Putri
Jurnal SIGMA Vol 15 No 1 (2024): Juni 2024
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v15i1.7323

Abstract

Curah hujan merupakan parameter penting dalam bidang lingkungan dan pertanian, sehingga diperlukan metode prediksi yang akurat. Penelitian ini membandingkan kinerja metode Decision Tree dan Random Forest dalam memprediksi curah hujan menggunakan data historis cuaca yang mencakup suhu, kelembaban, dan variabel terkait lainnya. Data terlebih dahulu diproses untuk mengatasi duplikasi dan nilai ekstrem, kemudian dibagi menjadi data pelatihan dan pengujian. Hasil evaluasi menunjukkan bahwa metode Decision Tree menghasilkan akurasi 80,82%, presisi 87,88%, dan recall 90,62%, sedangkan metode Random Forest memperoleh akurasi 87,67%, presisi 88,73%, dan recall 98,44%. Perbandingan hasil menunjukkan bahwa Random Forest memiliki kinerja yang lebih baik terutama dalam hal akurasi dan recall, sehingga lebih efektif dalam mengidentifikasi hari hujan. Meskipun demikian, pemilihan metode tetap perlu disesuaikan dengan kebutuhan aplikasi. Penelitian ini memberikan rekomendasi metode yang tepat untuk prediksi curah hujan.
IMPEMENTASI CONTENT MODERATION DALAM SOCIAL MEDIA INSTAGRAM UNTUK DETEKSI CYBERBULLYING DENGAN MACHINE LEARNING BERBASIS CLOUD. Wahyu Hadikristanto
Indonesian Journal of Business Intelligence (IJUBI) Vol 5 No 2 (2022): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v5i2.2804

Abstract

Media sosial adalah platform di internet yang memungkinkan pengguna untuk berkomunikasi, berbagi informasi, dan terhubung dengan orang lain. Instagram adalah salah satu media sosial yang paling banyak digunakan di seluruh dunia. Cyberbullying adalah tindakan menyiksa, mengancam, atau menyiksa seseorang secara online. Machine learning adalah teknologi yang memungkinkan komputer untuk mempelajari danmengembangkan kemampuan tanpa diberi instruksi secara eksplisit. Machine learning dapat digunakan dalam berbagai bidang, termasuk content moderation untuk mencegah cyberbullying. Secara keseluruhan, penelitian tentang content moderation dengan machine learning berbasis cloud cukup efisien, mengingat nilai akurasi yang diperoleh sebesar 85%.
IMPLEMENTASI COBIT 2019 PADA TATA KELOLA TEKNOLOGI INFORMASI DI UNIVERSITAS Fatchan Fatchan; Andri Firmansyah; Sanudin Sanudin; Wahyu Hadikristanto
INTI TALAFA Vol. 18 No. 1 (2026): Vol 18 No 1 Tahun 2026
Publisher : Program Studi Teknik Informatika Universitas Muhammadiyah Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32534/int.v18i1.8532

Abstract

Perkembangan teknologi informasi (TI) di lingkungan universitas menuntut pengelolaan yang efektif untuk mendukung layanan akademik dan administratif. Kerangka kerja COBIT 2019 dikenal sebagai standar tata kelola TI yang komprehensif dan dapat mengukur kapabilitas proses berdasarkan design factors dan komponen governance. Penelitian ini menelaah implementasi COBIT 2019 di institusi pendidikan tinggi melalui tinjauan literatur dan studi kasus empiris. Metode penelitian melibatkan penelusuran dan sintesis artikel ilmiah yang relevan dari basis data terindeks internasional dan lokal. Hasil analisis menunjukkan bahwa penerapan COBIT 2019 mampu memberikan gambaran tingkat kematangan proses TI, mengidentifikasi gap, dan menyusun rekomendasi perbaikan. Namun, masih terdapat tantangan berupa dukungan manajemen yang belum optimal, keterbatasan sumber daya manusia, dan integrasi sistem yang kompleks. Penelitian ini merekomendasikan tindakan perbaikan strategis serta arah riset lanjutan yang dapat meningkatkan tata kelola TI di lingkungan universitas
PENINGKATAN KESADARAN LINGKUNGAN MELALUI PENYULUHAN DAN SOSIALISASI KEPADA PEDAGANG PASAR SERANG, KABUPATEN BEKASI: PENINGKATAN KESADARAN LINGKUNGAN MELALUI PENYULUHAN DAN SOSIALISASI KEPADA PEDAGANG PASAR SERANG, KABUPATEN BEKASI Dodit Ardi Atma; wahyu hadikristanto
Jurnal Pelita Pengabdian Vol. 3 No. 1 (2025): Januari 2025
Publisher : DPPM Universitas Pelita Bangsa

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

Abstract

Pasar tradisional memiliki peran strategis sebagai pusat ekonomi masyarakat, namun juga menjadi salah satu sumber utama penghasil sampah. Pengelolaan sampah yang tidak memadai di pasar tradisional, seperti di Pasar Serang, Kecamatan Cikarang Selatan, Kabupaten Bekasi, menyebabkan pencemaran lingkungan, gangguan estetika, dan risiko kesehatan masyarakat. Studi ini menemukan bahwa pengelolaan sampah di Pasar Serang masih belum optimal, dengan sampah yang menumpuk dan tidak terpilah dengan baik. Masalah ini semakin diperparah dengan minimnya fasilitas pendukung, seperti tempat sampah terpisah untuk sampah organik dan anorganik.Edukasi kepada pedagang dilakukan melalui diskusi dan sosialisasi yang menekankan pentingnya pemilahan sampah, serta manfaat kebersihan pasar terhadap kesehatan, estetika, dan kenyamanan pengunjung. Sosialisasi ini disampaikan dengan metode tatap muka untuk memastikan komunikasi yang lebih efektif dan personal. Hasil penelitian menunjukkan bahwa pendekatan ini mampu meningkatkan kesadaran pedagang terhadap pengelolaan sampah, dengan banyak pedagang mulai mempraktikkan pemilahan sampah di tempat jualan mereka. Namun, terdapat tantangan seperti kebiasaan pedagang yang belum terbiasa memisahkan sampah dan keterbatasan waktu mereka. Oleh karena itu, diperlukan dukungan lebih lanjut dari pemerintah, pengelola pasar, dan masyarakat untuk menyediakan fasilitas yang memadai, kebijakan yang tegas, serta program kebersihan berkelanjutan.
Co-Authors ., Sapardi A. Reza Baehaqa Jamroni Jamroni Aas Novitasari Abdul Halim Anshor Abdul Hasyim Abimanyu, Aldo Anggito Achmad Firmansyah Putra Adrianna Syariefur Rakhmat Adriansyah, Putri Nabila Adinda Agung Nugroho Ahmad Gunawan Ahmad Turmudi Zy Ahmad Zy Ahmad, Asyari Alfarizi, Muhammad Farhan Ali Nurdiansyah Ananto Tri Sasongko Andika, Sophian Andri Firmansyah Anggara, Bastian Anisa Anisa Anisa Rahmawati Anshor , Abdul Halim Ansor, Abdul Halim Ariandi, Sheva Rizky Arvita Emarilis Intani Aswan S Sunge Atthoriq, Syaifullah Ayu Fitriyani Badruzzaman, Aceng Dahyoung Yenuargo Dichi Setiawan Diki Febriani Dodit Ardi Atma Dodit Ardiatma Doni, Muhamad Edi Junianto Edi Widodo Edora Edora Edora Edora, Edora Edy Widodo Eko Budiarto Eko Budiarto Ermanto Fadlurrohman, Muhammad Shiddiq Fajar Arief Rachman Fatchan Fatchan Fatchan, Muhammad Fauzi Ahmad Muda Ferdyana Eka Prasetya Fibi Eko Putra Fitri Rezeki Gatot Tri Pranoto Hanif, Sa’ad Khairudin Herdyanto, Febro Herol, Herol Holwati Ikmal Riyan Firmansyah Imam Nasai2 Indradewa, Rhian Intan Sari Rahayu Irfan Afriantoro Irfan Afriantoro Ismasari Ismasari Karsito, Karsito Keswanto Kumara Davin Valerian Kurniadi, Nanang Tedi Laela Nur Rohmah Laki, Abraham Leo Contantinus Meze Listanto, Firgiawan Maulida Ramadhan Mico Giovanni Dermawan Miharja, Muhammad Najamuddin Dwi Muhamad Baharudin Muhamad Fatchan Muhammad Arilda Aprilianto Muhammad Fatchan Muhammad Makmun Effendi Muhammad Suprayogi2 Nanang Tedi Kurniadi Nanang Tedi Kurniadi Naufal Muyassar Nawangsih, Ismasari Nita Paramita Njai Njai Nur Azizah Nurhadi Surojudin Nurul Ariffaeni Islami Oktavianto, Rainal Zulian Permana , Indra Prasetyo Prasetyo Pratama, Galang Rintang Widya Prayoga, Dimas Purdianto Purdianto Purnama Sakhrial Purwanto Purwanto Purwanto Putri N.A, Anindya Rahmawati, Shinta Melliana Rahmawati Rasmiati Nur Aeni Retno Purwani Setyaningrum Riska Puspa Anggraeni Putri Risky Bambang Sutrisna Rizky Igel Herisaputra romanuddin, ahmad Rosyati Adelia S Suprapto Sandi Salvan N N Sanudin Sanudin Sanudin Satria Permana, Muhammad Safri Setiawan, Dani Yuda Dwi Siska Wulandari, Siska Suderajat, Agung Sufajar, Sufajar Sufajar, Suprapto Suhardian Suhardian Suherman Suherman Suherman Sunaryati , Titin Sunita Dasman Sya syah Apriliyani Syach, Ridwan Taofik Safrudin Taufik Hidayat Tiani Ayu Lestari Tiara Deswara Pungkas Tiara Putri Tri Ngudi Wiyatno Turmudi Zy, Ahmad Vidya Anis Fitri Yahya, Adiba Yahya, Adibah Yoga Religia Yusup, Diana