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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Nasional Komputasi dan Teknologi Informasi Innovation in Research of Informatics (INNOVATICS) Jurnal Kolaboratif Sains PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Jurnal Sains, Teknologi dan Rekayasa (SAINTESA) Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Penelitian dan Pengabdian Masyarakat IPSIKOM Scientific Journal of Informatics Karya Nyata: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Dan Sistem Informasi Bisnis
ALAM
Universitas Cipasung Tasikmalaya
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Rancang Bangun Sistem Prediksi Varietas Padi Yang Cocok Dengan Lahan Menggunakan Metode Data Mining Algoritma C4.5 Dewanto Rosian Adhy; Alam
Jurnal Ilmiah Sains, Teknologi dan Rekayasa Vol 1 No 1 (2021): Oktober 2021
Publisher : P3M STT YBSI Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (791.506 KB)

Abstract

Kebutuhan pangan di Indonesia terus meningkat setiap tahunnya mengikuti pesatnya pertumbuhan penduduk. Untuk mengatasi masalah tersebut, produksi beras juga harus ditingkatkan. Namun, saat ini produk pertanian terkadang tidak menentu karena perubahan cuaca yang tidak terduga. Pemilihan varietas padi yang akan ditanam juga harus lebih selektif untuk menghindari resiko gagal panen dan penurunan hasil. Penelitian ini bertujuan untuk membantu petani di Kabupaten Tasikmalaya dalam menentukan varietas padi yang cocok dengan kondisi tanah dan cuaca. Penelitian ini menggunakan metode penelitian kuantitatif. Algoritma Data Mining yang digunakan dalam penelitian ini adalah algoritma Data Mining Decission Tree (C4.5).
Comparison Of The C.45 And Naive Bayes Algorithms To Predict Diabetes Alam, Alam; Alana, Divi Adiffia Freza; Juliane, Christina
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12998

Abstract

Diabetes mellitus is an urgent global health problem and has a major impact on people around the world. This disease is characterized by high levels of sugar (glucose) in the blood due to disturbances in the production or use of the hormone insulin by the body. This study aims to carry out accurate early detection of diabetics so that they can be treated as soon as possible to reduce the risk of death and to compare the two algorithms that have the best level of accuracy. The algorithms used in this study are the C4.5 and Naïve Bayes Decision Tree Algorithms. The results of the experiments carried out in this study the Decision Tree Algorithm C4.5 and Naïve Bayes can be used in modeling the early detection of diabetes. The highest average accuracy results were obtained at 90.835% using the Decision Tree C4.5 Algorithm. As for the Naïve Bayes Algorithm, an average accuracy rate of 90.745% is obtained. The pruning process was carried out using the Decision Tree Algorithm C4.5, the accuracy performance increased to 91.30%. There were 18 patterns or rules for the early detection of diabetics from the built model. The determination of attributes, the number of attribute dimensions, and the number of samples greatly affect the performance of the model built.
PEMANFAATAN DIGITALISASI DALAM BERWIRAUSAHA DI ERA INDUSTRI 4.0 BAGI USAHA MIKRO KECIL DAN MENENGAH (UMKM) Febriani SM, N Nelis; Sudiarti, Sri; Ghurroh Setyoningrum, Nuk; Aini Syifa, Raisa Hilia; Ardhiansyah; Alam
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 3 No. 1 (2025): Februari
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v3i1.1788

Abstract

Era Industri 4.0 membawa transformasi besar dalam berbagai sektor, termasuk Usaha Mikro, Kecil, dan Menengah (UMKM). Digitalisasi menjadi peluang strategis bagi UMKM untuk meningkatkan daya saing di tengah perubahan teknologi yang pesat. Pemanfaatan teknologi digital, seperti e-commerce, media sosial, dan platform berbasis aplikasi, memungkinkan UMKM memperluas jangkauan pasar, meningkatkan efisiensi operasional, serta menciptakan inovasi produk dan layanan. Tujuan dilaksanakan kegiatan pengabdian ini untuk meningkatkan kapasitas digitalisasi pada Usaha Mikro, Kecil, dan Menengah (UMKM) dalam menghadapi tantangan dan peluang di era Industri 4.0. Melalui sosialisasi dan pendampingan, kegiatan ini membantu pelaku UMKM memahami dan memanfaatkan teknologi digital, seperti platform e-commerce, media sosial, dan aplikasi manajemen bisnis, untuk mendukung operasional dan pemasaran usaha mereka. Kegiatan ini dilaksanakan dengan sosialisasi interaktif, diskusi peserta, dan praktik langsung yang disesuaikan dengan kebutuhan spesifik UMKM. Hasilnya menunjukkan peningkatan pemahaman peserta tentang pentingnya digitalisasi, kemampuan menggunakan teknologi digital, serta strategi pemasaran berbasis digital. Dampak langsung yang dirasakan adalah meningkatnya jangkauan pasar, efisiensi operasional, dan daya saing UMKM di tengah perubahan ekonomi yang semakin terhubung secara digital. Kegiatan ini diharapkan dapat menjadi model pemberdayaan UMKM yang relevan di era Industri 4.0.
The Impact of Linguistic Features on Emotion Detection in Social Media Texts Setyoningrum, Nuk Ghurroh; Febriani SM, Neng Nelis; Alam, Alam; Nurdin, Arif Muhamad; Nursamsi, Dede Rizal; Lodana, Mae B
Innovation in Research of Informatics (Innovatics) Vol 7, No 1 (2025): March 2025
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v7i1.13221

Abstract

Emotions are an important aspect of human life, and scientific theories on emotions have been widely developed in various research fields such as philosophy, psychology, and neuroscience. In human-computer interaction, understanding emotions is also very important. Detecting emotions not only enables better decision-making, but is also useful in various contexts such as business, politics, and mental health. The focus on identifying emotions in text arises because emotions are often implied without explicit words. Through the analysis of grammar and sentence structure, text mining techniques enable the extraction of sentiments and emotions. Detecting and identifying emotions in text is important because it can be applied in a variety of fields, including decision-making, prediction of human emotions, product assessment, analysis of political support, and identification of depression. Text as textual data is an important source of information due to its ability to convey human emotions. In this research, emotion detection uses the Naïve Bayes method, with attribute weighting to improve accuracy using count vector. This classification approach allows grouping text into six emotion categories: happy, sad, fear, love, shock, and anger. The Naïve Bayes method was chosen for its reliability in classifying data based on conditional probabilities. Thus, this research provides a deeper understanding of understanding and managing emotions in the context of social media. The data classification results yield precision, recall, F1-Measure, and accuracy values.
Pendampingan Pengembangan Ekonomi Kreatif Berbasis Potensi Lokal di Desa Wisata Sudiarti, Sri; Rusliana, Nanang; Setyoningrum, Nuk Gurroh; Alam, Alam; Syfa, Raisa Hillia Aini
Jurnal Penelitian dan Pengabdian Masyarakat Vol. 3 No. 3 (2025): August 2025
Publisher : Yayasan Pondok Pesantren Sunan Bonang Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61231/jp2m.v3i3.379

Abstract

This community mentoring activity aims to identify local potential that can be developed into creative economic products and formulate development strategies appropriate to the characteristics of tourist villages. The mentoring approach uses socialization and talk shows. The mentoring results indicate that creative economy development based on local potential, such as arts and crafts, traditional culinary arts, local culture, and ecotourism, can increase community income and strengthen local identity. Recommended development strategies include increasing human resource capacity, collaborating with various stakeholders, utilizing digital technology for promotion, and strengthening village institutions. In conclusion, developing a creative economy based on local potential requires a participatory, sustainable, and adaptive approach to the dynamics of the tourism market
Augmentasi Data Audio Menggunakan Metode Time Shifting dan Random Gain Alam Alam; Nuk Ghurroh Setyoningrum; Robby Maududy; Miftahudin Miftahudin
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 3 (2025): Juni 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i3.9062

Abstract

Abstrak - Penelitian ini membahas penerapan teknik augmentasi data audio sebagai solusi untuk mengatasi keterbatasan jumlah dataset dalam pengembangan model pembelajaran mesin pada pengenalan dan pemrosesan sinyal audio. Augmentasi data dilakukan untuk memperluas dan memperkaya variasi data tanpa perlu mengumpulkan data tambahan, dengan tujuan meningkatkan performa model. Dua metode augmentasi yang digunakan dalam penelitian ini adalah time shifting dan random gain. Time shifting dilakukan dengan menggeser sinyal audio sejauh 0,2 detik untuk menjaga kealamian suara, sementara random gain mengatur volume audio secara acak dalam rentang 0,5 hingga 1,5. Dataset yang digunakan berupa pelafalan 28 huruf hijaiyah dengan total 364 data audio dari sumber terbuka di Kaggle. Hasil augmentasi menunjukkan peningkatan variasi sinyal audio tanpa mengubah karakteristik inti suara, yang diharapkan dapat meningkatkan akurasi dan ketahanan model dalam menghadapi variasi input audio. Penelitian ini memberikan kontribusi terhadap pemanfaatan teknik augmentasi sebagai strategi efektif dalam pengolahan data audio terbatas untuk pengembangan model pembelajaran mesin yang lebih handal.Kata kunci: Augmentasi; Data; Audio; Random Gain; Time Shifting. Abstract  - This paper discusses the application of audio data augmentation techniques as a solution to the limited number of datasets in the development of machine learning models in audio signal recognition and processing. The process of data augmentation involves the expansion and enrichment of data sets without the necessity of collecting additional data. The objective of this process is to enhance the performance of models. The two augmentation methods employed in this study are time shifting and random gain. Time shifting involves the adjustment of the audio signal by 0.2 seconds, a modification intended to preserve the naturalness of the sound. Random gain, on the other hand, adjusts the audio volume within the range of 0.5 to 1.5, a process that is entirely random. The dataset employed in this study consists of the pronunciation of 28 Hijaiyah letters, encompassing a total of 364 audio data points sourced from open databases on Kaggle. The augmentation results demonstrate an augmentation in audio signal variation without a concomitant alteration in the fundamental characteristics of the sound. This is expected to enhance the accuracy and robustness of the model in the face of audio input variations. This research makes a significant contribution to the field by demonstrating the efficacy of augmentation techniques as a strategy for processing limited audio data, thereby facilitating the development of more reliable machine learning models.Keywords: Audio; Data; Augmentation; Random Gain; Time Shifting.
PENERAPAN ALGORITMA NAÏVE BAYES CLASSIFIER UNTUK KLASIFIKASI PENJUALAN OBAT DI APOTEK NUGRAHA Rifa Maulida; Nuk Ghurroh Setyoningrum; Alam
IPSIKOM Vol. 14 No. 1 (2026): Jurnal Ipsikom
Publisher : LPPM UNIVERSITAS INSAN PEMBANGUNAN INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/ipsikom.v14i1.446

Abstract

This study discusses the application of the Naive Bayes Classifier algorithm in analyzing drug sales transaction data at Apotek Nugraha. The purpose is to assist stock management and decision-making related to drug availability based on consumer purchasing patterns. The data used consists of sales transaction records, which are then processed and classified to predict drug demand trends. The Naive Bayes Classifier method was chosen for its ability to perform classification quickly, simply, and with relatively good accuracy even when using limited datasets. The results indicate that this algorithm can identify frequently purchased drug categories and provide predictions that support efficient inventory management. Thus, the implementation of data mining using Naive Bayes Classifier can improve the effectiveness of pharmacy services while minimizing the risks of both stock shortages and overstocking.
Implementasi Sistem Booking Online Berbasis Website untuk Mendukung Smart Business pada QM Photo Studio Dede Rizal Nursamsi; Alam Alam; De Ali Farizal; Ramadhan Ariandi; Riska Raudhatul A’naini
Karya Nyata : Jurnal Pengabdian kepada Masyarakat Vol. 3 No. 2 (2026): Juni : Karya Nyata : Jurnal Pengabdian kepada Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karyanyata.v3i2.3305

Abstract

QM Photo Studio still conducts its service booking process manually, which leads to several issues such as scheduling recording errors, delayed confirmations, and limited access to information regarding service availability. These conditions result in suboptimal operational efficiency and reduced service quality provided to customers. Therefore, this community service program aims to develop a web-based online booking system to improve efficiency, accuracy, and integration in photography service management. The system development was carried out using a multi-layer (4-tier) architecture method, Model-View-Controller (MVC), and a Service Layer approach implemented with the Laravel framework and MySQL database. Data collection involved observation, interviews, and documentation to comprehensively identify system requirements. The developed system is designed to facilitate customers in making online service bookings, while also assisting administrators in managing schedules, services, and transactions in a more structured and real-time manner. The implementation results show that the online booking system improves the operational efficiency of QM Photo Studio, reduces the potential for recording errors, and accelerates service confirmation processes. Furthermore, the system supports digital transformation in photography business management, making services more effective, modern, and responsive to customer needs.
IoT-Integrated Computerized Maintenance Management System (CMMS) for Optimizing Maintenance Efficiency in Smart Manufacturing Robby Maududy; Alam Alam; Wuslah Raia Maulidiyah; R Reza El Akbar
Scientific Journal of Informatics Vol. 13 No. 1: February 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v13i1.36306

Abstract

Purpose: The manufacturing industry continues to face persistent challenges in maintaining equipment reliability and maintenance efficiency, particularly in scheduling, spare parts control, and real-time monitoring of machine conditions. This study aims to develop an Internet of Things (IoT)-based Computerized Maintenance Management System (CMMS) to improve maintenance effectiveness, minimize equipment downtime, and support the realization of smart manufacturing in the automotive sector. Methods: The system was developed using the ADDIE model, consisting of analysis, design, development, Implementation, and Evaluation. and was integrated with IoT sensors to acquire real-time machine temperature and operational status data. and integrated with IoT sensors to collect real-time data on machine temperature and operational status. The collected data were processed in a centralized database and presented through a web-based CMMS application comprising work order management, preventive and corrective maintenance, inventory control, and analytical reporting modules. System functionality was validated using black-box testing, while performance evaluation was conducted by comparing Mean Time Between Failures (MTBF), Mean Time to Repair (MTTR), and maintenance efficiency before and after system implementation. Result: The results indicate that all evaluated equipment experienced performance improvements following CMMS implementation, characterized by increased MTBF and reduced MTTR. On average, overall maintenance efficiency increased by approximately 368%, demonstrating significant reductions in downtime and improvements in maintenance responsiveness supported by real-time condition data. Novelty: The novelty of this study lies in the integration of IoT technology into CMMS that emphasizes the utilization of real-time machine condition data not only for monitoring purposes but also to support maintenance planning, work order management, and data-driven decision-making within a single application. The findings provide empirical evidence that effective data utilization strategies within CMMS implementations can significantly enhance maintenance efficiency and support smart maintenance practices aligned with Industry 4.0 principles.
SISTEM PENGENDALIAN DAN MONITORING PROGRAM MAKAN BERGIZI GRATIS (MBG) BERBASIS WEB MENGGUNAKAN ALGORITMA RULE BASED DI SMK SARIWANGI Muhammad Miftah Khairul Muharom; Alam
PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer Vol. 13 No. 2 (2026): Prosisko Vol. 13 No. 2 Juli 2026
Publisher : Pogram Studi Sistem Komputer Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/tamxez63

Abstract

Pelaksanaan Program Makan Bergizi Gratis (MBG) di SMK Sariwangi masih menemui sejumlah hambatan, di antaranya pencatatan yang masih dilakukan secara manual, potensi pengambilan makanan lebih dari satu kali, ketidaksesuaian distribusi ketika siswa tidak hadir, serta permasalahan hilangnya wadah makanan. Penelitian ini bertujuan merancang dan membangun sistem pengendalian serta monitoring distribusi MBG berbasis web dengan menerapkan model pengembangan 4D (Define, Design, Develop, Disseminate). Sistem yang dibangun memanfaatkan teknologi QR Code berbasis Nomor Induk Siswa (NIS) sebagai pengenal unik setiap siswa dalam proses validasi pengambilan makanan. Algoritma rule-based dengan logika IF-THEN turut diterapkan guna mengotomatiskan kendali distribusi sekaligus memantau pengembalian wadah. Pengujian fungsional melalui Black Box Testing menunjukkan seluruh fitur berjalan dengan baik tanpa kendala berarti. Adapun uji usability menggunakan Skala Likert terhadap 30 responden menghasilkan skor 79,09%, menempatkan sistem dalam kategori "Baik" dan layak digunakan untuk meningkatkan efisiensi serta transparansi pengelolaan logistik MBG.
Co-Authors Adhy, Dewanto Rosian Aini Syifa, Raisa Hilia Alana, Divi Adiffia Freza Ardhiansyah Christina Juliane, Christina De Ali Farizal Dea Dewi Damayanti Dede Rizal Nursamsi Hilmi Rahmawati Irma Wati Ita Lodana, Mae B Miftahudin Miftahudin Muhammad Miftah Khairul Muharom Muhammad Mulyadi N. Nelis Febriani SM Nuk Ghurroh Setyoningrum Nurdin, Arif Muhamad Nursamsi, Dede Rizal R Reza El Akbar Ramadhan Ariandi Rifa Maulida Riska Raudhatul A’naini Robby Maududy Robby Maududy Rusliana, Nanang SALMAN AL FARISI Setyoningrum, Nuk Gurroh Sri Sudiarti Syfa, Raisa Hillia Aini Wuslah Raia Maulidiyah