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All Journal Journal of Information System JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) EVOLUSI : Jurnal Sains dan Manajemen Jurnal Teknologi Informasi dan Pendidikan Infotekmesin Journal of Innovation Information Technology and Application (JINITA) Madani : Indonesian Journal of Civil Society Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Blend Sains Jurnal Teknik Wahana Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat Jurnal Inovasi Daerah
Abdul Rohman Supriyono
Politeknik Negeri Cilacap
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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DAMPAK KNOWLEDGE MANAGEMENT TERHADAP PENINGKATAN KINERJA PEGAWAI PADA PERUSAHAAN HOTEL CILACAP Linda Perdana Wanti; Inka Putri Cahyanti; Abdul Rohman Supriyono
Jurnal Inovasi Daerah Vol. 1 No. 2 (2022): JID: Jurnal Inovasi Daerah, Desember 2022
Publisher : Badan Perencanaan Pembangunan Penelitian dan Pengembangan Daerah Kabupaten Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56655/jid.v1i2.42

Abstract

Indonesia has many tourist destinations that can be used to increase regional income. Among them are Teluk Penyu Beach and the tourist area of Benteng Pendem which is in Cilacap Regency. This will also affect the formation of tourism accommodations such as hotels. The purpose of this study is to improve the service of hotel employees who are influenced by the performance of hotel employees, so the purpose of this study is to analyze the effect of knowledge management on improving employee performance. The data used in this study uses employee data and other data taken at the Whiz Cilacap Hotel which is located on Jln. General Soedirman, Cilacap Regency, Central Java. The method used in this study is a quantitative descriptive method with independent variables including team performance (X1), employee empowerment (X2), and training (X3), while the dependent variable is employee performance (Y). The results of this study are that the independent variables have a positive and significant influence/impact on the dependent variable, which means that team performance, employee empowerment and training have a positive effect on improving the performance of Whiz Cilacap Hotel employees.
Perbandingan Kinerja Antara Gatling dan Apache JMeter pada Uji Beban RESTful API Prih Diantono Abda'u; Agus Susanto; Abdul Rohman Supriyono; Dwi Novia Prasetyanti
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.2176

Abstract

This research explores and compares the performance of two popular load testing tools, namely Gatling and Apache JMeter, with a focus on API performance testing. The rapid growth in web and mobile application development highlights the urgent need to ensure optimal API performance. This research was conducted to provide in-depth insight into the advantages and disadvantages of these two testing tools through the use of similar testing scenarios. The experimental method involves implementing test scenarios that include load variations and high demands on both devices. The main parameters observed include API response time, throughput, and latency. In-depth analysis was carried out on the data obtained to evaluate the reliability and efficiency of each tool. The results of this research provide a comprehensive understanding of the performance of Gatling and Apache JMeter in the context of API performance testing. These findings can provide practical guidance for software developers and testing practitioners in selecting load testing tools that suit their project needs. Recommendations for future research include expanding exploration of other load testing tools, comparison with more complex test scenarios, and integration with performance monitoring tools for more holistic analysis. Thus, this research is expected to make a significant contribution to the understanding and selection of effective load testing tools in web and mobile application development.
Development of a Hybrid CNN–SVM-Based Acute Lymphoblastic Leukemia Detection System on Hematology Image Data Linda Perdana Wanti; Annisa Romadloni; Kukuh Muhammad; Abdul Rohman Supriyono; Muhammad Nur Faiz
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 2 (2025): JINITA, December 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v7i2.3002

Abstract

Acute Lymphoblastic Leukemia (ALL) is among the most common pediatric blood cancers and progresses rapidly, necessitating early and accurate detection. Manual diagnosis via microscopic analysis of blood samples is time-consuming and highly dependent on specialist expertise. This study proposes a hybrid model that combines a Convolutional Neural Network (CNN) with a Support Vector Machine (SVM) to automatically detect ALL from blood-cell images. The CNN performs deep feature extraction from images, while the SVM serves as the classifier to determine ALL status. The dataset comprises microscopic images labeled as ALL or normal and is processed through preprocessing steps such as augmentation and normalization. The adopted CNN produces optimized feature representations. Experimental results show that the hybrid CNN–SVM model with an RBF kernel achieves the best performance, with an accuracy of 96.4%, precision of 95.8%, recall of 96.1%, and an F1-score of 96.0%, surpassing pure CNN-based baselines. Training converged at the 41st epoch, with a training accuracy of 97.2%, validation accuracy of 95.9%, training loss of 0.09, and validation loss of 0.11, indicating stable learning without overfitting. The model’s ROC curve lies well above the chance diagonal, with an Area Under the Curve (AUC) of 0.914, means there is a 91.4% chance the model assigns a higher score to a truly positive (leukemia) image than to a negative (normal) image.These findings suggest that the CNN–SVM hybrid approach enhances leukemia detection performance compared with conventional CNN-only methods and holds promise as a fast, accurate, and efficient image-based decision-support tool for early leukemia diagnosis in digital hematology.
Penguatan Kapasitas Digital UMKM Desa Menganti melalui Pelatihan Pemanfaatan Aplikasi Online untuk Pemasaran Produk LINDA PERDANA WANTI; Rahmawan Bagus Trianto; Abdul Rohman Supriyono; Annisa Romadloni; Muhammad Abdul Muin; Antonius Agung Hartono; Hety Dwi Hastuti
Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Vol. 8 No. 1 (2026): Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/abdimaspolibatam.v8i1.12145

Abstract

Micro, Small, and Medium Enterprises (MSMEs) in Menganti Village, Cilacap Regency, play a vital role in driving the local economy, yet they face limitations in utilizing digital technology for product marketing. Most MSMEs still rely on conventional marketing methods, resulting in relatively limited market reach and competitiveness. This community service program aims to improve the digital capacity of MSMEs through training in the use of online applications as a means of marketing their products. The program implementation method includes needs identification, outreach, hands-on training, and mentoring in the use of digital marketing applications, such as social media and marketplace platforms. The training focused on digital account management, creating simple promotional content, and implementing easy-to-implement online marketing strategies tailored to the characteristics of village MSME products. The results of the program indicate an increase in the knowledge, skills, and confidence of MSMEs in utilizing online applications to market their products more widely. Participants are now able to manage digital media independently and understand the importance of digital marketing as part of business development. This program is expected to encourage the independence and sustainability of MSMEs in Menganti Village in facing the challenges of the digital economy and continuously increase the competitiveness of local products.
Peningkatan Kapasitas UMKM Kabupaten Cilacap Melalui Kecerdasan Buatan dan Keamanan Transaksi Digital Bella Adinda Putri; Linda Perdana Wanti; Satriawan Desmana; Krisna Nuresa Qodri; Ratih Ratih; Abdul Rohman Supriyono; Muhammad Nur Faiz; Oman Somantri; Ratih Hafsarah Maharrani
Wahana Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 1 (2026): Edisi Juni
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/wahana.v5i1.1778

Abstract

UMKM di era digital menghadapi tantangan karena kurangnya pemahaman tentang literasi digital dan kesadaran akan ancaman siber. Kegiatan ini bertujuan untuk meningkatkan pemahaman pelaku UMKM–yang didukung oleh BAZNAS Kabupaten Cilacap–dalam memanfaatkan teknologi AI dan aplikasi keamanan digital. Metode pelaksanaannya menggunakan pelatihan praktik langsung, diskusi interaktif, dan pendampingan langsung melalui dua tahap: (1) pengenalan konsep AI untuk keamanan transaksi digital; dan (2) pelatihan tentang aplikasi pendukung keamanan digital (GetContact, Kredibel, dan VirusTotal). Kegiatan ini melibatkan 100 pelaku UMKM dari berbagai sektor usaha. Evaluasi yang dilakukan melalui pre-test dan post-test menggunakan 10 pertanyaan terkait materi pelatihan menunjukkan peningkatan yang signifikan dengan rata-rata skor peserta meningkat dari 78,09 (pre-test) menjadi 97,50 (post-test), yang menggambarkan peningkatan sebesar 19,41 poin atau 28,98%. Hal ini menunjukkan bahwa pelatihan tersebut efektif meningkatkan literasi keamanan digital dan memberdayakan pelaku UMKM untuk melindungi bisnis mereka dari ancaman kejahatan siber dan penipuan online.
Pembelajaran Berbasis Kasus untuk Pendidikan Keamanan Siber: Tinjauan Literatur Sistematis dan Agenda Penelitian Vokasi Bella Adinda Putri; Ratih Ratih; Krisna Nuresa Qodri; Satriawan Desmana; Abdul Rohman Supriyono
Blend Sains Jurnal Teknik Vol. 5 No. 1 (2026): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v5i1.1833

Abstract

Pembelajaran Berbasis Kasus (Case-Based Learning/CBL) telah terbukti efektif dalam pendidikan profesi seperti kedokteran, hukum, dan bisnis. Namun, penerapan dan kajian sistematisnya dalam bidang keamanan siber khususnya di pendidikan tinggi vokasi di negara berkembang masih sangat terbatas. Belum ada sintesis komprehensif yang memetakan pendekatan CBL, luaran kompetensi, instrumen pengukuran, maupun tantangan implementasi yang spesifik pada bidang ini. Tinjauan Literatur Sistematis (TLS) ini bertujuan memetakan pendekatan CBL dalam pendidikan keamanan siber (2014–2025), mengidentifikasi kompetensi yang dikembangkan, mensintesis instrumen pengukuran efektivitas, mengarakterisasi tantangan implementasi, dan menyusun agenda penelitian untuk pendidikan tinggi vokasi di negara berkembang dengan rujukan konteks Indonesia. Mengikuti panduan PRISMA 2020, pencarian sistematis dilakukan pada enam basis data elektronik (Scopus, Web of Science, IEEE Xplore, ACM Digital Library, ERIC, dan Google Scholar). Kriteria inklusi mengikuti kerangka PICOS. Dua peninjau independen melakukan penyaringan; penilaian kualitas menggunakan Mixed Methods Appraisal Tool (MMAT) yang diadaptasi. Sintesis menggunakan pendekatan naratif, tematik, dan pemetaan frekuensi. Terdapat sekitar 40–70 studi primer yang akan diinklusikan. Temuan yang diantisipasi mencakup dominasi kasus diskusi dan laboratorium; luaran kompetensi yang terkonsentrasi pada domain Serangan & Pertahanan serta Keamanan Sistem dari CyBOK; dan konteks vokasi negara berkembang yang sangat kurang terwakili. TLS ini menghasilkan peta komprehensif CBL dalam pendidikan keamanan siber, agenda penelitian berbasis bukti untuk institusi vokasi, dan rekomendasi desain modul CBL yang relevan untuk Prodi Rekayasa Keamanan Siber Politeknik Negeri Cilacap.
Support Vector Machine (SVM) - Based Optimization of Leukemia Cell Image Classification Linda Perdana Wanti; Annisa Romadloni; Kukuh Muhammad; Abdul Rohman Supriyono
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.2974

Abstract

Leukemia is a type of blood cancer characterized by the uncontrolled proliferation of abnormal white blood cells that originate from the bone marrow. Early detection of leukemia poses a significant challenge in the medical field, as the conventional diagnostic process still relies on manual microscopic observation by hematologists, which is time-consuming and prone to subjective errors. This study aims to analyze the potential of the Support Vector Machine (SVM) algorithm in optimizing the classification of leukemia cell images based on morphological and texture features extracted from microscopic images. The test results show that the SVM model with the RBF kernel provides the best performance with an accuracy of 96.4%, a precision of 95.8%, a recall of 96.1%, and an F1-score of 96.0%, surpassing the results of linear and polynomial kernels. The analysis shows that the use of a combination of shape and texture features has a significant effect on improving classification accuracy.
Co-Authors Agus Susanto Andesita Prihantara Anggita Dwi Fatimah Annas Setiawan Prabowo Annisa Romadloni Antonius Agung Hartono Arif Fahrizal Arif Wirawan Muhammad Bambang Sugiantoro Bella Adinda Putri Betti Widianingsih Devi Taufiq Nurrohman Dodi Satriawan Dwi Novia Prasetyanti Hety Dwi Hastuti Inka Putri Cahyanti Isa Bahroni, Isa Krisna Nuresa Qodri Kukuh Muhammad Laura Sari Linda Perdana Wanti Linda Perdana Wanti Lutfi Syafirullah Muhammad Abdul Muin Muhammad Nur Faiz Oman Somantri Oto Prasadi Prih Diantono Abda`u Rahmawan Bagus Trianto Ratih Hafsarah Maharrani Ratih Ratih Riyadi Purwanto Rostika Listyaningrum Sari, Eka Dyah Puspita Satriawan Desmana Yudi prayudi