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All Journal JSAI (Journal Scientific and Applied Informatics) Jurnal Abdi Insani Jurnal Teknik Informatika (JUTIF) Jurnal INFOTEL Dharmakayana: Journal of scientists, engineers, educators and scientific activists related to society development
Kurnia Anggriani, Kurnia
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering

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Analisis Manajemen Layanan TI pada Kebangkrutan E-commerce jd.id Menggunakan Kerangka Kerja Infrastructure Technology Information Library (ITIL v3) Anggriani, Kurnia; Ferzha Putra Utama; Okta Piani, Sri; Vatresia, Arie; Bismantolo, Putra
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 2 (2024): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i2.6348

Abstract

E-commerce has recently become a place that is in great demand by consumers to shop. In general, e-commerce is a term used to describe the sale of goods and services via the internet. Among the many e-commerce services in Indonesia, one of them is JD.id. This research aims to look at the IT services used by JD.id previously by looking at the processes of domain service operations with the ITIL V3 framework and finding out the extent of management of the IT services used by JD.id before JD.id closed. The method used in this research is a quantitative descriptive method and the assessment of the results of this research is based on the answers to the questionnaire given to respondents using a Likert scale. The sample taken was 100 people who were JD.id users. The data sources obtained in this research are primary data and secondary data. The data analysis carried out was calculating the Maturity Level of the Service Operation subdomain. The results of the research obtained the lowest value, namely the problem management variable with a value of 3.70, meaning that the JD.id marketplace is still not very optimal in terms of preventing incidents from occurring and there is no permanent improvement process and is not very optimal in terms of continuous service improvement. However, the overall maturity level (Maturity Level) on average is at level 4 with a score of 3.97 this means that the IT service processes in the JD.id marketplace have been planned and implemented well and consistently, but automation with the information technology tools used is limited.
Analysis of Maturity Alignment of Business Strategy with Information Technology at SAMSAT Bengkulu City Using Strategic Alignment Maturity Model (SAMM) Anggriani, Kurnia; Ferzha Putra Utama; Stern Imanuel Kristian; Arie Vatresia; Putra Bismantolo
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8018

Abstract

Motor vehicle tax payments represent a substantial portion of regional income. However, recurrent delays in motorbike tax payments, notably in the Kandang Limun sub-district of Bengkulu City, pose a significant threat to regional development. This research aims to address these delays by predicting and implementing effective strategies. Using the RapidMiner application and the Artificial Neural Network (ANN) method, a delay rate of 36.14% was predicted. The study incorporates interviews to propose several strategies, including enhancing websites, improving offline and online services, implementing Drivethru services, and using SMS Blast notifications to combat delays. To evaluate the feasibility of these strategies, the research employs the Strategy Alignment Maturity Model (SAMM). The assessment at BPKD reveals a maturity level of 4, signifying an ability to improve and manage processes effectively.The maturity assessment suggests that the proposed strategies for overcoming delays are well-aligned with BPKD's capabilities. They have demonstrated a robust alignment between IT and business strategies, leveraging IT to enhance performance, and conducting thorough business and IT evaluations.In addition to the maturity assessment, the research offers suggestions and evaluation strategies. These encompass the adoption of biometrics for authentication, implementation of chatbots, Samsat self-service kiosks, real-time vehicle monitoring, and the introduction of automatic tax programs.
Development of Smart Hydroponics System using AI-based Sensing Putra, Septafiansyah Dwi; Heriansyah, Heriansyah; Cahyadi, Eko Fajar; Anggriani, Kurnia; Imron S Jaya, Moh Haris
JURNAL INFOTEL Vol 16 No 3 (2024): August 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i3.1190

Abstract

This paper proposes a smart hydroponic system that operates automatically using a fuzzy logic algorithm, integrating IoT functionalities to support smart agriculture. The system allows for remote monitoring and control via the internet, providing real-time data on water levels, pH levels, temperature, and nutrient solution temperature. Precise dosing and temperature control are critical for optimal plant growth, and the system schedules temperature measurements to ensure stability. Unstable temperature can affect pH levels, thereby impacting nutrient absorption. The proposed system employs sensors to continuously monitor the electrical conductivity (EC) and pH levels of the nutrient solution. Fuzzy control is utilized to regulate the nutrient solution pump, automatically adjusting EC and pH levels to promote optimal plant growth. This approach reduces the time burden on producers and provides more precise control over the nutrient solution, resulting in improved growth outcomes. The main contributions of this work are as follows: the development and implementation of an AI-based system integrating a controller, IoT environment, fuzzy logic algorithm, and NFT (nutrient film technology) hydroponics; the creation of a user-friendly interface for farmers through the Smart-Hydroponic application, enabling hybrid monitoring and control of hydroponic farms; the establishment of an IoT-based cloud environment for sensor data monitoring; the implementation of a smart hydroponic system for nutrient sensing, monitoring, and control; and a comparative analysis between smart and conventional hydroponics based on morphological results.
Enhancing Malware Detection in IoT Networks using Ensemble Learning on IoT-23 Dataset Anggriani, Kurnia; Az Zahra, Syakira; Susanto, Agus
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4782

Abstract

The Internet of Things (IoT) has become a technological innovation that brings many benefits in various sectors, but also presents challenges, especially in terms of cybersecurity. One of the main threats is malware, which can damage devices, steal data, and disrupt system performance. With the increasing use of IoT, malware attacks on IoT devices are a serious concern. Previous research shows that malware detection models in IoT devices still have shortcomings, especially in terms of accuracy. One of the algorithms used in malware detection, Naïve Bayes, has been shown to provide low accuracy results. This study aims to improve the accuracy of malware detection on IoT networks by applying Ensemble learning techniques using traffic data from the IoT-23 dataset. The methodology used refers to the CRISP-DM (Cross Industry Standard Process for Data Mining) framework, which includes the stages of domain understanding, data understanding, data preparation, modelling, evaluation, and deployment. The results show that Ensemble learning improved the performance of individual models. Naïve Bayes as a single model produces an accuracy of 0.24, increasing to 0.35 when combined with AdaBoost, and 0.99 when combined with XGBoost. The combination of the three models also produced an accuracy of 0.99. These results demonstrate the effectiveness of ensemble learning in improving malware detection accuracy in IoT environments.
Herbal Plant Classification Using EfficientNetV2B0 Model and CRISP-DM Approach Sonita, Anisya; Anggriani, Kurnia; Vatresia, Arie; Putri, Tiara Eka; Darnita , Yulia; Zahra, Syakira Az; Aprilia, Vilda; Aziz, Dzakwan Ammar
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5141

Abstract

Herbal remedies have long been utilized by Indonesian communities as part of traditional medicine. However, identification of these natural resources is often challenging due to the morphological similarities among various species, which demand expert knowledge to differentiate. This study aims to implement the EfficientNetV2B0 model architecture for classifying medicinal leaves through an Android-based application designed to support recognition tasks. The dataset was composed of augmented images of plant foliage. The model was trained using the TensorFlow framework and evaluated to measure classification performance. Results demonstrate that EfficientNetV2B0 achieves excellent accuracy, with validation scores exceeding 97%, outperforming several other deep learning models. The resulting application allows the general public to identify local medicinal species more easily. This study contributes to the field of computer vision by providing an accurate and efficient classification framework, particularly beneficial for health-related informatics in biodiversity-rich regions.
Digital Transformation of Population Services through the Implementation of a Web Based Information System: (Sawah Lebar Baru Subdistrict, Bengkulu City, Bengkulu Province) Renaningtias, Nurul; Vatresia, Arie; Putri, Tiara Eka; Anggriani, Kurnia; Nata Kusuma, Teguh
Dharmakayana Vol 2 No 1 (2025): Mei : Dharmakayana: Journal of scientists, engineers, educators and scientific ac
Publisher : Program Studi Teknik Mesin, Fakultas Teknik Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/dk.v2i1.41929

Abstract

Permasalahan pengelolaan data kependudukan di Kelurahan Sawah Lebar Baru Kota Bengkulu masih dilakukan secara manual sehingga menyebabkan seringnya terjadi kesalahan dan keterlambatan dalam pelaporan. Kegiatan pengabdian ini bertujuan untuk membangun sistem infomasi manajemen data kependudukan berbasis web yang dapat memfasilitasi pencatatan, pemutakhiran dan pelaporan data warga secara digital dan terstrukutur. Metode pelaksanaan kegiatan ini meliputi identifikasi kebutuhan, pengembangan sistem menggunakan metode waterfall, implementasi sistem serta sosialiasai dan pendampingan secara berkelanjutan. Hasil implementasi sistem dengan pengujian blackbox testing menunjukkan bahwa seluruh fungsionalitas sistem berhasil untuk dijalankan. Berdasarkan hasil pre-test kegiatan pengabdian ini terjadi peningkatan dalam pemahaman konsep sistem, kemampuan operasional sistem, akurasi input data, dan efektivitas penggunaan fitur dengan rata-rata nilai 91,76. Kegiatan pengabdian ini tidak hanya meningkatkan literasi digital tetapi juga memperkuat partisipasi aktif warga dalam mendukung tata kelola administrasi berbasis teknologi informasi.
PENDAMPINGAN DIGITALISASI ASET SENI DAN BUDAYA BENGKULU DI MUSEUM BDARU SEBAGAI UPAYA TRANSFORMASI DIGITAL DAN PELESTARIAN BUDAYA LOKAL Putri, Tiara Eka; Anggriani, Kurnia; Vinalti, Gushe
Jurnal Abdi Insani Vol 12 No 9 (2025): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v12i9.3108

Abstract

Pelestarian budaya lokal menghadapi tantangan serius akibat keterbatasan literasi digital dan minimnya akses informasi budaya. Museum Balai Adat Rajo Penghulu (BDARU) di Bengkulu menjadi mitra pengabdian untuk menjawab tantangan tersebut melalui program pendampingan digitalisasi aset seni dan budaya. Kegiatan ini bertujuan meningkatkan kapasitas pengurus dalam pengelolaan koleksi berbasis teknologi, memperluas akses masyarakat, serta melibatkan generasi muda dalam pelestarian budaya. Metode kegiatan ini adalah pelatihan dan pendampingan bagi 15 pengurus inti BDARU selama enam bulan di Museum Balai Adat Rajo Penghulu, Bengkulu. Tahapan kegiatan meliputi: (1) analisis kebutuhan melalui observasi dan wawancara, (2) sosialisasi dan FGD untuk penyusunan sistem digitalisasi, (3) pelatihan manajemen data, produksi konten, dan simulasi QR-Code, (4) evaluasi melalui pre-test/post-test serta monitoring dua bulan pasca pelatihan, dan (5) pembentukan tim pengelola digitalisasi untuk keberlanjutan program. Hasil kegiatan menunjukkan peningkatan signifikan pada kompetensi digital pengurus BDARU, ditunjukkan oleh kenaikan rata-rata nilai pre-test dari 61 menjadi 87 pada post-test, dengan gain score 26 dan normalized gain 0,67 (kategori sedang–tinggi). Sebanyak 135 koleksi budaya berhasil terdigitalisasi, 100 koleksi telah dilengkapi QR-Code aktif, dan 10 konten budaya dipublikasikan melalui media sosial serta website museum digital. Pencapaian ini menegaskan efektivitas pelatihan dalam meningkatkan kapasitas pengelolaan aset budaya berbasis teknologi. Temuan ini menegaskan bahwa program efektif dalam meningkatkan keterampilan pengurus, memperkuat literasi budaya masyarakat, dan memperluas akses edukasi digital. Kesimpulannya, pendampingan digitalisasi BDARU berperan penting dalam transformasi pelestarian budaya lokal di era digital.
Co-Authors Agus Susanto Aprilia, Vilda Arie Vatresia Arie Vatresia Az Zahra, Syakira Aziz, Dzakwan Ammar Bismantolo, Putra Darnita , Yulia Eko Fajar Cahyadi Heriansyah Imron S Jaya, Moh Haris Nata Kusuma, Teguh Nurul Renaningtias, Nurul Okta Piani, Sri Putra Bismantolo Putra, Septafiansyah Dwi Putri, Tiara Eka Sonita, Anisya Stern Imanuel Kristian Utama, Ferzha Putra Vinalti, Gushe Zahra, Syakira Az