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All Journal Jurnal Masyarakat Informatika PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Infotekmesin Abdimasku : Jurnal Pengabdian Masyarakat Indonesian Journal of Public Administration Review
Kurniawan, Defri
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences

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TEST CASE GENERATION BERBASIS STATE MODEL UNTUK VERIFIKASI SISTEM LAYANAN PERMOHONAN ROHANIWAN Kurniawan, Defri; Utomo, Danang Wahyu; Ningrum, Novita Kurnia
Dinamika Rekayasa Vol 16, No 1 (2020): Jurnal Ilmiah Dinamika Rekayasa - Februari 2020
Publisher : Jenderal Soedirman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.dr.2020.16.1.275

Abstract

Pembuatan kasus uji (test case generation) merupakan tahapan yang membutuhkan sumber daya terbesar yang memiliki pengaruh terhadap keefektifan dan efisiensi suatu pengujian perangkat lunak. Pembuatan test case menjadi salah satu topik penelitian paling manarik. Pengujian berbasis model (model based testing) diusulkan untuk membuat kasus uji pada Sistem Layanan Permohonan Rohaniwan Kementerian Agama Provinsi Jawa Tengah. Model yang diusulkan dalam pembuatan kasus uji dimulai dari kegiatan pengumpulan kebutuhan, menganalisa use case dan class, mengidentifikasi state, melakukan pemodelan perilaku (behaviour modelling) menggunakan state machine diagram dan membuat daftar kasus uji. Penelitian menunjukkan penggunaan model berbasis state mempu mendukung pembuatan kasus uji (test case) dan dapat mendeteksi perilaku (behavior) dari response sistem yang kurang sesuai terhadap inputan atau aksi yang diberikan oleh user.
PENDAMPINGAN PEMBUATAN MODUL, SOAL, DAN TUGAS BERBASIS DARING UNTUK GURU SMP NEGERI 30 SEMARANG Sukmana, Septian Enggar; Kurniawan, Defri; Adi, Prajanto Wahyu
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 1, No 2 (2018): Juli 2018
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (500.647 KB)

Abstract

Penerapan e-Learning di berbagai sekolah perlu dilaksanakan maka diperlukan desiminasi terhadap pemahaman e-Learning di berbagai sekolah. Pemahaman mengenai e-Learningdi sekolah akan mengarah kepada implementasi e-Learning di sekolah tersebut. Tanpa desiminasi pemahaman dan pendampingan kepada guru-guru sekolah terhadap penggunaan e-Learning, maka sulit untuk terwujud suatu pembelajaran yang interaktif, kreatif dan mampu meningkatkan prestasi serta motivasi belajar siswa di sekolah. Pengembangan e-learning telah dilakukan oleh mitra pengabdian masyarakat yaitu SMPN 30 Semarang. Permasalahan muncul ketika implementasi e-learning di sekolah tersebut untuk kegiatan belajar-mengajar yaitu kurang optimalnya penggunaan media e-learning tersebut. Oleh karena itu, inisiatif pemberian pendampingan oleh beberapa dosen Universitas Dian Nuswantoro kepada para guru dapat menjadi solusi atas masalah tersebut. Kegiatan pendampingan yang dilakukan meliputi pembuatan modul, kuis, dan tugas. Hasil yang diperoleh menunjukkan para guru mampu mengoperasikan sistem manajemen pembelajaran dan diharapkan pendampingan secara intensif lebih sering dilakukan.
IbM Pendampingan Penggunaan Sistem Ujian Online Kepada Guru-guru MA Al Hadi Mranggen Kurniawan, Defri
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 2, No 2 (2019): Juli 2019
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (814.82 KB) | DOI: 10.33633/ja.v2i2.41

Abstract

Pelaksanaan Ujian Nasional di Indonesia telah menggunakan komputerisasi guna menggantikan sistem yang lama yaitu ujian nasional menggunakan kertas dan pensil. Adanya ujian nasional berbasis komputer, memberikan keuntungan dalam hal efisiensi waktu, biaya, mengurangi kecurangan, dan mempercepat proses evaluasi. Madrasah Aliyah Al Hadi yang berada di desa Banyumeneng, Kecamatan Mranggen, Demak merupakan sekolah yang telah menyelenggarakan Ujian Nasional Berbasis Komputer (UNBK). Namun berdasarkan Rekap Hasil Ujian Nasional (UN) Tingkat Sekolah tahun pelajaran 2017/2018 ketiga Program Studi pada Madrasah Aliyah Al Hadi masih masuk pada kategori Kurang. Kurangnya nilai UN siswa pada beberapa Program Studi tersebut, dapat disebabkan oleh kurangnya siswa dalam berlatih (try out) mengerjakan soal-soal UN dengan menggunakan komputer. Paperless Test System merupakan sistem yang dikembangkan dari penelitian untuk mengevaluasi hasil belajar siswa, dengan memberikan test yang dikerjakan secara online dengan batas waktu tertentu. Ketrampilan dalam pembuatan bank soal diberikan kepada guru-guru MA Al Hadi pada pelatihan penggunaan aplikasi Paperless Test System. Hasil pelatihan menunjukkan guru-guru MA Al Hadi menjadi lebih mengenal dan memahami penggunaan sistem ujian tanpa kertas sebagai media evaluasi hasil belajar siswa.
PENERAPAN EDMODO BAGI GURU DAN MURID SMK KARYA BHAKTI BREBES SEBAGAI MEDIA BELAJAR TAMBAHAN Sani, Ramadhan Rakhmat; Utomo, Danang Wahyu; Kurniawan, Defri
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 3, No 2 (2020): Mei 2020
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/ja.v3i2.92

Abstract

Berkembangnya teknologi secara masif memberikan pengaruh salah dalam dunia pendidikan. Para guru perlu mengimbangi perkembangan teknologi dari siswanya yang sangat mudah dalam mengabdospinya.  Pembelajaran online  sudah banyak diterapkan pada banyak sekolah tetapi hanya tidak jarang juga yang diterapkan oleh para guru untuk melaksanakannya. Salah satunya adalah SMK Karya Bhakti Brebes yang sudah mengetahui tentang e-learning tetapi hanya beberapa mata pelajaran saja dalam penerapannya. Dalam penerapan pembelajaran online terkadang para guru masih kesulitan dalam mengatur kelasnya. Maka dari itu diperlukan pendampingan dalam penggunaan sistem e-learning salah satunya adalah edmodo.  Dan juga sosialisasi terhadap guru-guru lainya untuk mendapatkan pemahaman khusus dalam proses pembelajaran online seperti dalam melakukan ulangan harian ataupun penugasan. Hasil dari pengabdian ini memberikan pemahaman khusus dasar aplikasi tersebut dan bagaimana proses pengisian konten yang dilakukan bagi para guru dengan melakuan simulasi langsung. 
Web-Based E-Log Book Application for Enhancing the Quality of Student Projects Ananta, Devanda Radya; Kurniawan, Defri
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 1 (2024): March 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i1.8094

Abstract

The student project is the biggest specter for students, and many are hindered by it. The problem that occurs is the difficulty of student activities and assignment supervisors who are still carried out manually, so it cannot be denied that there are many carelessness and errors that have an impact on the final result. The purpose of this research is to design and build a website-based final project guidance e-log book application using the prototyping method in Informatics Engineering S1 Faculty of Computer Science, Dian Nuswantoro University Semarang. The research method applies a qualitative approach with the source of interviews and document studies, while the development method uses the prototype method with three steps namely listening to customers, building and revising mock-ups, and testing. The results showed that the website for recording final project guidance in Informatics Engineering S1, Faculty of Computer Science, Dian Nuswantoro University Semarang that had been developed was in accordance with the needs of the Final Project Coordinator for monitoring students in recording final project guidance. The application of the prototype method that starts from listening to customers, building and revising mock-up, and testing is very helpful in the process of developing a website for recording final project guidance.
Optimizing Classification Algorithms Using Soft Voting: A Case Study on Soil Fertility Dataset Kamarudin, Fatkhurridlo Pranoto; Budiman, Fikri; Winarno, Sri; Kurniawan, Defri
Jurnal Teknologi Informasi dan Pendidikan Vol. 16 No. 2 (2023): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v16i2.800

Abstract

Classification algorithms are crucial in developing predictive models that identify and classify soil fertility levels based on relevant attributes. However, optimizing classification algorithms presents a major challenge in enhancing the accuracy and effectiveness of these models. Therefore, this research aims to optimize the classification algorithm in soil fertility analysis using ensemble learning techniques, specifically Soft Voting Ensemble. This research method is designed to understand soil fertility levels in modern agriculture by comparing the performance of various classification algorithms and ensemble approaches. Using a dataset from the Purwodadi Department of Agriculture, this study examines the optimization of algorithm parameters such as Random Forest, Gradient Boosting, and Support Vector Machine (SVM) and the implementation of Soft Voting Ensemble. Before applying Soft Voting Ensemble, each algorithm was evaluated with the following results: Random Forest achieved an accuracy of 90.93%, precision of 91.08%, recall of 90.33%, and F1-Score of 90.70%; Gradient Boosting achieved an accuracy of 91.53%, precision of 91.19%, recall of 91.56%, and F1-Score of 91.38%; SVM achieved an accuracy of 88.91%, precision of 89.66%, recall of 87.45%, and F1-Score of 88.54%. After implementing Soft Voting Ensemble, the accuracy improved to 91.63%, with an average precision of 91.21%, recall of 91.77%, and F1-Score of 91.49%. This study divided the data into 80% for training data and 20% for testing data. These findings indicate that the Soft Voting Ensemble has the potential to enhance agricultural productivity and sustainability.
Implementation of Scrum Framework Agile Method to Develop Integrated Asset Management Information System at Universitas Diponegoro Inventory Module Dzaky, Fauzan Abiyyu; Kurniawan, Defri
Jurnal Masyarakat Informatika Vol 14, No 1 (2023): JURNAL MASYARAKAT INFORMATIKA
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.14.1.52605

Abstract

Diponegoro University Property (BMU) requires an inventory process by the assets and logistics division at least once every five years. The inventory process is still manually. So it is necessary to develop an Integrated Asset Management Information System Inventory Module. The development of an information system that used the Big Bang and Use Case Points method, in this study the Agile method with Scrum Framework will be implemented based on considerations. Scrum as a framework that implements Sprints to break down complexity and accommodate priority features that need to be built from an information system, also divides the roles in implementing development into Product Owner, Developer Team and Scrum Master. The results of implementing this method can be a solution to several problems that arise during development, that is : dividing roles with existing teams, accepting all updates and changes originating from user evaluations through mutual agreement, work transparency which can be a reference in assigning the workload of each team members, regular periodic inspections to remind each member of development targets and goals, as well as adapt to implementing conditions, especially in adjusting communication and implementation times. So make information system development time can implemented shorter.
Penyusunan Analisis Kebutuhan Perangkat Lunak untuk Web Profil SMP Negeri 7 Semarang Utomo, Danang Wahyu; Kurniawan, Defri; Zeniarja, Junta; Dewi, Ika Novita; Salam, Abu; Muljono, Muljono
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 1 (2025): JANUARI 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i1.2700

Abstract

Penggunaan web profil sebagai alat penyebaran informasi telah banyak digunakan pada institusi Pendidikan utamanya sekolah. SMP N 7 Semarang menggunakan web profil untuk menyampaikan informasi terkait identitas sekolah seperti visi dan misi sekolah, kurikulum serta kegiatan siswa dalam sekolah. Namun web tersebut masih terdapat kekurangan dan perlu diperbaiki menyesuaikan dengan perkembangan saat ini. Pemahaman tentang analisis kebutuhan perangkat lunak penting bagi para guru dan tenaga pendidik untuk mengetahui kebutuhan pengguna dan kebutuhan sistem yang harus disediakan dalam sistem. Program pengabdian Masyarakat dilaksanakan dalam bentuk pelatihan kepada para guru dan tenaga pendidik. Para peserta diberikan materi analisis kebutuhan termasuk kebutuhan pengguna, kebutuhan sistem, kebutuhan fungsional dan non-fungsional. Selain itu, para peserta juga menerima pelatihan tentang desain antarmuka pengguna dan tata letak konten situs web. Hasil dari program ini, para peserta dapat mengidentifikasi perbaikan yang diperlukan untuk situs web profil SMP N 7 Semarang. Fitur berita diidentifikasi sebagai kebutuhan fungsional yang perlu ditambahkan pada situs web profil. Untuk kebutuhan non-fungsional, para peserta menyarankan desain ulang tata letak konten web
Deteksi Dini Risiko Penyakit Jantung Koroner Menggunakan Algoritma Decision Tree dan Random Forest Nurrohman, Slamet Hudha; Kurniawan, Defri
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.7029

Abstract

Coronary heart disease is the leading cause of global mortality, accounting for 17.9 million deaths annually. Early detection is crucial in mitigating risks and preventing further complications. However, conventional diagnostic methods, such as traditional medical evaluations, often struggle to efficiently process large volumes of medical data, necessitating a more optimal approach. To enhance efficiency, this study employs machine learning to develop a classification model for coronary heart disease risk using Decision Tree and Random Forest algorithms. These models are then compared to determine the most optimal approach. The model is built using the Framingham Heart Study Dataset, consisting of 4,240 records with 15 relevant features. Due to class imbalance in the target variable, the Random Over-Sampling method is applied to improve classification performance. Model evaluation is conducted using a confusion matrix to compare the performance of both algorithms. The results indicate that Random Forest outperforms Decision Tree, achieving an accuracy of 97.64%, precision of 96.02%, recall of 99.29%, and F1-score of 97.63%. In contrast, Decision Tree yields an accuracy of 91.04%, precision of 84.76%, recall of 99.57%, and F1-score of 91.57%. This study suggests that Random Forest is more effective for early detection of coronary heart disease. Therefore, Random Forest-based models hold potential for clinical prediction systems, though further optimization is needed to enhance accuracy and reliability.
Optimasi Model Particle Swarm Optimization (PSO) Menggunakan SMOTE Untuk Menentukan Penyakit Diabetes Mellitus Putro Utomo, Satrio Allam; Kurniawan, Defri
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.7111

Abstract

Diabetes mellitus is a chronic disease that continues to increase globally and can affect various age groups. If not properly managed, this disease can lead to serious complications. In recent years, technological advancements, particularly in the field of machine learning, have significantly contributed to improving the accuracy of diabetes diagnosis and prediction. This study utilizes the Decision Tree algorithm, enhanced by two optimization methods: the Synthetic Minority Over-sampling Technique (SMOTE) to address data imbalance and Particle Swarm Optimization (PSO) to optimize the model's hyperparameters, thereby improving classification accuracy. The dataset used in this study is the Diabetes Prediction Dataset available on Kaggle, consisting of 100,000 entries. Based on the analysis results, the implementation of data preprocessing and hyperparameter optimization has proven to increase the model's accuracy from 95.21% to 96.52%. Additionally, an evaluation using the confusion matrix shows an improvement in precision from 70.82% to 86.19% and an increase in the F1-score from 72.49% to 78.52%, although there is a slight decrease in recall from 74.24% to 72.11%. These findings demonstrate that a combination of data preprocessing, data balancing, and hyperparameter optimization can significantly enhance the performance of a classification model in detecting diabetes. For future development, it is recommended that the model be tested on other datasets to improve generalizability. Furthermore, exploring additional algorithms such as Random Forest or XGBoost could be beneficial in obtaining more optimal results.
Co-Authors Abu Salam Ainul Yaqin Amartha, Putri Ananta, Devanda Radya Azizah, Hidayatul Dzaky, Azmi Abiyyu Dzaky, Fauzan Abiyyu Egia Rosi Subhiyakto, Egia Rosi Erlin Dolphina Erwin Yudi Hidayat Etika Kartikadarma Fauziah, Mitha Fikri Budiman Haresta, Alif Agsakli Ida Ayu Putu Sri Widnyani Ika Novita Dewi Junta Zeniarja Kamarudin, Fatkhurridlo Pranoto Kuncoro, Aneira Vicentiya Muljono Muljono Ni'mah, Laila Maulin Ningrum, Novita Kurnia Nurrohman, Slamet Hudha Prajanto Wahyu Adi, Prajanto Wahyu Pranata, Eka Arya Purwanto Purwanto Putro Utomo, Satrio Allam Ramadhan Rakhmat Sani Rosi Subhiyakto, Egia Sabrina, Della Septian Enggar Sukmana Sindhu Rakasiwi Sri Winarno Utomo, Danang Wahyu