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PENGEMBANGAN SISTEM TRACER STUDY MENGGUNAKAN AGILE DEVELOPMENT METHODS PADA IBK NITRO Muhammad Ikhwan Burhan; Fadliyani Nawir; Karta Negara Salam
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 3 (2022): Jursima Vol.10 No.3 Desember 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.439

The Nitro Institute of Business and Finance has made various efforts to produce quality graduates who can compete in the world of work, including carrying out tracer studies to map the needs of the world of work with the competencies taught. However, in its implementation, the tracer study is not effective and has many obstacles because it is still carried out manually and is very simple. One of the efforts made to optimize and overcome these obstacles is to develop a website-based system that is able to support the process of distributing and filling out questionnaires, storing data, and facilitating reporting. Agile Development Methods with the Extreme Programming framework are used in the development of the tracer study system at the Nitro Business and Finance Institute because it is adaptive and responsive to changes, and the development process only takes a relatively short time without compromising the quality of the system. Based on the stages of system development using Agile Development Methods with the Extreme Programming framework, there have been three iterations of the development phase. The first iteration produces an initial prototype according to user requirements; the second iteration produces an advanced prototype with the addition of several user requirements; and the third iteration produces a system that is ready for release and has met all user requirements. Keywords: Tracer Study, Agile Deveplopment Methods, Extreme Programming.

PENGEMBANGAN SISTEM TRACER STUDY MENGGUNAKAN AGILE DEVELOPMENT METHODS PADA IBK NITRO Muhammad Ikhwan Burhan; Fadliyani Nawir; Karta Negara Salam
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 3: Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.439

The Nitro Institute of Business and Finance has made various efforts to produce quality graduates who can compete in the world of work, including carrying out tracer studies to map the needs of the world of work with the competencies taught. However, in its implementation, the tracer study is not effective and has many obstacles because it is still carried out manually and is very simple. One of the efforts made to optimize and overcome these obstacles is to develop a website-based system that is able to support the process of distributing and filling out questionnaires, storing data, and facilitating reporting. Agile Development Methods with the Extreme Programming framework are used in the development of the tracer study system at the Nitro Business and Finance Institute because it is adaptive and responsive to changes, and the development process only takes a relatively short time without compromising the quality of the system. Based on the stages of system development using Agile Development Methods with the Extreme Programming framework, there have been three iterations of the development phase. The first iteration produces an initial prototype according to user requirements; the second iteration produces an advanced prototype with the addition of several user requirements; and the third iteration produces a system that is ready for release and has met all user requirements. Keywords: Tracer Study, Agile Deveplopment Methods, Extreme Programming.

Implementasi Metode PERT dan CPM pada Proyek Integrasi Sistem Informasi Kontrol Pemantauan Kondisi Lalu Lintas Muhammad Ikhwan Burhan; A. We Tenri Fatimah Singkeruang; Nur Alam
BUGIS : Journal of Business, Technology, & Social Science Bugis Journal Volume 1 No. 2, April 2023.
Publisher : Pusat Penelitian dan Pengabdian Masyarakat (P3M) IBK Nitro

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

Studi Kasus dalam makalah ini mengangkat proyek Integrasi Sistem Informasi Kontrol Kondisi Lalu Lintas Menggunakan Pemantauan WLAN CCTV pada Dinas Komunikasi dan Informatika Kabupaten Sinjai yang dikerjakan oleh CV. Gowtechno. Target/sasaran yang ingin dicapai dalam pengerjaan proyek ini adalah tersedianya pengamatan dan pengawasan dalam rangka memantau situasi dan kondisi kondisi lalu lintas serta keamanan sekitar (Ruang Publik, Jalan Utama, Pertokoan dan tempat-tempat strategis lainnya). Hasil Penelitian menunjukkan bahwa terdapat kumungkinan 90 % bahwa proyek akan dapat diselesaikan dalam waktu 12 minggu, serta Critical Path memerlukan waktu 11 minggu pengerjaan, dengan project crashing waktu critical path dapat disingkat menjadi 7 minggu.

VERIFIKASI DOKUMEN TRANSKRIP NILAI SEMESTER MENGGUNAKAN METODA OPTICAL CHARACTER RECOGNITION zulkarnaen hatala
Jurnal Informatika dan Teknik Elektro Terapan Vol 11, No 3 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i3.3277

At the Ambon State Polytechnic, students' semester grade reports are still manually typed. This causes frequent typo errors which can result in the invalidity of the document, let alone incorrect grades, student identification numbers and many other label values. Here a java application has been implemented to detect these errors. This application is primarily intended for officials of the Head of Study Program, Head of the Department before signing and validating the report. Officials who legalize it will be greatly assisted because tedious validation work can be replaced by computers. The validation process is carried out by utilizing the optical character recognition technique from the open source library Tesseract-OCR. From the experimental results the verification process can be improved by using OCR specific on specific regions of interest (ROI) after using template matching method from OpenCV. The consideration of the Levehnstein distance in the comparison of label values against the reference database also improves the success rate of the algorithm. The database used has been tested for about 800 grade report documents, with successful verification result above 90%.

Rancang Bangun E-Commerce B-To-B pada PT. Mitra Kabel Indonesia Cabang Makassar Burhan, Muhammad Ikhwan; Nawir, Fadliyani; Jariah, Putri Ainun
Jurnal Manajemen Perbankan Keuangan Nitro Vol. 7 No. 1 (2024): Januari 2024
Publisher : LP2M IBK Nitro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56858/jmpkn.v7i1.209

Penelitian ini dilatarbelakangi oleh banyaknya permintaan barang PT. Mitra Kabel Indonesia cabang Makassar dari daerah-daerah, dimulai dari Sulawesi, Nusa Tenggara, Bali hingga ke Papua. Banyaknya proses transaksi dari permintaan tersebut tidak lepas dari banyak kendala sehingga menyebabkan kerugian pada perusahaan karena harus mengeluarkan biaya yang seharusnya tidak perlu. Berdasarkan hal tersebut, dibutuhkan sistem perdangangan elektronik (E-Commerce) agar transaksi lebih efektif dan efisien. Jenis penelitian yang digunakan pada penelitian ini adalah jenis penelitan kualitatif, dengan metode pengumpulan data yaitu observasi, wawancara dan riset kepustakaan. Pengembangan aplikasi ini menggunakan metode waterfall melalui tahapa-tahapan seperti analisa kebutuhan, desain sistem, penulisan kode program, pengujian program dan penerapan program. Adapun teknik metode pengujian yang digunakan pada penelitian ini adalah menggunakan metode pengujian Black Box. Hasil penelitian menunjukkan tujuan penelitian sudah tercapai serta didukung dengan oleh hasil pengujian yang menyatakan bahwa output yang dihasilkan oleh sistem sudah sesuai dengan yang diharapkan. Data juga telah tersimpan pada database dengan akurat sehingga sistem yang telah dibuat menjadi efektif.

Bayesian Intelligent Tutoring System for Vocational High Schools Muhammad Ikhwan Burhan; Arsan Kumala Jaya; Luthon Adira
PENA TEKNIK: Jurnal Ilmiah Ilmu-Ilmu Teknik VOLUME 9 NUMBER 1 MARCH 2024
Publisher : Faculty of Engineering, Andi Djemma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51557/pt_jiit.v9i1.2415

The absence of individualized tutorials during regular school hours has resulted in a suboptimal learning method at Vocational High Schools(SMK), limiting students' ability to reach their optimum competency. Several Computerized self-study systems have been created as potential solutions to these challenges. Regrettably, a notable drawback of the system lies in its failure to address students' diverse range of abilities adequately. This study presents a proposed model for an Intelligent Tutoring System (ITS) utilizing the Bayesian Network (BN) at Vocational High Schools. The model aims to assess students' proficiency levels and deliver skill-based instructional materials tailored to individual students' abilities. This type of research is called research and development (RD), to develop and know the validity of a product. The system under development will undergo trials within the Computer and Network Engineering (TKJ) program at SMK Negeri 4 Gowa. These trials will employ a quasi-experimental approach, explicitly utilizing a one-group pretest-posttest design.The findings indicated that there were notable disparities in the learning outcomes of students following the implementation of the proposed ITS. To put it otherwise, the proposed ITS has improved students' proficiency in Vocational High Schools. The evaluation outcomes suggest that the BN model had a significant level of accuracy, reaching 84%.

Sentiment Analysis of Bapenda South Sulawesi Mobile Application on Google Play Store Using Support Vector Machine Burhan, Muhammad Ikhwan; Ali, Andi Nurfadillah; Auliyah, A. Inayah; Hading, Muhaimin
Journal of Mathematics and Applied Statistics Vol. 2 No. 2 (2024): December 2024
Publisher : Yayasan Insan Literasi Cendekia (INLIC) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35914/mathstat.v2i2.244

This study analyzes user sentiment toward the Bapenda Sulsel Mobile application, an e-government platform developed by the Regional Revenue Agency of South Sulawesi, Indonesia. The research aims to evaluate user feedback and identify areas for improvement to enhance user satisfaction. Using sentiment analysis, user reviews from Google Play Store were collected and classified into positive, negative, and neutral sentiments through the Support Vector Machine (SVM) algorithm. Preprocessing steps such as tokenization, stopword removal, and stemming were applied to prepare the data. Term Frequency-Inverse Document Frequency (TF-IDF) was used for feature extraction to enhance classification accuracy. The SVM model demonstrated an overall accuracy of 80%, achieving a high recall of 98% for positive reviews but only 40% for negative reviews, reflecting challenges in handling class imbalance. Results show that 72% of users expressed positive sentiment, praising the app’s functionality and ease of use. However, 28% of reviews were negative, citing issues like technical bugs and usability challenges The findings highlight the app’s strengths in delivering e-government services and its role in improving tax management. However, the significant proportion of negative feedback emphasizes the need for addressing user concerns. Recommendations include balancing the dataset, refining the SVM model, and prioritizing improvements based on user feedback. This study contributes to the broader understanding of applying sentiment analysis in evaluating e-government platforms and offers actionable insights for enhancing the user experience.

PENGEMBANGAN SISTEM TRACER STUDY MENGGUNAKAN AGILE DEVELOPMENT METHODS PADA IBK NITRO Burhan, Muhammad Ikhwan; Nawir, Fadliyani; Salam, Karta Negara
JURSIMA Vol 10 No 3 (2022): Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.439

Institut Bisnis dan Keuangan Nitro telah melakukan berbagai upaya dalam menghasilkan lulusan yang berkualitas dan dapat bersaing dalam dunia kerja, termasuk melaksanakan tracer study untuk memetakan kebutuhan dunia kerja dengan kompetensi yang diajarkan. Namun dalam implementasinya, tracer study berjalan tidak efektif dan memiliki banyak kendala karena masih dilaksanakan secara manual dan sangat sederhana. Salah satu upaya yang dilakukan untuk mengoptimalkan dan mengatasi kendala tersebut adalah mengembangkan sistem berbasis website yang mampu menunjang proses penyebaran dan pengisian kuesioner, penyimpanan data, maupun kemudahan dalam pelaporan. Agile Deveplopment Methods dengan kerangka kerja Extreme Programming digunakan dalam pengembangan sistem tracer study pada Institut Bisnis dan Keuangan Nitro karena mempunyai sifat adaptif dan responsif terhadap perubahan, serta proses pengembangan hanya membutuhkan waktu relatif singkat tanpa mengurangi kualitas sistem. Berdasarkan tahapan pengembangan sistem menggunakan Agile Deveplopment Methods dengan kerangka kerja Extreme Programming telah terjadi tiga kali iterasi (perulangan) fase pengembanga. Iterasi pertama menghasilkan prototype awal sesuai dengan kebutuhan pengguna; iterasi kedua menghasilkan prototype lanjut dengan penambahan beberapa kebutuhan pengguna; dan iterasi ketiga menghasilkan sistem yang siap rilis dan telah memenuhi semua kebutuhan pengguna.Kata Kunci : Tracer Study, Agile Deveplopment Methods, Extreme Programming.

ANALISIS SENTIMEN PUBLIK TERHADAP APLIKASI MYPERTAMINA PADA GOOGLE PLAYSTORE Burhan, Muhammad Ikhwan
Jurnal Manajemen Perbankan Keuangan Nitro Vol. 8 No. 1 (2025): Volume 8, Nomor 1, Januari 2025
Publisher : LP2M IBK Nitro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56858/jmpkn.v8i1.390

This study aims to analyze public sentiment towards the MyPertamina application on Google Playstore in order to understand user perceptions and identify the main problems faced. The method used is machine learning-based sentiment analysis with the optimized Support Vector Machine (SVM) algorithm. Data was obtained from user reviews on Google Playstore within a certain time period, then pre-processed and classified sentiment into positive, negative, or neutral. The results showed that the majority of reviews were positive, but there were a number of negative reviews that reflected technical and policy challenges in using the application. The SVM model managed to achieve an accuracy of 85.31%, indicating effectiveness in identifying public sentiment. These results are expected to help PT Pertamina in improving the quality of MyPertamina application services.

Comparative Analysis of Algorithms for Sensitive Outlier Protection in Privacy Preserving Data Mining Burhan, Muhammad Ikhwan; Ali, Andi Nurfadillah; Auliyah, A. Inayah; Hading, Muhaimin
Jurnal Tekno Kompak Vol 19, No 2 (2025): AGUSTUS (In Progress)
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtk.v19i2.4754

Data mining is a crucial method in the realm of Big Data for extracting valuable predictive insights from extensive datasets. In the contemporary digital landscape, a significant difficulty is preserving individual privacy during data mining, particularly in safeguarding sensitive outliers that may harbour personal information. Outliers are data points that markedly diverge from the overall trend and frequently encompass very specialised or sensitive information. This paper examines the comparative efficacy of various clustering algorithms employed in outlier detection, specifically PAM (Partitioning Around Medoids), CLARA (Clustering Large Applications), CLARANS (Clustering Large Applications Based on Randomised Search), and ECLARANS (Enhanced CLARANS). This study aims to evaluate the efficacy of each algorithm in identifying outliers and to examine the usefulness of the employed privacy protection strategy, specifically the Gaussian Perturbation Random method. This experiment utilises two health datasets: the Diabetes Dataset from the National Institute of Diabetes and Digestive and Kidney Diseases and the Wisconsin Breast Cancer Dataset. The two datasets were chosen because to their multivariate features, which exhibit adequate data variation for outlier detection. The study's results indicate that the CLARA algorithm effectively identified a superior quantity of outliers compared to the other algorithms, with the diabetes dataset exhibiting the greatest count of outliers (65 outliers). The CLARA algorithm shown superiority in identifying outliers within extensive datasets due to the utilisation of a sampling methodology. Conversely, the PAM, CLARANS, and ECLARANS algorithms identified a same quantity of outliers in both datasets. ECLARANS shown superior time efficiency on the diabetic dataset, but CLARA demonstrated the highest efficiency on the breast cancer dataset. The Gaussian Perturbation Random technique was employed for preserving the identified sensitive outliers. The findings indicate that this strategy effectively maintains privacy while ensuring detection accuracy is not compromised. This method provides a dependable means of safeguarding individual privacy in health data mining, a domain characterised by significant privacy concerns.

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