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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Masyarakat Informatika Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika
Indra Waspada
Department Of Informatics, Faculty Of Science And Mathematics, Diponegoro University, Tembalang, Semarang
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science

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The Design of Exploratory Application and Preprocessing of Event Log Data in LMS Moodle-Based Online Learning Activities for Process Mining Demaspira Aulia; Indra Waspada
Khazanah Informatika Vol. 5 No. 2 December 2019
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v5i2.8023

Abstract

Process Mining is one of the sub-studies of Data Mining that focuses on the events of a system. An area that benefits from process mining is education, especially online learning. This study used Moodle as a platform to provide online event activity log data in online learning. Moodle-based process mining requires several stages that are not easily understood directly by teachers. As a solution, some efforts are needed to integrate Moodle with process mining. This study built an application that could contribute to the Preprocessing and Exploratory Data Analysis (EDA) stages of Moodle event log data – as an important part of the process mining stage. Preprocessing was implemented by using the simple heuristic filtering method, while EDA was employed through visualization using flow control and dotted charts. Eventually, the application built in this study successfully performed preprocessing in Moodle event log data and could display the results visually, as a tool of control flow analysis and dotted chart analysis.
Hybrid ERC20 Ethereum Blockchain Multisignature Wallet 3of3 with Withdrawal Pattern, External Effects, and Mutex as Single Key and Reentrancy Mitigation. Sabda Dewa, Jason Al Hilal; Waspada, Indra; Sasongko, Priyo Sidik
Jurnal Masyarakat Informatika Vol 15, No 1 (2024): May 2024
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.15.1.62835

Abstract

In the rapidly evolving era of Decentralized Finance (DeFi), the convergence of Blockchain technology with intermediary-free financial services has forged a revolutionary landscape. However, this progress has been accompanied by critical challenges, notably the Single Key Risk and reentrancy attack threats against ERC20 smart contracts in private Ethereum Blockchain. This research formulated a proactive approach and implemented an innovative solution by embodying Reliable Decentralized Finance through the deployment of a 3-of-3 Hybrid Multisignature Wallet system with Withdrawal Pattern, External Effects, and Mutual Exclusion in the form of a Decentralized Application (DApps). The system not only applied withdrawal patterns but also integrated external effects and the principle of mutual exclusion to enhance the security of smart contracts. The system development methodology was executed comprehensively using Agile Software Engineering, encompassing the development of both smart contracts and external applications (decentralized applications). Testing was conducted using Ganache EVM (Ethereum Virtual Machine) connected to the Hot Wallet Metamask as an Externally Owned Account (EOA) for transaction signing. Valid results were obtained from comprehensive testing against the system's functional requirements, affirming the system's success in managing Single Key Risk and preventing reentrancy attacks, providing a reliable and concrete solution
Applying the Scrum Method in Software Development for Undergraduate Thesis Project Implementation Ramadhan, Attaf Riski Putra; Waspada, Indra; Bahtiar, Nurdin; Pramayoga, Adhe Setya
Jurnal Masyarakat Informatika Vol 16, No 1 (2025): May 2025
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.16.1.73187

Abstract

The Scrum Method, as one of the frameworks within Agile-based software development, has become the de facto standard in industry practices. However, to date, there is no specific guideline or adaptation model that directs the application of Scrum in undergraduate thesis project settings, particularly within the Bachelor of Informatics Study Program at Diponegoro University. In this program, the final project is carried out individually by a student under the supervision of two academic advisors, forming a small team structure that differs from conventional Scrum configurations. This study proposes an adaptation model of the Scrum method for such a scenario, assigning the roles of Product Owner and Tester to the First Supervisor, Scrum Master and Tester to the Second Supervisor, and Developer as well as Assistant to the Student. The implementation of Scrum in this context facilitates structured communication between supervisors and the student, while also supporting flexibility in accommodating changing requirements throughout the development process. Moreover, active stakeholder involvement during the requirements gathering and Sprint Review stages contributes to the enhanced quality of the final deliverable. The project was executed over four sprints within a total of 40 working days, covering 13 product backlog and several derivative tasks. The findings indicate that adapting Scrum to the context of a final project enables timely project completion with outcomes that are academically and technically accountable.
APLIKASI HYBRID PADA SISTEM INFORMASI PENYEWAAN BUKU Pradana, Dimas Iqbal; Waspada, Indra
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 1 (2019): JURNAL SIMETRIS VOLUME 10 NO 1 TAHUN 2019
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1449.579 KB) | DOI: 10.24176/simet.v10i1.2600

Abstract

Saat ini persewaan buku konvensional mengalami permasalahan dalam manajemen data, pemberian informasi  koleksi  buku,  serta  transaksi  penyewaan yang  mengharuskan penyewa  untuk  mendatangi tempat persewaan buku. Untuk itu diperlukan suatu sistem informasi yang dapat mendukung transaksi penyewaan.  Penggunaan  smartphone  yang   memiliki   akses   internet   sudah   menjadi  hal   umum. Pemanfaatan aplikasi mobile yang mendukung akses internet dalam pengembangan sistem informasi penyewaan buku dapat memberi kemudahan penggunaan dan akses informasi yang cepat bagi penyewa buku. Beragamnya jenis mobile platform menyebabkan pengembangan aplikasi mobile native menjadi tidak efisien, baik dalam aspek waktu maupun biaya pengembangan. Sebagai solusinya, teknologi mobile hybrid dapat mengatasi masalah tersebut. Berdasarkan latar belakang tersebut maka dibangun aplikasi mobile hybrid pada sisi klien sistem informasi penyewaan buku menggunakan framework Ionic. Klien ini terhubung dengan aplikasi back-end web administrator melalui RESTful Web Service.
Implementasi Data Mining untuk Deteksi Penyakit Ginjal Kronis (PGK) menggunakan K-Nearest Neighbor (KNN) dengan Backward Elimination Gamadarenda, Ikhsan Wisnuadji; Waspada, Indra
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 2: April 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020721896

Abstract

Penyakit ginjal kronis (PGK) merupakan masalah kesehatan publik di seluruh dunia dengan insiden yang terus meningkat. Berdasarkan sumber dari BPJS Kesehatan, perawatan PGK merupakan ranking kedua pembiayaan terbesar setelah penyakit jantung. Pendeteksian PGK juga memerlukan banyak atribut sehingga membutuhkan biaya yang cukup mahal. Oleh sebab itu dibuat sistem dengan tahapan data mining berbasis web yang memudahkan untuk melakukan deteksi PGK, sehingga PGK dapat dicegah, ditanggulangi, dan kemungkinan mendapatkan terapi yang efektif lebih besar jika diketahui lebih awal. Proses penelitian ini menggunakan sebuah rangka kerja data mining Knowledge Data Discovery (KDD). Dalam skenario rangka kerja yang digunakan, sistem ini menggunakan Algoritme Backward Elimination untuk mengurangi jumlah atribut yang dipakai dengan tujuan untuk mengurangi jenis pemeriksaan yang dilakukan, dan Algoritme k-Nearest Neighbor sebagai algoritme klasifikasi untuk mendeteksi penyakit. Hasil pemodelan terbaik data mining dari sistem yang dibuat menggunakan Backward Elimination (α = 0,05) dan kNN (k = 3) dengan pertimbangan penurunan biaya pemeriksaan dan sensitivity tertinggi. Rekomendasi sistem menghasilkan 10 atribut yang terpilih dari 24 atribut awal yang digunakan, yaitu: berat jenis (sg), albumin (al), urea darah (bu), kreatinin serum (sc), sodium (sod), hemoglobin (hemo), sel darah merah (rbc), hipertensi (htn), diabetes mellitus (dm), dan nafsu makan (appet). Penggunaan atribut yang telah terseleksi tersebut, berhasil menekan biaya pemeriksaan hingga 73,36%. Selanjutnya dilakukan pendeteksian penyakit menggunakan Algoritme k-Nearest Neighbor menghasilkan nilai akurasi sebesar 99,25%, sensitivity sebesar 99,5%, dan specificity sebesar 98,745%.AbstractChronic kidney disease (CKD) is a health problem for people around the world with increasing incidence. Based on sources from BPJS Kesehatan, CKD care is the second largest ranking of financing after heart disease. CKD detection also requires many attributes, so it requires quite expensive costs. Create a system with web-based data mining stages that makes it easy to detect CKD. Allowing CKD to be prevented, addressed, and advised to get effective therapy is greater if acknowledged earlier. The process of this research uses work methods of Data Mining Knowledge Data Discovery (KDD). In the framework of the framework used, this system uses the Backward Elimination Algorithm to reduce the number of attributes used to reduce the type of inspection performed, and the k-Nearest Neighbor Algorithm as an algorithm to update disease. The best data mining modeling results from the system are made using Backward Elimination (α = 0.05) and kNN (k = 3) by calculating the increase in inspection costs and the highest sensitivity. System recommendations produce 10 attributes selected from the 24 initial attributes used, namely: specific gravity (sg), albumin (al), blood urea (bu), serum creatinine (sc), sodium (soil), hemoglobin (hemo), cell red blood (rbc), hypertension (htn), diabetes mellitus (dm), and appetite (appetite). The use of the selected attributes succeeded in achieving inspection costs of up to 73.36%. Furthermore, disease detection using the k-Nearest Neighbor Algorithm produces an accuracy value of 99.25%, sensitivity of 99.5%, and specificity of 98.745%.
Co-Authors Abidah Elcholiqi, Abidah Adhe Setya Pramayoga, Adhe Setya Adi Wibowo Aprilia, Ayu Riana Devi Aprilia, Ayu Riana Devi Aulia, Demaspira Awan, Bagus Dwi Ari Beta Noranita Demaspira Aulia Egga Bahartyan, Egga Gamadarenda, Ikhsan Wisnuadji Istanto, Adik M. Fakhri Darmawan, M. Fakhri Mohamad Endy Y Yulianto Nikmatun, Inna Alvi Noel Segura Meraz Nurdin Bahtiar Panji Wisnu Wirawan Pradana, Dimas Iqbal Pradana, Dimas Iqbal Priyo Sidik Sasongko Putri, Ratna Puspita Sari Putut Sri Wasito Ramadhan, Attaf Riski Putra Ratna Puspita Sari Putri Sabda Dewa, Jason Al Hilal Sarwo Dwi Waskito, Sarwo Dwi Selvina Selvina Sutikno Sutikno Sutikno Sutikno Wendi E Wendi E Wijayanto, Danur Zainal Abidin