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Smart City Maturity Analysis Based on COBIT 2019 and SNI ISO 37122:2019 Ahkam, Syuaib; Ginardi, R. V. Hari
International Journal of Organizational Behavior and Policy Vol 4 No 2 (2025): JULY 2025
Publisher : Accounting Department, School of Business and Management - Universitas Kristen Petra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/ijobp.4.2.53-64

Abstract

In the current era of digital transformation, the development of Smart City is crucial for regions that want to improve public services, stimulate economic growth, and improve the quality of life of their citizens. West Sumbawa Regency, with its tourism and creative economy potential, has adopted the Smart City initiative. However, its effectiveness is hampered by suboptimal IT governance, limited digital infrastructure, and a lack of standardized integrated evaluation models. This study aims to analyze and assess the maturity of Smart City in West Sumbawa Regency by combining the COBIT 2019 framework for IT governance and SNI ISO 37122:2019 for smart city performance indicators. Using a mixed-methods approach—including a survey of 150 stakeholders for quantitative analysis and in-depth interviews with 50 key informants for qualitative analysis—as well as PLS-SEM analysis, capability maturity assessment, and GAP analysis, the results show that most IT governance processes are at maturity levels 2–3. This indicates a significant gap between existing IT governance practices and the achievement of Smart City indicators, particularly in aligning corporate objectives and risk management. The main contribution of this research is the development of an integrated evaluation model that provides a holistic evidence-based roadmap for local governments to formulate more effective Smart City policies to achieve sustainable smart city transformation.
Identifikasi Penyakit pada Daun Tebu dengan Gray Level Co-Occurrence Matrix dan Color Moments Dewi, Ratih Kartika; Ginardi, R.V. Hari
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 1 No 2: Oktober 2014
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (819.699 KB) | DOI: 10.25126/jtiik.201412114

Abstract

Abstrak Karat dan mosaik adalah penyakit pada tebu yang menyerang tebu di Indonesia dan menimbulkan kerugian. Teknologi informasi untuk deteksi penyakit tebu diperlukan dalam menunjang peningkatan produksi tebu yang dapat menghasilkan panen optimal. Penelitian yang berkembang dalam identifikasi penyakit tanaman melalui identifikasi citra digital daun belum ada yang khusus membahas tebu, tetapi mengenai penyakit tanaman secara umum. Penelitian ini membangun sistem identifikasi penyakit pada daun tebu melalui identifikasi citra digital daun dengan pemilihan fitur tekstur dan warna melalui gray level co-occurrence matrix (GLCM) dan color moments. Tahap awal penelitian adalah pengumpulan data citra daun tebu berpenyakit dari survei lapangan. Tahap selanjutnya adalah pre-processing citra untuk dapat diolah ke tahap selanjutnya yaitu ekstraksi fitur. Ekstraksi fitur tekstur dilakukan dengan gray level co-occurrence matrix (GLCM) dan ekstraksi fitur warna dengan color moments. Klasifikasi dilakukan berdasarkan fitur yang telah diekstraksi sebelumnya. Penelitian ini menggunakan metode klasifikasi support vector machine (SVM). Pengujian dilakukan untuk mengetahui fitur yang kemunculannya menyebabkan perubahan dalam hasil klasifikasi dengan 4 skenario meliputi penghapusan fitur bentuk, pemilihan fitur tekstur, pemilihan fitur warna, dan kombinasi fitur tekstur dan warna. Kombinasi fitur tekstur dengan GLCM correlation, energy,  homogeneity dan variance bersama fitur warna dengan color moments 1,2 dan 3 yang diuji pada skenario 4 merupakan kombinasi fitur yang direkomendasikan untuk identifikasi penyakit pada daun tebu dengan akurasi 97%. Kata kunci: ekstraksi fitur, penyakit tebu, citra daun, GLCM, dan color moments. Abstract Mosaic and rust are sugarcane diseases that happen in Indonesia and has considerable economic impact. Information technology for sugarcane disease detection is useful in supporting optimal sugarcane production. Most of current researches are about plant disease identification in general. There is no specific research about identification of sugarcane disease. This research proposes a sugarcane disease identification from sugarcane leaf image with gray level co-occurrence matrix (GLCM) and color moments. This research begins with collecting data from field survey. After sugarcane leaf images are captured through a field survey, they are pre-processed in order to be used in the features extraction step. Extracted features from these images are texture and color. Texture feature extraction is conducted by GLCM while color feature extraction is conducted by color moments. Classification method which is used in this research is support vector machine (SVM). Test conducted to find distinctive feature that has a significant impact in classification, there are 4 scenario to test the effects in deletion of shape feature, selection of texture and color feature, and also combination of texture and color feature. Texture feature with GLCM correlation, energy,  homogeneity and variance combined with color moments 1, 2 and 3 for color feature extraction in 4th scenario is an appropriate feature for identification of sugarcane leaf disease with 97% classification accuracy. Keywords: feature extraction, sugarcane disease, leaf image, GLCM and color moments.
Komparasi Kinerja Algoritma C4.5, Gradient Boosting Trees, Random Forests, dan Deep Learning pada Kasus Educational Data Mining Mutrofin, Siti; Machfud, M. Mughniy; Satyareni, Diema Hernyka; Ginardi, Raden Venantius Hari; Fatichah, Chastine
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 4: Agustus 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020742665

Abstract

Penentuan jurusan di SMA Negeri 1 Jogoroto, Jombang, Jawa Timur menggunakan kurikulum 2013, di mana penentuan jurusan siswa tidak hanya melibatkan keinginan siswa, tes peminatan yang dilakukan siswa di SMA pada minggu pertama, tetapi juga dilengkapi dengan nilai siswa semasa di SMP (nilai rapor siswa, nilai Ujian Nasional, serta rekomendasi guru Bimbingan Konseling), rekomendasi orang tua siswa. Selama ini, sekolah menggunakan proses konvensional dalam menentukan jurusan, yaitu menggunakan Microsoft Excel, yang cenderung lama serta rawan akan kekeliruan dalam melakukan penghitungan. Penentuan jurusan ini dilakukan setiap awal ajaran baru pada siswa baru kelas X. Rata-rata setiap tahun, sekolah mengelola siswa sejumlah 290 dengan waktu dan sumber daya manusia yang terbatas. Pada penelitian ini, penggunaan algoritma ID3 tidak cocok karena data bertipe numerik, sedangkan ID3 hanya mampu menggunakan data bertipe nomial maupun polinomial, sehingga diganti algoritma C4.5. Namun, beberapa penelitian mengatakan algoritma C4.5 memiliki kinerja kurang bagus dibandingkan algoritma Gradient Boosting Trees, Random Forests, dan Deep Learning. Untuk itu, dilakukan perbandingan antara keempat metode tersebut untuk melihat keefektifannya dalam menentukan jurusan di SMA. Data yang digunakan pada penelitian ini adalah data penerimaan siswa baru tahun ajaran 2018/2019. Hasil dari penelitian ini menunjukkan jika atribut yang digunakan bertipe polinomial dengan Deep Learning memiliki kinerja paling unggul untuk semua algoritma jika menggunakan fungsi activation ExpRectifier. Sedangkan jika atributnya bertipe numerik, Deep Learning memiliki kinerja paling unggul untuk semua algoritma jika menggunakan fungsi Tanh untuk semua random sampling. Namun, Deep Learning memiliki kinerja paling buruk untuk semua algoritma jika menggunakan loss Function berupa absolut.  Abstract In SMAN 1 Jombang, East Java, the process of determining the students’ majors referred to the 2013 curriculum in which not only the students’ own choices and specialization tests conducted in their first week of SMA were considered but also the student’s SMP grades (a report card, UN scores, and counseling teacher’s recommendation) and parents' recommendation. So far, the school had used Microsoft Excel which required a long time to do and was prone to calculation errors in the process of determination. The process was carried out, with limited time and human resources, at the beginning of a new academic year for grade X students, consisting of 290 students on average. In this present research, the use of ID3 algorithm was not suitable because of its numeric data type instead of nominal or polynomial data. Thus, the C4.5 algorithm was applied, instead. However, the performance of C4.5 algorithm was proved lower than the algorithms of Gradient Boosting Trees, Random Forests, and Deep Learning. Hence, a comparison of performance between them was done to see their effectiveness in the process. The data was the list of new students of the academic year 2018/2019. The results showed that if the attributes are polynomial, the Deep Learning algorithm had the best performance when using the ExpRectifier activation function. When they were numeric, Deep Learning has the most superior performance when using the Tanh function. However, Deep Learning has the worst performance when using the loss function in the form of absolute.
Pengembangan Metode Information Retrieval dan Haversine Formula untuk Rekomendasi Penentuan Klinik di Kabupaten Jember Hizham, Fadhel Akhmad; Ginardi, Raden Venantius Hari
Journal of Informatics Development Vol. 1 No. 1 (2022): Oktober 2022
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v1i1.896

Abstract

Klinik merupakan fasilitas tempat orang berobat dan memperoleh advis medis serta tempat mahasiswa kedokteran melakukan pengamatan terhadap kasus penyakit yang diderita para pasien. Saat ini, hadirnya virus Corona (COVID-19) membuat banyak klinik menampung pasien yang terpapar virus tersebut. Dari kasus tersebut, rekomendasi penentuan klinik sangat diperlukan karena kondisi yang sangat darurat dan kasus positif yang bertambah setiap harinya. Pada penelitian ini, ditambahkan metode information retrieval, yaitu metode TF-IDF dan BM25 untuk menentukan rekomendasi klinik di Kabupaten Jember berdasarkan kata pencarian dari penggunanya dan diurutkan berdasarkan kemiripan (similarity) dari yang terbesar hingga yang terkecil. Sementara metode Haversine Formula digunakan untuk memilih klinik dengan jarak yang ditentukan oleh pengguna sebelumnya Penentuan rekomendasi klinik yang menggunakan metode gabungan information retrieval (similarity) + haversine dilakukan dengan formulasi rata-rata peringkat antara metode haversine dengan metode gabungan, dan formulasi normalisasi nilai similarity maupun nilai haversine. Hasilnya, ada 7 klinik yang menempati peringkat terbaik untuk metode gabungan dengan formulasi rata-rata peringkat, dan ada 47 klinik yang menempati peringkat terbaik untuk metode gabungan dengan formulasi normalisasi.
Evaluation of the Effectiveness of Audit Management System (AMS) Using COBIT 2019 and ISO 31000:2018 in the Internal Audit Function Miharja, Indra Setya; Ginardi, Raden Venantius Hari
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2627

Abstract

The Audit Management System (AMS) is utilized by the Internal Audit Function to manage audit processes in a structured, documented, efficient, and risk-aligned manner, aiming to provide added value to the organization. This system is supported by the Pentana Audit software, implemented across 22 entities, functioning as a secure platform that records the entire audit process in real-time. This study aims to identify gaps, analyze areas for improvement, assess potential financial and operational impacts, and provide recommendations and mitigation steps related to AMS management. The evaluation applies the COBIT 2019 and ISO 31000:2018 Risk Management frameworks, focusing on five Governance and Management Objectives from COBIT 2019: EDM03, APO12, APO14, DSS03, and MEA04. The novelty of this research lies in the dual-framework approach that systematically integrates COBIT and ISO standards to produce a strategic, risk aligned improvement roadmap. The specific focus on AMS within the Internal Audit context also contributes to strengthening governance and audit risk management. The findings indicate that AMS management has not yet reached full effectiveness, with 13 identified areas of improvement that may cause financial and operational impacts. Key issues include the lack of integration between the audit risk database and ERM, absence of automated notifications, no monitoring dashboard, inadequate data security policies, and suboptimal real-time utilization across entities. APO12 recorded the largest gap, primarily related to IT based audit risk management integration. Recommendations are categorized into three mitigation priorities using an action priority matrix: quick wins, important tasks, and other tasks, with phased implementation over three years.
Maturity Measurement of Information and Communication Technology Infrastructure Governance and Management in Mojokerto Regency using Cobit 2019 Susandik, Muzakir Adi; Hari Ginardi, Raden Venantius
Journal Research of Social Science, Economics, and Management Vol. 5 No. 4 (2025): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v5i4.1191

Abstract

Abstract. In the current era of digital transformation, local governments are responsible for providing convenient and fast services to the public. Therefore, adequate preparation of information and communication technology (ICT) infrastructure is crucial to supporting the digital transformation initiated by the Mojokerto Regency government. The Mojokerto Regency Communications and Information Technology Office (Diskominfo) faces several challenges related to managing ICT service infrastructure. These include the uneven distribution of ICT network infrastructure across all service departments and the lack of integration of data services within Diskominfo's data center. The purpose of this study is to examine the current situation and provide recommendations regarding the stages and priorities for managing ICT network infrastructure at Diskominfo. Therefore, an appropriate method is needed to identify the condition of the ICT infrastructure and evaluate its performance achievements using the COBIT 2019 framework. The research was conducted through problem identification, stakeholder discussions, data collection, data analysis, and reporting. The results of this study are a measurement of the maturity of ICT infrastructure governance and management, based on the COBIT 2019 framework with objective domain processes BAI02 Managed Requirements Definition, BAI03 Managed Solutions Identification and Build, BAI06 Managed IT Changes, and BAI10 Managed Configuration. These recommendations and suggestions can be used to further improve ICT governance and management services in all organizations.
Designing an Information Technology Governance Roadmap for Prioritising Initiatives Based on the COBIT 2019 Framework and Mcfarlan Grid Risk-Value Analysis Novianto, Hendi Novianto; Ginardi, Raden Venantius Hari
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 7 No. 1 (2026): INJIISCOM: VOLUME 7, ISSUE 1, JUNE 2026 (ONLINE FIRST)
Publisher : Universitas Komputer Indonesia

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

Abstract

The strategic role of information technology (IT) governance in preserving operational performance and competitive advantage is strengthened by digital transformation. Perusahaan Gas Negara (PGN), a state-owned company in the energy sector, finds it difficult to manage rising technological risks while coordinating IT investments with business priorities. In order to create an improvement roadmap, this study combines the COBIT 2019 framework with a Value-Risk prioritization technique using the McFarlan Strategic Grid. A qualitative descriptive case study was carried out using observation, capability assessments, literature reviews, and interviews. An average capability score of 3.67, which denotes a Defined/Established maturity level, was obtained from the evaluation of fifteen COBIT priority processes. The McFarlan analysis identified four Strategic, six Key Operational, one High-Potential, and seventeen Support initiatives. The final roadmap enhances governance effectiveness by improving strategic alignment, sequencing initiatives based on risk and value, and supporting executive decision making.
ANALISIS FAKTOR YANG MEMPENGARUHI NIAT ADOPSI STASIUN PENGISIAN KENDARAAN LISTRIK UMUM (SPKLU) OLEH PENGGUNA MOBIL LISTRIK DI INDONESIA DENGAN PENDEKATAN UTAUT2 Prasetya, Anggih; Suryani, Erma; Ginardi, Raden Venantius Hari
Journal of Economic, Bussines and Accounting (COSTING) Vol. 8 No. 6 (2025): COSTING : Journal of Economic, Bussines and Accounting
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/c67pec55

Abstract

Lonjakan adopsi Kendaraan Listrik (EV) di Indonesia, yang didorong oleh insentif masif, menuntut ketersediaan infrastruktur pengisian daya publik yang memadai. Keberhasilan target ambisius pemerintah menyediakan 62.918 unit SPKLU pada tahun 2030 sangat bergantung pada niat adopsi pengguna.  Penelitian ini penting karena ekosistem SPKLU menghadapi tantangan kritis, termasuk persebaran yang belum merata, isu keandalan dan tingginya Perceived Risk pengguna, yang menciptakan ketidakpastian dalam niat adopsi. Penelitian ini bertujuan mengidentifikasi faktor-faktor yang memengaruhi niat adopsi SPKLU berfokus pada konstruk utama UTAUT2 (Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition, Price Value), serta pengaruh dua faktor ekstensi krusial yaitu Perceived Risk dan Policy Incentives. Penelitian ini menggunakan pendekatan kuantitatif dengan data dikumpulkan melalui metode survei terhadap pengguna SPKLU menggunakan teknik pemodelan persamaan struktural (SEM) untuk menguji hipotesis dan mengidentifikasi hubungan kausalitas serta faktor dominan. Hasil penelitian ini menunjukan bahwa perceived risk, effort expectancy, dan performance expectancy terbukti berpengaruh positif dan signifikan terhadap niat adopsi SPKLU sedangkan social influence dan price value tidak menunjukkan pengaruh positif yang signifikan. Selain itu, facilitating condition tidak mampu memoderasi hubungan antara perceived risk dan niat adopsi SPKLU namun policy incentives terbukti dapat memoderasi pengaruh price value terhadap niat adopsi SPKLU.
Implementasi Gamifikasi Berbasis AI untuk Pembelajaran Interaktif: Studi Kasus pada Guru di SMA Negeri 5 Surabaya Sri Indrawanti, Annisaa; Ciptaningtyas, Henning Titi; Muchammad Husni; Khakim Ghozali; Ginardi, Raden Venantius Hari; Sutryotrisongko, Hatma; Hariadi, Ridho Rahman; Sholikah, Rizka Wakhidatus; Sabilla, Irzal Ahmad; Rosyadi, Fuad Dary; Firdausi, Hafara; Sunaryono, Dwi; Irin, Tio Axellino; Indranto, Dionisius Marcell Putra; Nasution, Hazwan Adhikara
Sewagati Vol 10 No 1 (2026): Pre-Printed
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v10i1.9315

Abstract

Pemanfaatan kecerdasan buatan (AI) memegang peranan krusial dalam modernisasi media ajar. AI memungkinkan personalisasi materi ajar sesuai kebutuhan siswa, memberikan umpan balik real-time, dan membantu guru dalam memahami kemajuan belajar secara efisien. Oleh karena itu, dalam kegiatan pengabdian masyarakat ini, tim dosen dan mahasiswa dari Departemen Teknologi Informasi Institut Teknologi Sepuluh Nopember menyelenggarakan pelatihan pengembangan media ajar berbasis tools AI untuk para guru di SMA Negeri 5 Surabaya. Melalui pelatihan ini, para guru dibekali kemampuan untuk mengadopsi beragam tools AI, dengan fokus pada penggunaan ChatGPT untuk perancangan ajar serta Wayground (Quizizz) dan Wordwall untuk gamifikasi pembelajaran, guna menunjang proses belajar yang lebih efektif dan interaktif. Rangkaian kegiatan ini mencakup tahap perencanaan, survei lokasi, penyusunan modul, pelaksanaan pelatihan selama dua hari, evaluasi, hingga pelaporan. Pelaksanaannya terbagi menjadi sesi penyampaian materi dan praktik langsung, yang diperkuat dengan pre-test dan post-test untuk mengukur peningkatan pemahaman. Hasilnya menunjukkan bahwa proses pengabdian berjalan sukses dengan partisipasi konsisten dari 54 guru. Antusiasme peserta sangat tinggi, yang tercermin dari keaktifan selama sesi, peningkatan signifikan pada hasil post-test, serta tingkat kepuasan yang sangat memuaskan.