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All Journal JURNAL REKAYASA SISTEM INDUSTRI Jurnal Industri Kreatif (JIK) JATI (Jurnal Mahasiswa Teknik Informatika) Engineering and Technology International Journal (EATIJ) JURNAL PENGABDIAN MASYARAKAT AKADEMISI JT-IBSI (Jurnal Teknik Ibnu Sina) JR : Jurnal Responsive Teknik Informatika The Indonesian Journal of Computer Science Jurnal Responsive Teknik Informatika
Laurensius Setyabudhi, Albertus
Universitas Ibnu Sina
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences

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Analisis Kepuasan Pelayanan di UPTD Metrologi Legal Kota Batam pada Sektor Industri dengan Metode Importance Performance Analysis (IPA) dan Customer Satisfaction Index (CSI) Alamsyah, Nanang; Widodo, Trenggono Tri; Setyabudhi, Albertus Laurensius; Rifanti
Jurnal Teknik Ibnu Sina (JT-IBSI) Vol. 6 No. 01 (2021): Jurnal Teknik Ibnu Sina (JT-IBSI)
Publisher : Fakultas Teknik Universitas Ibnu Sina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jt-ibsi.v6i01.259

Abstract

Kepuasan pelanggan merupakan salah satu sasaran mutu yang harus dicapai dalam setiap pelayanan. Berdasarkan Undang-Undang Nomor 25 Tahun 2009 tentang Pelayanan Publik, seluruh instansi pemerintahan wajib menerapkan pelayanan sesuai dengan standar. Unit Pelaksana Teknis Daerah (UPTD) Metrologi Legal Kota Batam merupakan salah satu instansi pemerintah yang bergerak dalam bidang jasa tera/tera ulang terhadap alat ukur yang digunakan dalam kegiatan perdagangan. Berfungsi untuk memastikan keadilan transaksi yang dilakukan. Dalam hal ini tidak hanya kepuasan wajib tera saja, namun juga kepuasan masyarakat. Penelitian ini dilakukan dengan menggunakan kuesioner dan metode perhitungan Importance Performance Analysis (IPA) dan Customer Satisfaction Index (CSI) dengan objek wajib tera dan masyarakat pengguna Stasiun Pengisian Bahan Bakar Umum (SPBU). Metode Importance Performance Analysis (IPA) digunakan untuk mengidentifikasi tingkat kepentingan setiap atribut pelayanan dan Customer Satisfaction Index (CSI) digunakan untuk mengetahui tingkat kepuasan wajib tera dan masyarakat secara keseluruhan. Berdasarkan hasil penelitian, metode Importance Performance Analysis (IPA) untuk pengguna SPBU sebesar 94% dan Wajib Tera sebesar 96%. Sedangkan perhitungan metode Customer Satisfaction Index (CSI), untuk pengguna SPBU sebesar 75,55% dan Wajib Tera sebesar 82,73%. Dapat dikatakan bahwa UPTD Metrologi Legal Kota Batam telah memberikan kinerja terbaiknya pada Wajib Tera dan hasil tera/tera ulang yang dilakukan UPTD Metrologi Legal Kota Batam kepada Wajib Tera telah sampai dan dirasakan manfaatnya kepada masyarakat luas.
RANCANG BANGUN SISTEM INFORMASI ABSENSI PEGAWAI DI SDN 010 BULANG BERBASIS WEBSITE Fernandes, Atman Lucky; Veza, Okta; Arifin, Nofri Yudi; Setyabudhi, Albertus Laurensius; Larisang, Larisang; Ade Kurnia, Riska
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 3 (2024): JATI Vol. 8 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i3.9160

Abstract

Penggunaan teknologi informasi digital di Indonesia, terutama di lembaga pendidikan, semakin berkembang pesat. Salah satu aspek kritis adalah pengelolaan absensi pegawai, yang sering kali masih mengandalkan proses manual.Penelitian ini menyoroti permasalahan pengelolaan absensi pegawai di SD Negeri 010 Bulang, Batam. Proses manual yang saat ini digunakan menyebabkan ketidakakuratan dan ketidakefisienan data absensi. Penelitian bertujuan untuk merancang dan mengimplementasikan sistem informasi absensi pegawai berbasis web dengan memanfaatkan teknologi barcode di SDN 010 Bulang.Metode pengembangan sistem menggunakan model waterfall, yang terkenal dengan pendekatan sistematis dan berurutan dalam mengembangkan sistem informasi.Hasil penelitian mencakup analisis kebutuhan fungsional, desain sistem, penerapan antarmuka, dan pengujian. Sistem informasi absensi pegawai yang dihasilkan dapat digunakan dengan baik, meskipun masih memerlukan pengembangan lebih lanjut untuk optimalitas kinerja
Analisa Pengendalian Persediaan Bahan Baku Digipass pada Perusahaan Industri Elektronik (Study Kasus di PT.Venturindo Jaya Batam) Yusdinata, Zeri; Setyabudhi, Albertus Laurensius; Mulyani, Eka
Jurnal Teknik Ibnu Sina (JT-IBSI) Vol. 4 No. 01 (2019): Jurnal Teknik Ibnu Sina (JT-IBSI)
Publisher : Fakultas Teknik Universitas Ibnu Sina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jt-ibsi.v4i01.90

Abstract

PT.Venturindo Jaya Batam,adalah perusahaan yang bergerak dibidang manufaktur yang beralamat di Batu Ampar kota Batam. PT. Venturindo Jaya Batam merupakan salah satu perusahaan yang mengalami masalah pada pengendaliaan persediaan bahan baku, khususnya bahan baku LCD, dimana LCD merupakan bahan baku utama yang dibutuhkan pada saat berlangsungnya proses produksi. Pengendalian bahan baku yang digunakan adalah PCB, Dioda,Buzzer, kapasitor, resistor, LCD, Front Cassing, Back Cassing dan lain sebagainya. Permintaan produksi digipass pada PT. Venturindo Jaya Batam, yang berfluktuasi dan tidak terduga. Tujuan dari penelitian ini adalah penentuan pemesanan bahan baku yang optimum untuk meminimalkan total biaya persediaan dengan menggunakan pengendalian persediaan bahan baku dengan metode Material Requirement Planning (MRP).
Perancangan Sistem Informasi Pengolahan Data Absensi dan Pengambilan Surat Cuti Kerja Berbasis Web Albertus Laurensius Setyabudhi
Jurnal Responsive Teknik Informatika Vol. 1 No. 01 (2017): JR : Jurnal Responsive Teknik Informatika
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jr.v1i01.213

Abstract

Perancangan sistem informasi ini berbasis web untuk menyajikan informasi pengolahan data absensi dan pengambilan surat cuti kerja dalam industri dengan menggunakan Pemrograman PHP dan MySQL. Tujuan dari sistem ini adalah merancang, mengelola dan mengimplementasikan pengambil cuti kerja pada perusahaan. Rancangan sistem informasi ini menggunakan pemodelan data flow diagram, relation diagram. Implementasi dari sistem informasi ini ditujukan agar proses pengambilan surat izin cuti kerja dapat lebih efektif dan efisien. Sistem ini berbasis pemrograman HTML 5, sehingga dapat diakses dengan menggunakan perangkat browser.
Perancangan Sistem Informasi Pengolahan Data Absensi dan Pengambilan Surat Cuti Kerja Berbasis Web Albertus Laurensius Setyabudhi
Jurnal Responsive Teknik Informatika Vol. 1 No. 01 (2017): JR : Jurnal Responsive Teknik Informatika
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jr.v1i01.213

Abstract

Perancangan sistem informasi ini berbasis web untuk menyajikan informasi pengolahan data absensi dan pengambilan surat cuti kerja dalam industri dengan menggunakan Pemrograman PHP dan MySQL. Tujuan dari sistem ini adalah merancang, mengelola dan mengimplementasikan pengambil cuti kerja pada perusahaan. Rancangan sistem informasi ini menggunakan pemodelan data flow diagram, relation diagram. Implementasi dari sistem informasi ini ditujukan agar proses pengambilan surat izin cuti kerja dapat lebih efektif dan efisien. Sistem ini berbasis pemrograman HTML 5, sehingga dapat diakses dengan menggunakan perangkat browser.
Analysis and Design of Web-based Internal Office Memo (IOM) Management System Veza, Okta; Larisang, Larisang; Setyabudhi, Albertus Laurensius; Arifin, Nofri Yudi; Syofiawan, Doni; Martino, Hisar Gusdian
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3511

Abstract

This research focuses on the design and implementation of a web-based Internal Office Memo (IOM) Management System in the PT InnoArk Servis Internasional Optipedia Team. The main problem relates to ineffective communication and coordination between divisions, which results in backlogs and repetition of work as well as difficulties in monitoring task progress. The research method adopts a System Development Life Cycle (SDLC) approach with a waterfall model and uses the Unified Modeling Language (UML) for system design. Implementation was carried out by utilizing the CodeIgniter framework and MySQL as a database, followed by black box testing of the requirements testing type. The result is a system that successfully improves operational efficiency, team collaboration, and transparency of work progress. This application not only overcomes communication obstacles, but also provides a basis for making better decisions based on actual data, maintaining the smooth implementation of tasks, and improving the quality of team collaboration in the PT InnoArk Servis Internasional Optipedia Team.
Comparative Simulation of EfficientNetB0, ResNet50, and MobileNet for Cocoa Pod Disease Detection Okta Veza; Nofri Yudi Arifin; Sherly Agustini; Albertus Laurensius Setyabudhi
Jurnal Responsive Teknik Informatika Vol 9 No 01 (2025): JR : Jurnal Responsive Teknik Informatika
Publisher : LPPM Universitas Ibnu Sina Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jr.v9i01.1515

Abstract

The selection of a convolutional neural network (CNN) architecture for cocoa (Theobroma cacao) pod disease detection involves a trade off between classification accuracy and computational efficiency that is decisive for eventual deployment on the mobile hardware available to smallholder farmers. This study presents a controlled comparative simulation of three widely used architectures, EfficientNetB0, ResNet50, and MobileNetV2, under identical, literature-grounded conditions. Rather than reporting field-validated results, a balanced synthetic dataset of 3,000 images spanning four classes (healthy, black pod, pod borer, frosty pod) was generated with class-conditional feature statistics parameterized from published references. All three models were initialized with ImageNet weights, fine-tuned with an identical training protocol and shared data splits, and evaluated on the same held-out test set. In simulation, EfficientNetB0 achieved the highest accuracy (93.8%) and macro F1 (0.938), followed by ResNet50 (92.7%, 0.926) and MobileNetV2 (91.1%, 0.909). When efficiency is considered, the ranking shifts: MobileNetV2 offered the smallest footprint and lowest latency, EfficientNetB0 delivered the best accuracy-per-parameter, and ResNet50 was the most resource-intensive without a commensurate accuracy gain. The dominant error mode across all models was confusion between pod borer and frosty pod. The results indicate that EfficientNetB0 offers the most favorable accuracy efficiency balance for this task, while MobileNetV2 is preferable under strict on-device constraints. All figures are framed explicitly as simulation outputs and discussed in light of the synthetic-to-real domain gap
Comparative Simulation of EfficientNetB0, ResNet50, and MobileNet for Cocoa Pod Disease Detection Okta Veza; Nofri Yudi Arifin; Sherly Agustini; Albertus Laurensius Setyabudhi
Jurnal Responsive Teknik Informatika Vol 9 No 01 (2025): JR : Jurnal Responsive Teknik Informatika
Publisher : LPPM Universitas Ibnu Sina Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jr.v9i01.1515

Abstract

The selection of a convolutional neural network (CNN) architecture for cocoa (Theobroma cacao) pod disease detection involves a trade off between classification accuracy and computational efficiency that is decisive for eventual deployment on the mobile hardware available to smallholder farmers. This study presents a controlled comparative simulation of three widely used architectures, EfficientNetB0, ResNet50, and MobileNetV2, under identical, literature-grounded conditions. Rather than reporting field-validated results, a balanced synthetic dataset of 3,000 images spanning four classes (healthy, black pod, pod borer, frosty pod) was generated with class-conditional feature statistics parameterized from published references. All three models were initialized with ImageNet weights, fine-tuned with an identical training protocol and shared data splits, and evaluated on the same held-out test set. In simulation, EfficientNetB0 achieved the highest accuracy (93.8%) and macro F1 (0.938), followed by ResNet50 (92.7%, 0.926) and MobileNetV2 (91.1%, 0.909). When efficiency is considered, the ranking shifts: MobileNetV2 offered the smallest footprint and lowest latency, EfficientNetB0 delivered the best accuracy-per-parameter, and ResNet50 was the most resource-intensive without a commensurate accuracy gain. The dominant error mode across all models was confusion between pod borer and frosty pod. The results indicate that EfficientNetB0 offers the most favorable accuracy efficiency balance for this task, while MobileNetV2 is preferable under strict on-device constraints. All figures are framed explicitly as simulation outputs and discussed in light of the synthetic-to-real domain gap
Simulation Study of EfficientNetB0 Performance for Cocoa Pod Disease Classification Using Literature Based Synthetic Data Okta Veza; Sherly Agustini; Nofri Yudi Arifin; Albertus Laurensius Setyabudhi
Engineering and Technology International Journal Vol 7 No 03 (2025): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/eatij.v7i03.1335

Abstract

Automated detection of cocoa (Theobroma cacao) pod diseases such as black pod, pod borer infestation, and frosty pod rot is critical for safeguarding yield, yet the development of deep-learning classifiers is frequently constrained by the scarcity of curated, well-balanced image datasets. This study presents a controlled simulation that evaluates the expected performance envelope of an EfficientNetB0 classifier under idealized, literature-grounded conditions before field data collection is undertaken. Rather than asserting empirical field results, a synthetic dataset is constructed whose per-class feature distributions (color, texture, and lesion morphology) are parameterized from values reported across six core references. A balanced corpus of 3,000 synthetic images spanning four classes (healthy, black pod, pod borer, frosty pod) was generated and partitioned using a stratified 70/15/15 split. EfficientNetB0, initialized with ImageNet weights and fine-tuned with standard augmentation, achieved a simulated test accuracy of 93.8%, a macro-averaged F1-score of 0.926, and balanced per-class precision and recall in the 0.90-0.95 range. The confusion matrix indicates that the principal source of error is morphological overlap between pod borer and frosty pod presentations. The results delineate a plausible upper-bound performance band to guide sample-size planning, augmentation strategy, and architecture selection for a subsequent field study. All reported figures are framed explicitly as simulation outputs.
Deep Learning Approaches for Cocoa Pod Disease Classification A Literature Review Okta Veza; Nofri Yudi Arifin; Albertus Laurensius Setyabudhi
Engineering and Technology International Journal Vol 6 No 03 (2024): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/eatij.v6i03.1337

Abstract

Cocoa (Theobroma cacao) is a cornerstone of many tropical economies, yet its yield is persistently threatened by pod diseases such as black pod rot, frosty pod rot, and cocoa pod borer infestation. Over the past decade, deep learning, and convolutional neural networks (CNNs) in particular, has emerged as a powerful tool for automated plant disease diagnosis from images. This paper presents a structured literature review of deep-learning approaches applied, directly or by close analogy, to cocoa pod disease classification. Following a PRISMA style protocol, 41 studies published between 2016 and 2025 were selected from major databases and synthesized along five dimensions: data sources and dataset construction, preprocessing and augmentation, network architectures, training and transfer-learning strategies, and evaluation methodology. The review finds that transfer learning with compact architectures, notably ResNet, MobileNet, and EfficientNet variants, dominates recent work and consistently achieves reported accuracies above 90% on related tasks. Three persistent gaps are identified: the scarcity of large, balanced, and openly available cocoa specific image datasets; limited validation under realistic field conditions; and inconsistent reporting of evaluation metrics. The review concludes by outlining research directions, including domain adaptation, lightweight on device inference, explainability, and standardized benchmarking, to move cocoa pod disease classification from controlled experiments toward deployable tools for smallholder agriculture.
Co-Authors Abdurahman, Nandar Cundara Ade Kurnia, Riska Agustin Dwi Sumiwi Alamsyah, Nanang Amelia Rachmi Nasution Arifin, Nofri Yudi Cahyo, Yayan Nur Decky Antony Kifta Delia Meldra Djalil, Atika Nur Hikmah Doni Damara Doni Syofiawan Eci Ermawati Eka Mulyani, Eka Enggar Adi Sulityo Evis Saputra Fernandes, Atman Lucky Hutauruk, Sabam Mauliate Indah Kusuma Dewi, Indah Kusuma Larisang Lucky Agustin Martino, Hisar Gusdian Muhammad Bobbi Kurniawan Nasution Muhammad Rizki Reza Saputra Nandar Cundara Nandar Cundara Abdurahman Nandar Cundara, Nandar Nofri Yudi Arifin Nurul Alfika Okta Veza Putra, Bima Putri, Meylia Vivi Ramdhani Yusli Arbain Sugoro Rapani Rifanti Samad sherly agustini Sirait, Ganda Syofiawan, Doni Veza, Okta Widodo, Trenggono Tri Yayan Nur Cahyo Yuni Hardi Yusdinata, Zeri Yusdinata, Zeri Zaharani, Rafika Indah Zulfirman Syahputra Hasibuan