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All Journal International Journal of Supply Chain Management Jurnal Ekonomi Manajemen Sistem Informasi Scientific Contributions Oil and Gas
Taufik Roni Sahroni
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Chemical Engineering, Chemistry & Bioengineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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Application of Theory of Constraint Supply Chain Replenishment System in Fast Moving Consumer Goods Company Taufik Roni Sahroni; Margaretha Margaretha; Dyah Budiastuti
International Journal of Supply Chain Management Vol 6, No 4 (2017): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.161 KB)

Abstract

Todays market competitiveness has reached its peak since the rapid growth of industrial and technology development. The market dominance aims to fulfill the consumer supply and demand, by giving excellent service, such as stabilizing the finished goods inventory level in the right time and quantity.XYZ is one of the Fast Moving Consumer Goods (FMCG) Company which has several problems in supplying their product to market. Actual market condition and demand become the main factor why the company is unable fulfilling the right product to its consumer, despite the Production Planning and Inventory Control (PPIC) segment has made the right production target based on the Purchase Order and Selling Target from Distributors Company. Thus, further development by combining supply chain management system with several theory of constraints is required to manage the material inventory and finished goods, which meet the consumer needs such as integrated master production schedule, market demand condition, finished goods inventory, and material replenishment by suppliers.
Klasifikasi Cacat Permukaan Keramik Menggunakan Logistic Regression dan SVM Berbasis CNN Inggrid Nindia Aprila Palupi; Budiyan Mariyadi; Imam Yuadi; Taufik Roni Sahroni
Jurnal Ekonomi Manajemen Sistem Informasi Vol. 7 No. 4 (2026): Jurnal Ekonomi Manajemen Sistem Informasi (Maret - April 2026)
Publisher : Dinasti Review

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jemsi.v7i4.7551

Abstract

Klasifikasi dalam mendeteksi cacat permukaan pada ubin keramik merupakan langkah penting dalam memastikan kualitas produk di industri manufaktur. Klasifikasi yang akurat sangat diperlukan untuk meningkatkan kualitas hasil produksi dan mengurangi kesalahan faktor manusia. Penelitian ini bertujuan untuk deteksi dan klasifikasi secara akurat pada jenis cacat baik yang bertekstur 2D dan 3D. Metode yang diusulkan dengan menggunakan Logistic Regression dan dibandingkan dengan Support Vector Machine. Dalam Penelitian ini menggunakan 133 data jenis cacat yang diambil menggunakan kamera smartphone dengan sudut 45˚. Proses pelatihan menggunakan 66% data yang dilatih dengan model Inception V3, VGG-16 dan VGG-19 kemudian 34% data jenis cacat untuk pengujian. Logistic Regression dan Support Vector Machine dengan Inception V3 memberikan hasil klasifikasi terbaik dengan akurasi dan presisi 0,99 dengan kemampuan untuk klasifikasi 100% jenis cacat seperti gompal, lubang, terkelupas, retak dengan tekstur 2D. Sedangkan VGG-19 dapat melakukan klasifikasi 100% pada jenis cacat gelembung dengan tekstur 3D. Waktu pelatihan dan pengujian Logistic Regression dengan Inception V3 6,9 dan 2,1 detik dan VGG-19 membutuhkan waktu pelatihan dan pengujian 53,8 dan 5,36 detik. Sedangkan Support Vector Machine dengan Inception V3 membutuhkana waktu pelatihan dan pengujian 6,6 dan 4,7 detik, sedangkan VGG-19 membutuhkan waktu pelatihan dan pengujian 10,1 dan 4,7 detik.
Evaluating Global Oil Data Reporting Consistency and Stability with Insights from Indonesia Taufik Roni Sahroni; Lulut Alfaris; Siagian, Ruben Cornelius; Andri Wahyudi; Anas Noor Firdaus; Ukta Indra Nyuswantoro
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.2010

Abstract

Transparent and consistent oil data reporting is a critical component of global energy governance and market stability. This study evaluates the consistency, stability, and overall quality of global oil data reporting from 2002 to 2025 using the dataset of the Joint Organizations Data Initiative (JODI), with Indonesia employed as a regional reference case. The principal indicators applied include the Index of Reporting Consistency (IRC), the Reporting Volatility Index (RVI), and the Oil Data Availability Index (ODAI). Countries are classified according to market role (producer or importer), economic grouping, and geographical region. The analysis further incorporates K-means clustering and structural change detection to assess temporal stability and responsiveness to major global shocks. The findings reveal substantial variation in reporting performance across countries. Nations exhibiting high IRC values and low RVI scores generally possess more mature institutional and statistical capacities, whereas those with low IRC scores tend to face governance or data management constraints. Oil-producing countries typically demonstrate higher ODAI values but display greater vulnerability to systemic crises, while importing countries show relatively more stable reporting patterns. Major global shocks in 2008, 2014, 2020, and 2022 exerted asymmetric impacts on producers and importers, highlighting structural vulnerabilities within the global energy reporting system. Indonesia demonstrates consistently strong reporting performance, with an ODAI value of 0.944, exceeding the averages of ASEAN (0.889) and OPEC (0.829). The country records a non-reporting rate of only 5.6% and a maximum non-reporting duration of ten months. This study addresses a gap in long-term, shock-sensitive analyses and introduces an integrated framework combining IRC, RVI, and ODAI as a novel approach for assessing oil data reporting quality. The findings provide a foundation for strengthening institutional capacity, enhancing regional coordination, and developing crisis-resilient reporting systems, while positioning ODAI as a practical indicator for evaluating energy governance and policy transparency.
Co-Authors Andri Wahyudi Budiyan Mariyadi Dyah Budiastuti Firdaus, Anas Noor Imam Yuadi Inggrid Nindia Aprila Palupi Lulut Alfaris Margaretha Margaretha Siagian, Ruben Cornelius Ukta Indra Nyuswantoro