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Angelia Putriana
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INDONESIA
Jurnal Sains dan Teknologi
Published by Yayasan Literasi Sains Indonesia
ISSN : 28284992     EISSN : 28284984     DOI : https://doi.org/10.55123/insologi
Core Subject : Health, Science, Education, Agriculture, Engineering,
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Dentistry Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary
INSOLOGI (Jurnal Sains dan Teknologi) diterbitkan 6 (enam) kali dalam setahun, yaitu pada bulan Februari, April, Juni, Agustus, Oktober dan Desember oleh Yayasan Literasi Sains Indonesia. Jurnal INSOLOGI adalah jurnal yang dapat diakses secara terbuka bagi para Peneliti, Dosen dan Mahasiswa yang ingin mempublikasikan hasil penelitiannya pada bidang ilmu sains dan teknologi. Jurnal INSOLOGI juga merupakan wadah informasi berupa hasil penelitian, studi kepustakaan, gagasan, aplikasi teori dan kajian analisis kritis dibidang perkembangan sains dan teknologi yang meliputi bidang ilmu pengetahuan alam (biologi, kimia, dan fisika), matematika dan statistik, perikanan/kelautan, kesehatan dan farmasetika, pertanian (agribisnis dan agroteknologi), keteknikan (teknik sipil, mesin, arsitektur, lingkungan, dan pertambangan), pengembangan/desain miniatur/rancang bangun dan bidang ilmu lainnya yang relevan dengan penelitian sains dan teknologi.
Arjuna Subject : Matematika - Matematika Terapan
Articles 428 Documents
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Korelasi Sifat Fisik Biodiesel Campuran Jatropha - Kedelai: Densitas, Viskositas, Titik Nyala dan Nilai Kalor Wahyudi, Wahyudi
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 3 (2025): Juni 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i3.5191

Abstract

The physical properties of biodiesel—such as density, viscosity, flash point, and calorific value—play a crucial role in determining its combustion performance, safety, and compatibility with diesel engines. This study aims to evaluate the correlation between these physical properties in biodiesel blends derived from various ratios of jatropha and soybean oil. Biodiesel was produced using standard esterification and transesterification processes. Each sample was then tested using ASTM-standard methods to determine density, viscosity, flash point, and higher heating value (HHV). The results revealed strong linear correlations among the measured parameters. Density exhibited a positive correlation with viscosity (R² = 0.8834) and flash point (R² = 0.9655), but a negative correlation with HHV (R² = 0.8312). Additionally, flash point was positively correlated with HHV (R² = 0.8416). These findings confirm that the blend ratio significantly influences biodiesel properties and that increasing soybean content improves heating value while reducing viscosity. The established correlations provide a scientific basis for formulating biodiesel blends that optimize combustion efficiency, enhance engine performance, and ensure safe handling and storage, thereby supporting more sustainable energy solutions.
Analisis Kualitas Wine Menggunakan Machine Learning dengan Pendekatan SMOTE dan Seleksi Fitur Triandes Sinaga; Kevin Bastian Sirait; Pangaribuan, Jefri Junifer; Barus, Okky Putra; Romindo, Romindo
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 3 (2025): Juni 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i3.5436

Abstract

Conventional wine quality assessment remains reliant on subjective expert judgment, which introduces potential bias and inconsistency in quality control processes. This study aims to develop an objective and automated machine learning-based classification model to enhance the accuracy of wine quality prediction. To address the issue of class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied, along with ANOVA F-test-based feature selection to optimize model performance. The White Wine Quality dataset from the UCI Machine Learning Repository (4,898 samples, 11 numerical features) was utilized to evaluate five classification algorithms: Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN). Before SMOTE application, the Random Forest model achieved an accuracy of only 67.55%. After implementing SMOTE and parameter tuning, the Random Forest (Tuned) model demonstrated the best performance with 90.29% accuracy, 89.99% precision, 90.29% recall, and 89,97%.  % F1-score. Additionally, Decision Tree and KNN algorithms also exhibited notable improvements. SMOTE effectively balanced extreme minority class representations (quality levels 3 and 9). The most influential features in quality classification were alcohol content, density, and chlorides. These findings indicate that the proposed framework offers a reliable, objective, and scalable solution for automated wine quality control in industrial production environments.
Analisis Perbedaan Kekuatan Struktur Kolom Akibat Tsunami pada Gedung Laboratoriom Dinas PUPR Kota Banda Aceh Mhd. Arief Diana; Michel Kasaf; Taufik, Taufik; Anwar, Khairul; Pitri, Deni Trianda
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 3 (2025): Juni 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i3.5510

Abstract

The earthquake and subsequent tsunami that struck Banda Aceh at the end of 2004 caused extensive damage to various infrastructures, including the Laboratory Building of the Public Works Department of Banda Aceh City. This study aims to evaluate the variation in concrete strength between columns that were submerged during the tsunami and those that remained unaffected. A non-destructive testing (NDT) method was employed, using a Concrete Hammer Test device to assess the condition of the concrete. The testing was conducted on first-floor columns, with each column section tested 12 times at intervals of 3 cm between points. The results indicate a significant reduction in compressive strength, with the most severe decline observed in column K.6.4, where a 57% strength loss was recorded due to porous concrete conditions. The smallest reduction was found in columns K.1.9 and K.6.5, both showing a 5% decrease, while column K.1.7 exhibited no detectable deterioration. Overall, the majority of columns experienced notable degradation in structural integrity, underscoring the necessity for further comprehensive evaluations to determine the building’s continued feasibility and safety for use.
Deteksi Dini Stroke Menggunakan Machine Learning Kevinda Sari; Muhammad Fadli; Fudholi, Muhammad Fahmi; Susanto, Erliyan Redy
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.5590

Abstract

Stroke is one of the leading causes of death and disability worldwide. Early detection of stroke risk is crucial to prevent more severe complications. This study aims to develop a stroke prediction model based on machine learning using an open dataset from Kaggle containing patients' medical and demographic information. Four machine learning algorithms were utilized and compared: AdaBoost, Gradient Boosting, LightGBM, and XGBoost. Data preprocessing steps included missing value imputation, categorical variable encoding, numerical feature normalization, and class balancing using the SMOTEENN method. Additionally, feature selection was performed using the Extra Trees algorithm to enhance model performance. The results showed that the XGBoost model delivered the best performance, achieving an accuracy of 97.16%, an F1-score of 97.49%, and an AUC of 99.75%. This model proved to be effective in detecting stroke cases and holds potential for integration into clinical decision support systems. The study concludes that a combination of modern boosting algorithms and optimal preprocessing techniques can yield a reliable stroke prediction system suitable for implementation in digital healthcare contexts.
Analisa Faktor Eksternal Pemanfaatan Internet of Things pada Industri Minyak Kayu Putih Suyanto, Suyanto; Tantri Yanuar Rahmat Syah; Edi Hamdi; Sunaryanto, Ketut
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.5685

Abstract

PT. Fear Densu Farm is a manufacturing company engaged in the eucalyptus oil industry in Indonesia, with a cutting-edge technology-based approach that utilizes the Internet of Things (IoT). This business planning project is designed to create a sustainable, efficient, and innovative eucalyptus oil ecosystem through the integration of digital technology into every aspect of its operations to address the imbalance between demand and supply of eucalyptus oil in Indonesia. This business is rooted in Indonesia's great potential as a producer of essential oils, including eucalyptus oil. With a tropical climate and abundant natural resources, Indonesia has the capacity to become a global leader in this industry. However, various challenges still hinder the progress of this sector, such as low quality raw materials, lack of efficiency in the production process, and dependence on imports to meet domestic needs. This study aims to identify and evaluate external factors that influence the implementation of Internet of Things (IoT) technology in the eucalyptus oil industry, so that it can provide a clear picture of external opportunities and challenges that impact the effectiveness and efficiency of IoT utilization in this
Implementasi Teknologi Flaudized Bed Cover (FBD) dan Perencanaan Human Capital untuk Peningkatan Kualitas Garam Indonesia di PT. Ladang Garam Indonesia Muhammad Iqbal Ramadhan; Tantri Yanuar Rahmat Syah; Dimas Angga Negoro; Ruswanti, Endang
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.5688

Abstract

PT Ladang Garam Nasional (PT LGN) aims to be a pioneer in the caustic soda salt industry in Indonesia by utilizing modern technology to meet the needs of the national chemical industry. This project is driven by Indonesia's dependence on industrial salt imports, especially for the chemical sector, which reaches more than 3 million tons per year. With the establishment of a factory in Tegal, Central Java, PT LGN will produce high-quality salt with a NaCl content of ≥99% through Fluidized Bed Dryer (FBD) technology and apply the principles of Good Manufacturing Practice (GMP). The global industrial salt market is projected to grow by 2.4% per year. PT LGN takes advantage of this opportunity by offering products that meet the specific needs of the caustic soda industry. This project will also support the government's program for salt self-sufficiency, create jobs, and reduce imports. The method used in this study is a qualitative approach with case studies on several industrial salt processing companies that have adopted advanced technology. The results of the study indicate that mature internal planning, including supply chain management, production management, and quality control, is very important in increasing the competitiveness of the salt industry. This study provides recommendations for salt processing companies to maximize the potential of technology in supporting business planning and HR management, as well as increasing global market competitiveness.
Implementasi E-Commerce di Toko The Familly Collection Desa Panjangsari Kecamatan Gombong Kabupaten Kebumen Salma Anisa Rinanti; Endang Wahyuningsih
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.5694

Abstract

Retail businesses are increasingly using e-commerce platforms in the quickly changing digital age in order to reach a wider audience, increase operational effectiveness, and satisfy changing customer demands. For The Familiy Collection Store, a fashion and family accessory firm, to be competitive in a changing and difficult market, it must integrate e-commerce in a suitable and well-thought-out manner. The purpose of this study is to evaluate and create an e-commerce platform that is specifically suited to the requirements of The Familiy Collection Store's operations. A user-friendly and responsive interface design, quick and secure integration of a digital payment system, effective and real-time inventory management, and the application of data-based marketing strategies and consumer behavior to boost customer engagement are the primary goals in the development of this platform. In order to gather thorough and precise insights, this study's methodologies include a review of the literature on e-commerce, an analysis of current developments in the digital business, and in-depth interviews with important stakeholders. It is envisaged that by using this strategy, the created e-commerce platform will be able to improve customer happiness, attract a wider audience, fortify the brand, and significantly and sustainably contribute to the long-term success of the business.
Inovasi Sistem Electronic Nose untuk Monitoring Kualitas Oli dan Deteksi Dini Kerusakan Ring Piston pada Mesin Kapal Nelayan (Studi Kasus: Kampung Nelayan Desa Kronjo) Ikhwanuddin, Ikhwanuddin; M. Anang Jatmiko; A. Nur Fajri Irwan; Ferro Hidayah; Juliaster Marbun
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.5700

Abstract

Electronic Nose system to optimize fishing vessel engine maintenance through in situ oil quality monitoring. This system integrates four gas sensors (TGS 813, TGS 822, TGS 2600, TGS 2602) with a DC pump and Arduino Uno, enabling early detection of piston ring damage without disassembling the engine. It detects volatile compounds in the oil, such as heavy metals and acidic substances caused by piston friction, using the iontophoresis method.Sensor readings for normal piston rings are: TGS2600 (410–600 mV), TGS2602 (200–210 mV), TGS813 (55–60 mV), TGS822 (70–110 mV); for worn rings: TGS2600 (540–730 mV), TGS2602 (330–350 mV), TGS813 (100–107 mV), TGS822 (90–150 mV); and for scratched rings: TGS2600 (480–690 mV), TGS2602 (220–245 mV), TGS813 (80–90 mV), TGS822 (100–200 mV).With real-time damage detection, this technology reduces repair time, cuts operational costs, and extends engine life. Additionally, it supports lower carbon emissions and oil waste, contributing to environmental sustainability. The adoption of Nautical Guardian is expected to improve the productivity and income of fishermen, particularly in Kronjo Fishing Village, Tangerang City
Pengaruh Variasi Konsentrasi Asam pada Pembuatan Bioetanol dari Buah Kumbi (Voacanga foetida (Bl.) ROLFE) melalui Proses Hidrolisis Sulwiyatul Kamariyah Sani
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.5702

Abstract

Currently, the availability of petroleum and natural gas as non-renewable energy sources is steadily decreasing. One alternative energy source that can be developed for the future is bioethanol, as it is renewable and environmentally friendly. The kumbi fruit (Voacanga foetida (Bl.) ROLFE) is a potential raw material for bioethanol production due to its cellulose content, which can be converted into bioethanol. The objective of this study was to investigate the effect of acid concentration on the hydrolysis process in the production of bioethanol from kumbi fruit. In this study, hydrolysis was carried out using HCl at concentrations of 1%, 2%, 3%, 4%, and 5% (v/v) at 70°C for 90 minutes. To determine the reducing sugar content produced, the hydrolysate was analyzed using UV-Vis spectrophotometry. The hydrolysate was then fermented using baker's yeast containing Saccharomyces cerevisiae for 72 hours. The fermentation product was distilled at 78°C, and the obtained bioethanol was analyzed using GC-MS. The results showed that the highest reducing sugar concentration was obtained at 2% acid concentration, amounting to 7.18 g/L, while the highest crude bioethanol yield was 47.64%, achieved at 4% acid concentration with a reducing sugar content of 1.04 g/L.
Evaluasi Kinerja Diagnostik dan Pemasaran Tes ColoSTAT Berbasis Darah untuk Deteksi Dini Kanker Kolorektal di Indonesia Munatsir Oteiba; Tantri Yanuar Rahmat Syah; Edi Hamdi; Muhammad Reza Hilmy
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 4 (2025): Agustus 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i4.5760

Abstract

This study aims to evaluate the diagnostic performance of the blood-based ColoSTAT test as an early detection method for colorectal cancer while analyzing the marketing aspects of the product in Indonesia. The ColoSTAT test offers a non-invasive approach with ease of sampling and potentially high accuracy in detecting colorectal cancer at an early stage. The ColoSTAT test is a non-invasive method that utilizes specific biomarkers in the blood to identify the presence of colorectal cancer. This study method involves testing blood samples in populations at risk of colorectal cancer at several hospitals in Indonesia, and comparing the ColoSTAT test results with clinical diagnostic standards such as colonoscopy and biopsy. Diagnostic performance parameters analyzed include sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the test. The results indicate that the ColoSTAT test has competitive diagnostic performance and strong market potential if supported by an appropriate marketing strategy. The technological and marketing implications of the ColoSTAT test include increasing colorectal cancer screening coverage, reducing the burden on primary healthcare services, and increasing the effectiveness of colorectal cancer control in Indonesia.

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