E-Journal Politeknik Negeri Cilacap
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Pembuatan Briket Berbahan Arang Bambu dan Batok Kelapa sebagai Energi Alternatif
Full text linkThe utilization of biomass as a renewable energy source represents a strategic alternative to reduce dependence on fossil fuels while promoting the sustainable use of organic waste. This study aims to evaluate the effect of varying ratios of bamboo charcoal and coconut shell charcoal, with coconut husk charcoal and binder composition kept constant, on the combustion characteristics of biomass briquettes, including ignition time, burning duration, and maximum combustion temperature. The research was conducted experimentally through biomass pyrolysis at a temperature of 300 °C for 10 hours, followed by material mixing, briquette molding, and combustion testing. The results indicate that variations in raw material composition significantly influence briquette combustion behavior. Briquettes with higher bamboo charcoal content exhibit faster ignition, whereas those dominated by coconut shell charcoal produce longer burning duration and higher combustion temperatures. The observed combustion behavior is qualitatively discussed based on differences in biomass characteristics as reported in the literature. These findings demonstrate that blending biomass with different combustion properties can achieve more balanced briquette performance
Implementasi Agile Scrum Pada Pengembangan Website untuk Manajemen Barang PT Alita Praya Mitra
Full text linkPT Alita Praya Mitra is a company engaged in the field of Information and Communication Technology (ICT). In the process of managing Bill of Quantity (BoQ) data, the company does not yet have an integrated system, and data processing is still carried out conventionally, which requires a considerable amount of time. This condition causes the processes of recording, processing, and retrieving data to be less efficient and potentially prone to errors. Therefore, one possible solution is the development of an integrated web-based inventory management system. The system was developed using the Agile Scrum methodology, which consists of several stages, including user stories, product backlog, sprint planning, sprint backlog, and daily scrum. This method was chosen because it supports gradual and flexible system development based on user needs. Based on the testing results, the system has been successfully implemented and named the PO Management Tools. The implementation results show that the system can accelerate the BoQ data processing process and improve work efficiency. In addition, Agile Scrum has proven to support system development effectively even with a small development team
Pemberdayaan Masyarakat Lokal: melalui Pelatihan Pembuatan Komposter dan Dampaknya untuk Ekowisata Berkelanjutan di Pamboborang
Full text linkOrganik waste management is a major challenge in developing ecotourism in Pamboborang Village, Majene Regency, West Sulawesi. This community service activity aimed to empower the local community, particularly the blacksmith group, through training in simple composter construction to support sustainable organik waste management. The applied methods included a one-day intensive workshop, one-month post-training mentoring, and pre-test and post-test evaluations using structured questionnaires. The training involved constructing composters using two lidded buckets, perforated PVC pipes, and a leachate tap. The results indicated a 70% increase in participants’ knowledge, with the highest improvement (40%) in technical aspects of composter making. Post-training monitoring showed that 80% of participants continued to use the composters after three months. This activity provided environmental benefits through a 40% reduction in organik waste and socio-economic benefits by increasing awareness of cleanliness and promoting compost utilization for local agriculture. The novelty of this program lies in its integration of technical training with a community-based mentoring system, which enhances the sustainability of ecotourism development in Pamboborang.
Optimalisasi Digital Marketing dalam Promosi dan Jaringan di SMKS Wikrama 1 Garut -
Full text link The advancement of digital technology compels educational institutions to optimize digital media-based promotional strategies to enhance the visibility and competitiveness of schools. In a specific context, SMKS Wikrama 1 Garut faces challenges in the form of limited human resources, variations in digital literacy, and the absence of a consistent and structured digital marketing strategy. Although many studies emphasize the role of digital marketing in educational institutions, there is still a knowledge gap that includes a lack of integration of technology adoption theory, utilization of internal resources, and long-term relationship strategies in the context of vocational schools in rural areas. This research employs a qualitative-descriptive approach through in-depth interviews, field observations, and document analysis to explore the current conditions and strategies for optimizing digital marketing in schools. The results of the study show that the use of platforms such as Instagram, TikTok, Facebook, and YouTube is still sporadic, lacks data-driven approaches, and does not optimally showcase the school\u27s vocational identity and narrative; content management is influenced by low perceptions of ease of use, limited strategic resources, and the absence of an editorial calendar; while the use of short videos and storytelling has been proven to generate the highest engagement but has not been implemented consistently. The analysis also identified that school websites have not been optimized through SEO, and collaboration with alumni and industry has not been maximized as strategic content. This research implicitly emphasizes the necessity of a theory-based digital marketing strategy, utilizing data and internal resources to enhance promotion while simultaneously establishing sustainable institutional networks.
Penyelidikan Kampas Rem Komposit Matriks Aluminium Diperkuat Boiler-Fly-Ash dan Silika Terhadap Nilai Densitas dan Kekerasannya
Full text linkThis study aims to investigate the effect of the percentage of reinforcement and hot compaction pressure on the density value of Aluminum Matrix Composite brake pads, reinforced with Boiler-Fly-Ash and silica sand. The Powder Metallurgy method was used in this study, with variations in the weight fraction of reinforcement being 6%, 10%, and 14%. Mixing of the matrix powder and reinforcement was performed using a Ball Mill Machine, with a Ball Powder weight Ratio of 10:1, within 6 hours of mechanical alloying at a speed of 90 rpm. The molding process used a hot compaction system in the form of a Hydraulic Jack machine with an upper press and a lower press, with a hot pressing temperature of 350 ºC, a holding time of 10 minutes, at a pressure variation of 5200 Psi, 5600 Psi, and 6000 Psi. The sintering process used a temperature of 600 ºC at a holding temperature of 10 minutes. The density test of the specimen uses the ASTM B962-17 standard with the Archimedes theory approach, while the hardness test uses the Brinnel Hardness, referring to ASTM E110-14. The result, the highest average density value is 2.10 g/cm³ with a reinforcement percentage variation of 10%, while the lowest density value is 1.90 g/cm³ with a reinforcement percentage of 14%. The highest hardness value is 42.93 HB with a percentage of 10%, while the lowest hardness value is 41.4 HB with a reinforcement percentage of 14% compaction of 6000 PsiPenelitian ini menyelidiki pengaruh persentase penguat dan tekanan kompaksi panas terhadap nilai densitas dan kekerasan kampas rem AMC diperkuat Pasir Silika dan Boiler Fly Ash. Penelitian ini menggunakan metode Powder Metallurgy (P/M), dengan variasi penguat 6%, 10%, dan 14%. Mixing menggunakan Ball Mill Machine perbandingan Ball Powder weight Ratio 10:1 waktu 6 jam kecepatan 90/menit. Proses pencetakan digunakan mesin Hydraulic Jack berpenekan dari atas dan bawah dengan suhu penekanan panas 300 ºC waktu tahan 10 menit. Variasi tekanan yang digunakan 5200 Psi, 5600 Psi, dan 6000 Psi. Perlakuan sintering 600 ºC dalam Holding Time 10 menit. Uji densitas ASTM B962-17 dan uji kekerasan ASTM E110-14. Hasil yang didapatkan, nilai densitas tertinggi 2,055 g/cm³ dengan persentase 10% kompaksi 5600 Psi. Nilai densitas terendah 1,848 g/cm³ dengan persentase penguat 14% kompaksi 5600 Psi. Nilai kekerasan tertinggi 47,3 HB ada pada persentase 10% kompaksi 5600 Psi. Nilai kekerasan terendah 39,4 HB persentase penguat 10% kompaksi 6000 Psi
Pengaruh Variasi Waktu Curing Pada Kegagalan Uji Bending Komposit Sandwich Serat Karbon Dengan Core PVC Foam
Full text linkCuring is a method used to enhance the performance of composite materials by heating them in an electric oven for a specific duration and at a controlled temperature. This study aims to examine the effect of curing time variations on the failure analysis of carbon fiber sandwich composites with a PVC foam core under bending tests. The materials used in this research include polyester resin, 240 gsm carbon twill fiber, and a 5 mm thick PVC foam core. The manufacturing method applied was vacuum bagging, followed by a curing process with time variations of 30 minutes, 60 minutes, 90 minutes, and 120 minutes at a constant holding temperature of 80°C. Bending tests were carried out according to ASTM C393 standards. The highest bending strength of the sandwich composite was achieved with a curing time of 120 minutes, reaching 45.55 MPa, while the lowest strength was observed in the specimen without curing, at 25.76 MPa. The failures observed after bending tests included core failures such as core crush, indentation, and delamination, as well as skin failures like micro buckling
Pengembangan Sistem Pendeteksi Tekanan Ban Berbasis Internet of Things untuk Otomatisasi Inspeksi Kendaraan
Full text linkTire pressure inspection is a crucial procedure at PT HMMI based on the Part Inspection Standard (PIS), with a recommended pressure of 105-125 Psi for buses. Currently, inspections are still performed manually, deemed inefficient and prone to human error. To address this and meet inspection standards, this research aims to develop an Internet of Things (IoT)-based bus tire pressure detection system. The Research and Development (R&D) method was applied to design and build this system. The developed system utilizes a pressure transmitter sensor integrated with an ESP32 microcontroller, equipped with LCD, LED, and buzzer outputs. Pressure measurement data is transmitted in real-time and stored in Google Spreadsheet for paperless documentation. Functional testing of the system on buses demonstrated the sensor\u27s detection capability within 2-3 seconds with all outputs functioning optimally. Accuracy test results showed excellent performance, reaching 99.44% with an average error of only 0.56% after calibration with 30 pressure parameters. This system successfully proved its capability as an effective solution for automatically and accurately monitoring bus tire pressure, supporting the achievement of PIS standards and enhancing the efficiency of inspection processes in the automotive industry
Pengembangan Model Machine Learning Berbasis Linear Discriminant Analysis (LDA) untuk Deteksi Gejala Penyakit Jantung Menggunakan Python
No full textHeart disease is the leading cause of death globally and is often not detected early due to limited awareness and the high cost of medical diagnosis. This study aims to develop an accurate and efficient prediction model for heart disease using the Linear Discriminant Analysis (LDA) algorithm. The dataset, obtained from Kaggle, contains 1,024 patient records with 14 clinical attributes, including age, blood pressure, cholesterol, and ECG results. The preprocessing steps include handling outliers, duplicates, class imbalance using SMOTE, and feature standardization. The model was evaluated using cross-validation and learning curve analysis. Results show that the optimized LDA model, tuned with GridSearchCV, achieved an accuracy of 82.54%, a recall of 88.91%, a precision of 79.03%, and an F1-score of 83.54%. The model demonstrates balanced and stable performance, although some misclassification in the positive class remains. This study highlights LDA as a promising method for the early detection of heart disease based on structured clinical data.Sistem peredaran darah manusia memegang peranan penting dalam tubuh, dengan fungsi utama mengedarkan oksigen dan nutrisi serta mengangkut sisa metabolisme. Jantung, sebagai organ vital dalam sistem ini bertindak sebagai pompa darah. Penyakit jantung adalah penyebab utama kematian global dengan lebih dari 7,3 juta kematian setiap tahun. Penyakit kardiovaskular (PKV) meliputi berbagai kondisi seperti penyakit jantung koroner, hipertensi, stroke, dan gagal jantung. Kesadaran masyarakat terhadap pola hidup sehat dan infromasi mengenai penyakit jantung masih rendah, menyebabkan banyak orang tidak mengenali gejala awalnya. Deteksi manual penyakit jantung membutuhkan biaya yang besar, sehingga diperlukan sistem deteksi yang akurat dan terjangkau. Penelitian ini bertujuan untuk membuat model machine learing menggunakan metode Linear Discriminant Analysis (LDA) dengan python untuk mendeteksi gejala penyakit jantung secara efektif, terjangkau, dan akurat. Hasil menunjukkan bahwa model menunjukkan performa baik dengan metrik yang seimbang namun masih ada beberapa kesalahan klasifikasi yang masih bisa diperbaiki
Pengaruh Komposisi Bahan Baku dan Kadar Perekat Tepung Tapioka Terhadap Kualitas Briket dari Campuran Daun Ketapang dan Tempurung Kelapa
Full text linkKetapang leaves are an example of biomass that can be used to make briquettes. However, ketapang leaves produce a low calorific value, so they require additional ingredients to increase the calorific value, one of which is coconut shell. This research aims to evaluate how variations in raw material composition and adhesive content of tapioca flour affect the quality of briquettes on the parameters of calorific value, water content, ash content, volatile substances, fixed carbon content, and density. The method applied in this research involved mixing ketapang leaf charcoal and coconut shell charcoal, then adding adhesive in the form of tapioca flour. The study results showed that all the briquettes tested met SNI 8966-2021 standards except for the density parameter. The conclusion of this study is that the greater the composition of the briquette raw materials and the lower the adhesive content of tapioca flour, the better the quality of the briquettes. The mixed briquettes that produce the best quality are composed of 20% Ketapang leaf charcoal and 80% coconut shell charcoal. The tapioca flour adhesive that delivers the best quality briquettes is at a percentage of 5%.Daun ketapang merupakan contoh biomassa yang dapat dimanfaatkan menjadi briket. Namun, daun ketapang menghasilkan nilai kalor yang rendah sehingga membutuhkan bahan tambahan untuk meningkatkan nilai kalor, salah satunya adalah tempurung kelapa. Penelitian ini bertujuan untuk mengevaluasi bagaimana variasi komposisi bahan baku dan kadar perekat tepung tapioka memengaruhi kualitas briket. Metode yang diterapkan dalam penelitian ini melibatkan pencampuran arang daun ketapang dan arang tempurung kelapa, lalu ditambahkan perekat berupa tepung tapioka. Hasil studi menunjukkan bahwa semua briket yang diuji sudah memenuhi standar SNI 8966-2021 kecuali pada parameter densitas. Kesimpulan dari studi tersebut adalah semakin banyak komposisi bahan baku briket dan semakin rendah kadar perekat tepung tapioka maka kualitas briket akan semakin baik. Briket campuran yang menghasilkan kualitas terbaik adalah pada komposisi 20% arang daun ketapang : 80% arang tempurung kelapa. Perekat tepung tapioka yang menghasilkan kualitas briket terbaik adalah pada persentase 5%
Evaluasi Kinerja Model Machine Learning dalam Klasifikasi Penyakit THT: Studi Komparatif Naïve Bayes, SVM, dan Random Forest
Full text linkClassification of Ear, Nose, and Throat (ENT) diseases is essential to support faster and more accurate diagnosis. However, no prior studies have specifically compared the performance of Naïve Bayes, Support Vector Machine (SVM), and Random Forest algorithms in ENT cases. This study aims to evaluate and compare the three classification models in identifying ENT diseases with or without comorbidities. Medical record data were processed through preprocessing, feature selection using ANOVA, and class balancing with SMOTE. The results showed that SVM outperformed the other models with the highest accuracy (59%), followed by Random Forest (57%), and Naïve Bayes (48%). SVM demonstrated superior performance due to its consistent scores across all evaluation metrics. The study concludes that the choice of classification model significantly impacts the accuracy of ENT disease diagnosis