Rekayasa ulang proses produksi bibit tanaman jati berkelanjutan pada pt harfam jaya makmur

Deforestation and degradation continue to occure. Forest management on a partnership basis with the community was also one of the methods of forest management to tackle deforestation. Forest and land rehabilitation is intended to restore, maintain and improve the functions of forests and land so that their carrying capacity, productivity and role in supporting life support systems are maintained. Forest rehabilitation activities that have been done including reforestation, maintenance, plant enrichment, and the application of vegetative and civil technical soil conservation techniques on critical and unproductive lands. Forest management on a partnership basis with the community were also one of the methods of forest management to tackle deforestation. PT. Harfam Jaya Makmur, as an agroforestry company were committed to supporting the provision of legal teak and supporting forest afforestation. Breeding efforts undertaken by PT. Harfam Jaya Makmur implemented by cooperating with BPPT as a partner to seek superior teak plant. Problems faced to create superior teak seedlings is the high cost of seed production, this causes PT. Harfam Jaya Makmur teak seed products has a higher price. The objectives of this research were 1) to know and to analyze the production process of teak seedlings, 2) to measure the performance of teak seed production process as parameter of re-engineering of sustainable teak forest business process, 3) to re-engineer the teak seed production process at PT. Harfam Jaya Makmur. The study was conducted on March 2015 - May 2017 in teak forests in Situbondo and Bondowoso regencies managed by PT Harfam Jaya Makmur. Business process revitalization will be done with value stream mapping approach. Value stream mapping analysis begins with creating value stream mapping current state, waste identification and measurement, waste analysis, and value stream mapping future state. Based on the results of Structural Equation Model (SEM) model analysis, there was known that all the main factors affecting the production process of teak seedlings at PT. Harfam Jaya Makmur is transportation, process, man, material and machine factors. The factor directly affecting each of main factors is the motion, while the indirectly affecting is based on motion, inventory, and defect factors. This condition shows that there are 3 factors becoming priorities in teak seed production system improvement at PT. Harfam Jaya Makmur with the priority ranks as follows: 1) transportation that directly and indirectly influence the occurrence of waste with a strong influence reaches 60.8%, 2) motion that directly or indirectly influence, strong influence 49.5% 3) defect that has an indirect effect on strong influence of 3.8%, 4) inventory that has an indirect effect on with strong influence of 2.5%. Factors affecting the most dominant inefficiency are transportation, consists of transporting the seedling production process supporting materials, removal from the nursery to adaptation field, and the distribution process. Inhibition of supply needs for seed production process caused by production area location that is far from supplier so impacting the delivery retard of goods especially for special case of unplanned needed materials. The second factor is motion, the excessive movement affects the endurance decreasing of seedlings after transferred, this is happen due to several things such as the occurrence of root shift, uprooted fibers that come out from polybag and the planting media pressure diminished. Furthermore, defect and inventory are the least influential factor. Parameters affecting performance and become the basis of system improvement is material preparation, which takes a long time because the materials must be ordered from Surabaya before entering the warehouse, whereas it is impossible to dumped the material a long time in the warehouse due to short shelf life and limited facilities of raw material inventory. Seeding production process, the waste is emerged due to defect in the process of planting explant, incubation, nursery, climatization, and distribution. This defect arises because in the plant process is moved first before processed, and the existence of facilities that need to be improved. The distribution process often leads to defects because the loading process is not done carefully and is implemented one by one, so it takes longer to process the loading, in addition the long shipping distance by ship outside region costumers requires an appropiate treatment for the plant can arrive at destination in good condition. The engineering undertaken to system improvement involves capacity increasement, retention of non-durable materials by adding refrigerators, providing independent media planting facilities, providing special trays for exploratory planting, for incubation and nursery processes, changing shifting cultivation media models, shelf use for crops grown into polybags, this facilitates the transfer process specifically for processes that does not need to remove planting media and the use of handlifts is to move plants in groups to reduce defects and accelerate the process of removal of plants

Prediksi Jumlah Kejadian Titik Api Melalui Pendekatan Deret Waktu Menggunakan Model Seasonal Arima

Kebakaran hutan merupakan permasalahan yang hampir setiap tahun terjadi di Indonesia terutama di pulau Sumatera dan Kalimantan. Umumnya kejadian kebakaran hutan di Indonesia terjadi pada lahan gambut, hal ini dikarenakan pada musim kemarau, lahan gambut akan menjadi sangat kering sampai kedalaman tertentu sehingga akan mudah terbakar. Upaya menanggulangi kebakaran hutan telah dilakukan melalui pemantauan titik api melalui satelit, hal ini telah dilakukan oleh NASA (National Aeronautics and Space Administration) dengan satelit Terra dan Aqua melalui instrument MODIS (Moderate Resolution Imaging Spectroradiometer). Data yang didapatkan dari satelit tersebut mulai dari tahun 2001 sampai dengan 2018 kemudian diproses menjadi jumlah kejadian titik api perbulan yang selanjutnya dianalisa dengan pendekatan deret waktu menggunakan model Seasonal ARIMA (Auto Regressive Integrated Moving Average). Hal ini dilakukan untuk mengetahui korelasi jumlah kejadian titik api yang terjadi dengan jumlah kejadian titik api pada waktu sebelumnya. Hasil pengujian menunjukkan bahwa model ARIMA (1,0,1)x(1,0,1,12) adalah model terbaik untuk melakukan prediksi jumlah titik api dengan nilai RMSE sebesar 5.85

Rekayasa ulang proses produksi bibit tanaman jati berkelanjutan pada pt harfam jaya makmur

Deforestation and degradation continue to occure. Forest management on a partnership basis with the community was also one of the methods of forest management to tackle deforestation. Forest and land rehabilitation is intended to restore, maintain and improve the functions of forests and land so that their carrying capacity, productivity and role in supporting life support systems are maintained. Forest rehabilitation activities that have been done including reforestation, maintenance, plant enrichment, and the application of vegetative and civil technical soil conservation techniques on critical and unproductive lands. Forest management on a partnership basis with the community were also one of the methods of forest management to tackle deforestation. PT. Harfam Jaya Makmur, as an agroforestry company were committed to supporting the provision of legal teak and supporting forest afforestation. Breeding efforts undertaken by PT. Harfam Jaya Makmur implemented by cooperating with BPPT as a partner to seek superior teak plant. Problems faced to create superior teak seedlings is the high cost of seed production, this causes PT. Harfam Jaya Makmur teak seed products has a higher price. The objectives of this research were 1) to know and to analyze the production process of teak seedlings, 2) to measure the performance of teak seed production process as parameter of re-engineering of sustainable teak forest business process, 3) to re-engineer the teak seed production process at PT. Harfam Jaya Makmur. The study was conducted on March 2015 - May 2017 in teak forests in Situbondo and Bondowoso regencies managed by PT Harfam Jaya Makmur. Business process revitalization will be done with value stream mapping approach. Value stream mapping analysis begins with creating value stream mapping current state, waste identification and measurement, waste analysis, and value stream mapping future state. Based on the results of Structural Equation Model (SEM) model analysis, there was known that all the main factors affecting the production process of teak seedlings at PT. Harfam Jaya Makmur is transportation, process, man, material and machine factors. The factor directly affecting each of main factors is the motion, while the indirectly affecting is based on motion, inventory, and defect factors. This condition shows that there are 3 factors becoming priorities in teak seed production system improvement at PT. Harfam Jaya Makmur with the priority ranks as follows: 1) transportation that directly and indirectly influence the occurrence of waste with a strong influence reaches 60.8%, 2) motion that directly or indirectly influence, strong influence 49.5% 3) defect that has an indirect effect on strong influence of 3.8%, 4) inventory that has an indirect effect on with strong influence of 2.5%. Factors affecting the most dominant inefficiency are transportation, consists of transporting the seedling production process supporting materials, removal from the nursery to adaptation field, and the distribution process. Inhibition of supply needs for seed production process caused by production area location that is far from supplier so impacting the delivery retard of goods especially for special case of unplanned needed materials. The second factor is motion, the excessive movement affects the endurance decreasing of seedlings after transferred, this is happen due to several things such as the occurrence of root shift, uprooted fibers that come out from polybag and the planting media pressure diminished. Furthermore, defect and inventory are the least influential factor. Parameters affecting performance and become the basis of system improvement is material preparation, which takes a long time because the materials must be ordered from Surabaya before entering the warehouse, whereas it is impossible to dumped the material a long time in the warehouse due to short shelf life and limited facilities of raw material inventory. Seeding production process, the waste is emerged due to defect in the process of planting explant, incubation, nursery, climatization, and distribution. This defect arises because in the plant process is moved first before processed, and the existence of facilities that need to be improved. The distribution process often leads to defects because the loading process is not done carefully and is implemented one by one, so it takes longer to process the loading, in addition the long shipping distance by ship outside region costumers requires an appropiate treatment for the plant can arrive at destination in good condition. The engineering undertaken to system improvement involves capacity increasement, retention of non-durable materials by adding refrigerators, providing independent media planting facilities, providing special trays for exploratory planting, for incubation and nursery processes, changing shifting cultivation media models, shelf use for crops grown into polybags, this facilitates the transfer process specifically for processes that does not need to remove planting media and the use of handlifts is to move plants in groups to reduce defects and accelerate the process of removal of plants

Hubungan Nilai Rasio Neutrofil-Limfosit Pra Pembedahan dengan Prognosis Kanker Ovarium Jenis Epitelial di RSUP Dr. Sardjito

LATAR BELAKANG: Kanker ovarium merupakan salah satu keganasan pada perempuan yang paling sering dan mematikan. Angka kejadian kanker ovarium di Indonesia mencapai 15 per 100.000 dan menempati urutan kelima penyebab kematian terbanyak akibat kanker pada wanita di Indonesia. Lebih dari 75% pasien kanker ovarium terdiagnosis pada stadium lanjut. Setelah menjalani tatalaksana primer, 50% pasien akan mengalami rekurensi dalam waktu 1 tahun, dan angka 5 years survival rate kurang dari 50%. Secara umum, prognosis kanker ovarium epitelial secara independen dipengaruhi oleh stadium, tipe dan derajat histologis, serta diameter residu maksimum setelah operasi sitoreduktif. Rasio neutrofil-limfosit (RNL), suatu prediktor status inflamasi, telah terbukti menjadi penanda prognostik yang efektif untuk sebagian keganasan, termasuk keganasan ovarium. Nilai RNL yang tinggi menggambarkan kecenderungan peningkatan inflamasi pro-tumor dan penurunan kapasitas imun anti-tumor.TUJUAN: Mengetahui hubungan antara Rasio Neutrofil-Limfosit (RNL) pra pembedahan primer dengan prognosis kanker ovarium epitelial pada pasien kanker ovarium di RSUP Dr. Sardjito, Yogyakarta.METODE: Penelitian ini merupakan penelitian uji prognosis dengan rancangan kohort retrospektif yang melibatkan 106 penderita kanker ovarium di RSUP Sardjito yang memenuhi kriteria inklusi. Sumber data berasal dari data sekunder yang diambil dari Instalasi Catatan Medik (ICM) dalam kurun waktu Januari 2016 sampai dengan Maret 2019.HASIL: Dari 106 subjek, didapatkan rerata usia pasien adalah 48.58 dengan 69.8% subjek merupakan multipara. Sebanyak 50.94% subyek didapatkan dalam stadium lanjut (III dan IV) dan 71.7% merupakan tumor high grade. Risiko relatif subyek dengan RNL ≥ 3,1 yang mengalami Progression Free Survival (PFS) 3.1 dan stadium lanjut berhubungan dengan PFS secara klinis maupun statistik. KESIMPULAN: RNL pra pembedahan > 3.1 berhubungan dengan kejadian PFS 3.1 dan stadium lanjut mengalami PFS < 12 bulan.KATA KUNCI: Kanker ovarium epitelial, Rasio Neutrofil-Limfosit, progression free survival

Pemanfaatan Wireless Sensor Network Berbasis Internet Of Things Untuk Monitoring Lahan Gambut Jarak Jauh

Lahan gambut di Indonesia tersebar di beberapa pulau, yaitu Kalimantan, Sumatera dan Papua. Kalimantan Selatan merupakan salah satu provinsi yang memiliki lahan sawah dan lahan gambut terbesar di Indonesia, yaitu sekitar 250.000 hektar yang tersebar di beberapa kabupaten. Ada banyak manfaat dari lahan gambut, dua manfaat utamanya adalah kemampuan menyimpan sejumlah besar karbon dan kemampuan untuk menyimpan air hingga 13 kali beratnya. Sayangnya, lahan gambut setiap tahunnya mengalami penurunan, baik dari segi ukuran maupun kualitasnya. Upaya pemulihan telah dilakukan oleh pemerintah dan juga pengamat lingkungan baik Nasional maupun Internasional. Meski begitu, kondisi lahan gambut masih belum bagus. Banyak kendala yang dihadapi seperti luas lahan dan sulitnya lokasi menyebabkan biaya yang dibutuhkan untuk melakukan pengawasan dan pemeliharaan lahan gambut cukup tinggi. Untuk mengembalikan ratusan ribu lahan gambut dibutuhkan triliunan rupiah. Salah satu pendekatan yang dapat dilakukan untuk melestarikan lahan gambut adalah dengan pemantauan lahan gambut secara langsung dan teratur. Khususnya pada musim kemarau, lokasi lahan gambut awal dengan potensi kebakaran bisa dideteksi. Penelitian ini mengusulkan penggunaan Wireless Sensor Network (WSN) berbasis Internet of Things (IoT) untuk pemantauan lahan gambut terpencil. Dalam perkembangannya, diharapkan penelitian ini dapat menghasilkan prototipe peralatan pemantauan nirkabel untuk pemantauan lahan basah terutama lahan gambut

RANCANG BANGUN SISTEM INFORMASI PENJUALAN MEUBEL (STUDI KASUS: CV. FAJAR INDAH AMUNTAI)

One of the media information that is widely used by some companies today is desktop-based information systems where an application is expected to help facilitate in resolving a problem. Furniture Fajar Indah Amuntai in managing goods data, pricing and reporting the results of the transaction is still using paper media or notebook in storing such data, however, when there are changes in prices of goods then the data is written back in a new book, so the time and cost of wasted writing and buying new books. To identify the needs of the system in this study using data flow trending analysis. From the information obtained by the analysis conducted inputs, outputs and system processes that are expected, which is a facility operator to manipulate data, manipulate data items, records every sales transaction, it can display and print the report. With the analysis results can be obtained interface design is more user friendly and easy to use. &nbsp

Sistem Peringatan Dini Keterlambatan Masa Studi Mahasiswa Menggunakan Metode Support Vector Machine

Students graduating late from college are a common problem in universities. The study of students at universities is generally designed to be completed in 3.5 to 4 years. If a student has not graduated past that time, he is considered late in completing his education. Lambung Mangkurat University, as the oldest university in Kalimantan, also experienced these problems. Therefore, an early warning system was build to predict students' possibility of being late in completing their studies. This study uses a sample of students from the Faculty of Engineering, the University of Lambung Mangkurat, to predict students who will be late graduating from Lambung Mangkurat University since semester 5. This system was to develop using a model built using the Support Vector Machine (SVM) method. Model training conducted using 755 data from Lambung Mangkurat University Faculty of Engineering students from 2010 to 2014. Then, the performance of the model tested using 234 student data from 2015 and 2016. The parameters used were the number of credits, gender, GPA on semester 1 to 4, and study programs. The test results show that the model has good performance to predict students who will be late in completing their studies with 88.2% accuracy

Modelling and predicting wetland rice production using support vector regression

Food security is still one of the main issues faced by Indonesia due to its large population. Rice as a staple food in Indonesia has experienced a decline in production caused by unpredictable climate change. In dealing with climate change, adaptation to fluctuating rice productivity must be made. This study aims to build a prediction model of wetland rice production on climate change in South Kalimantan Province which is one of the national rice granary province and the number one rice producer in Kalimantan Island. This study uses monthly climatic data from Syamsudin Noor Meteorological Station and quarterly wetland rice production data from Central Bureau of Statistics of South Kalimantan. In this research, Support Vector Regression (SVR) method is used to model the effect of climate change on wetland rice production in South Kalimantan. The model is then used to predict the amount of wetland rice production in South Kalimantan. The results showed that the prediction model with the RBF kernel with the parameter of C=1.0, epsilon=0.002 and gamma=0.2 produces good results with the RMSE value of 0.1392

Hate Speech Detection for Banjarese Languages on Instagram Using Machine Learning Methods

Hate speech refers to verbal expression or communication that aims to provoke or discriminate against individuals. The Ministry of Communication and Information of Indonesia has encountered and dealt with 3,640 cases of hate speech transmitted through digital channels between 2018 and 2021. Particularly in South Kalimantan, hate speech in the local language, Banjarese has become increasingly prevalent in recent years. Surprisingly, there is a lack of research on using machine learning to detect hate speech in the Banjarese language, specifically on Instagram. Therefore, this study aimed to address this gap by constructing a dataset of Banjarese language hate speech and comparing various feature extraction and machine learning models to detect Banjarese language hate speech effectively. Thisresearch used several feature extraction techniques and machine learning methods to detect Banjareselanguage hate speech. The feature extraction methods used were Word N-Gram, Term Frequency- Inverse Document Frequency (TF-IDF), a combination of Word N-Gram and TF-IDF, Word2Vec, and Glove, while the machine learning methods used were Support Vector Machine (SVM), Na¨ıve Bayes, and Decision Tree. The results of this study revealed that the combination of TF-IDF for feature extraction and SVM as the model achieves exceptional performance. The average Recall, Precision, Accuracy, and F1-Score score exceeded 90%, demonstrating the model’s ability to identify Banjarese hate speech accurately

Penerapan Generalized Regression Neural Networks untuk Memprediksi Produksi Padi Terhadap Perubahan Iklim

Padi sebagai bahan makanan pokok utama bagi masyarakat Indonesia merupakan tanaman pangan yang rentan terhadap perubahan iklim. Pendataan dan perhitungan ramalan hasil produksi padi sangat diperlukan untuk mendukung kebijakan yang berkaitan dengan ketahanan pangan. Penelitian ini bertujuan untuk melakukan peramalan terhadap produksi padi di Kabupaten Barito Kuala sebagai kabupaten penghasil padi terbesar di Kalimantan Selatan dengan menggunakan data iklim sebagai input. Data iklim yang digunakan berasal dari Stasiun Meteorologi Syamsudin Noor, sedangkan sebagai data output adalah data produksi padi dari Badan Pusat Statistika (BPS) Provinsi Kalimantan Selatan. Metode yang digunakan untuk melakukan peramalan produksi padi adalah Generalized Regression Neural Networks (GRNN). Dari hasil pengujian didapatkan nilai Root Mean Square Error (RMSE) sebesar 0,296 dengan menggunakan parameter smoothness bernilai 1.