Hasil Pencarian  ::  Simpan CSV :: Kembali

"Pada tahun 2017, Bursa Efek Indonesia memiliki initial return positif IPO yang luar biasa. Indeks komposit juga mencapai titik tertinggi sepanjang masa. Fenomena ini menarik untuk diteliti lebih lanjut. Hubungan antara pasar bull dan bear dan initial return IPO dianalis dalam penelitian ini untuk memberikan gambaran apakah kondisi pasar tahun bullish dan bearish mempengaruhi initial return dari IPO. Kinerja jangka panjang IPO dihitung menggunakan event study dari tahun yang berbeda untuk memberikan gambaran kepada investor tentang kinerja jangka panjang IPO dan apakah perusahaan dan underwriter efektif dalam memilih waktu untuk IPO. Penelitian ini akan menganalisis dan menggunakan data dari IPO dari bulan Januari tahun 2010 hingga Desember 2017. Benchmark yang digunakan adalah indeks pasar dan perusahaan yang memiliki sektor yang sama serta indeks sektoral. Kondisi penting dalam penelitian ini adalah initial return dan tiga tahun pasca IPO yang digunakan dalam penelitian sebagai periode jangka pendek dan jangka panjang. Sebagai ukuran kinerja, wealth relatives/adjustment dapat menyimpulkan dan menjadi indikasi performa IPO dalam jangka panjang. Hasil penelitian menunjukkan ada hubungan pasar saham bearish/bullish terhadap initial return. Tidak ada pengaruh tingginya initial return terhadap kinerja jangka panjang, namun kondisi pasar saat IPO ada indikasi mempengaruhi kinerja jangka panjang.

---

In 2017, Indonesia Stock Exchange had the exceptional initial return of IPOs. The composite index also reached the all-time high. This phenomenon is interesting to study for further details. The relationship between the bull and bear market and the initial return of IPOs is being studied to give insight whether specific market and year condition influence the initial return of IPOs. The long-term performance of IPOs is calculated according to year of IPO and after three years to give the long-term perspective for investors and whether the underwriters and public companies are effective on choosing the best time to IPO. This paper will analyze using datas of IPOs from January 2010 until December 2017. The benchmarks are the market index and the matching firm with the same size and same industry with the use of event series and also sectoral index. Two necessary events are the initial return and the three-year anniversary of IPOs which the event this paper used as a short term and long-term perspective. As a performance measure, the wealth relatives/adjustment can conclude and indicate the underperformed IPOs. Initial returns are higher when the bull market is present. The bull market will produce the highest initial return of IPOs. There is indication that the market trend condition in each year affect the long term performance."

"Saham merupakan salah satu surat berharga yang diterbitkan dan dijual oleh perusahaan,yang telah memenuhi syarat, di Bursa Efek Indonesia. Prinsip dasar yang dimiliki olehsaham adalah High Risk High Reward, yang menggambarkan bahwa saham memangdapat memiliki hasil yang besar, namun memiliki risiko yang tinggi pula. Denganprinsip High Risk High Reward, tentunya para investor harus lebih hati-hati dalammenentukan langkah yang akan mereka lakukan. Salah satu cara yang dapat digunakanuntuk mengurangi risiko, yaitu melakukan prediksi tren harga saham menggunakanMachine Learning. Menggunakan data historis saham pada Bursa Efek Indonesia,yaitu open, high, low, dan close price, algoritma Machine Learning dapat melakukanprediksi tren harga saham yang selanjutnya akan digunakan sebagai strategi investasipara investor. Terdapat banyak metode Machine Learning yang dapat digunakan untukmelakukan prediksi, salah satu metode yang dapat digunakan adalah Recurrent NeuralNetwork yaitu Long Short Term Memory (LSTM). Pada metode LSTM, data historisharga saham akan dibawa ke depan melalui seluruh gerbang LSTM yaitu: ForgetGate, Input Gate, dan Output Gate. Selanjutnya akan dicari nilai loss dari model,setelah didapat nilai loss, model akan ditinjau kembali setiap tahapannya, dimulai daribelakang. Langkah pengulangan tesebut dilakukan agar mendapat variabel Weight danBias yang optimal. Kemudian, tingkat akurasi dari metode tersebut akan ditentukanmenggunakan: Root Mean Square Error (RMSE) dan Mean Absolute Error (MAE).Penelitian ini menggunakan data historis perusahaan yang termasuk pada Indeks LQ45dan dapat diambil melalui website, finance.yahoo.com. Dari penelitian ini, diketahuibahwa, masing-masing masalah memiliki model terbaiknya, untuk penyelesaian masalahtersebut.

---

Stock is a part of ownership of a company, that have fulfill the requirement to be sold at

Bursa Efek Indonesia. The basic principal of stock market is High Risk High Reward,

which describe that stock market indeed have a chance to get a great profit, but it also

come with a high risk. This principal is the reason that all investor must be cautious in

deciding their move. There’s many method to do this, with one of the being, forecasting

the stock market trend with machine learning. With the historical data, that include

open, high, low, dan close price, the machine learning algorithm, could forecast the stock

market direction for the next days, which will be one of the deciding factor for investor to

choose their move. Nowadays, there’s many machine learning method that can be used to

forecast, one of them is the branch method of Recurrent Neural Network, which is, Long

Short Term Memory (LSTM). LSTM use the historical data, and bring them forward to,

Forget Gate, Input Gate, Memory State, Output Gate. Then the loss value of the model

will be calculated. After all the process the model will be re-evaluated. The re-evaluation

step is to update all the weights and biases in the model. Then the accuracy of the model

will be evaluated with Root Mean Squared Error (RMSE) and Mean Absolute Error

(MAE). This study uses the historical data of the companys that’s included in the index

LQ45, and the data is taken from the website, finance.yahoo.com. From this research, it

is known that every problem has their own preference model to solve."

"The columns of a building must be stronger than the beams. The aim of this study is to obtain the cause of the long-term deformation difference by shrinkage between the beams and columns of high performance concrete with compressive strength of 60 MPa. This research was done experimentally in Indonesia during 410 days. Specimens measuring 150 mm × 150 mm × 600 mm were used, 3 pieces for the beams and 2 pieces for the columns. Deformation was obtained by using an embedded vibrating wire strain gauge for each specimen. The difference of long-term deformation in columns and beams is in their autogenous deformation behavior. This is because during the autogenous phase, swelling abnormally occurs in the column before shrinkage occurs. The abnormal swelling is caused by the press of its own weight. This phenomenon does not occur in beams. In the age range of 1 to 200 days, the behavior of the beam deformation has a similar pattern to the deformation behavior of the column with a high deformation rate. After that, at 200–410 days, column deformation changes to a very slow deformation rate. Long-term deformation in columns is lower (64%) than in the beams at 410 days age."

"Tujuan penelitian ini adalah membahas dampak perbedaan motif Merger dan Akuisisi (M&A) terhadap kinerja jangka panjang dan kualitas laba perusahaan pasca M&A serta peran moderasi Corporate Governance, baik pada tingkat perusahaan maupun tingkat negara terhadap hubungan antara motif M&A dan kinerja jangka panjang. Selain itu penelitian ini juga menganalisis pengaruh motif M&A terhadap tingkat pengungkapan transaksi M&A serta dampak dari tingkat pengungkapan tersebut bagi kinerja jangka panjang serta kualitas laba perusahaan pasca M&A. Penelitian ini berfokus pada pemisahan persepsi motif M&A dari investor menjadi motif sinergi dan agensi berdasarkan reaksi investor saat pengumuman M&A dilakukan serta menggunakan variabel akuntansi. Penelitian ini dilakukan secara lintas negara dengan menggunakan sampel kasus M&A yang terjadi di 11 negara Asia selama periode 2002-2012. Dengan menggunakan metode cross-sectional ordinary least square, hasil analisis menunjukkan bahwa M&A bermotif sinergi menghasilkan kinerja yang lebih baik dibandingkan M&A motif agensi, dan mekanisme Corporate Governance yang diterapkan perusahaan terbukti dapat lebih memaksimumkan dampak positif tersebut. Temuan lain dari penelitian ini menunjukkan bahwa motif M&A juga menjadi faktor penting yang menjelaskan tingkat pengungkapan informasi M&A yang kemudian terbukti secara signifikan menentukan kualitas laba perusahaan pasca M&A. Penelitian ini tidak dapat membuktikan pengaruh motif M&A terhadap kualitas laba, pengaruh tingkat pengungkapan M&A terhadap kinerja jangka panjang serta peran moderasi Corporate Governance tingkat negara pada hubungan antara motif M&A dan kinerja jangka panjang.

---

The purpose of this study is to analyze the effect of Merger and Acquisition (M&A) motives to the long-term performance and earnings quality of companies post M&A, and the moderating effect of Corporate Governance, both in firm-level and country-level, to the relationship between M&A motives to the long-term performance. In addition, this study also analyses the influence of M&A motive to the M&A transaction disclosure level and then analyses how the M&A disclosure level can determine the long-term performance and the earnings quality post M&A. This study uses M&A transactions in 11 Asian countries during 2002 until 2012 as research sample. Using cross-sectional ordinary least square method, this study proves that the M&A motives have significant positive influence to the long-term performance post M&A and the significant moderating effect of Corporate Governance at firm-level in maximizing the influence between it. Other findings in this study show that the M&A motives have a significant positive influence on the level of M&A disclosure which is then proven to be one of the significant factors that determining the quality of earnings post M&A. In the other side, this study fails to prove the significant impact of the M&A motive to the earnings quality post M&A, the influence of the disclosure level to the long-term performance and the moderating effect of the Corporate Governance at country-level to the relationship between the M&A motives and the long-term performance post M&A."

"Summary: Overview: Now in its 6th Edition, ASSISTING IN LONG-TERM CARE is the complete learning solution for Certified Nursing Assistants! The user-friendly book delivers all required content to prepare you for the certification exam while developing career skills for long-term care and sub-acute hospital settings. Topics include professional communication, daily CNA responsibilities, residents' rights, nutrition and hydration, restorative care, resident mobility, and maintaining a safe environment - all according to federal OBRA standards for nursing home care. ASSISTING IN LONG-TERM CARE, 6th Edition also walks you through more than one hundred clinical procedures, detailing your role as a CNA in each. Available in hard copy and e-book formats, ASSISTING IN LONG-TERM CARE, 6th Edition's helpful study features include review questions and self-tests, icons that point out key material, and a robust package of interactive, supplemental learning tools."

"ABSTRAKPendahuluan: Kusta merupakan penyakit menular yang belum sepenuhnya dapatdikendalikan, dan menjadi masalah kesehatan masyarakat karena cacat yang ditimbulkan,salah satunya akibat reaksi kusta. Terapi utama untuk reaksi kusta adalah kortikosteroid,dalam dosis standar 12 minggu sesuai rekomendasi WHO dan Kemenkes RI. Denganterapi standar ini, kesembuhan dapat tidak tercapai dan sering terjadi rekurensi, sementaradurasi pemberian yang lama diduga dapat memberikan perbaikan klinis lebih baik sertabertahan lebih lama. Bukti efikasi kortikosteroid pada reaksi kusta masih kurang, dandosis optimal serta lama terapi yang dibutuhkan sangat bervariasi. Di sisi lain, kebutuhanakan kortikosteroid dosis tinggi jangka panjang menimbulkan kesulitan menghindari efeksamping, mencakup hampir semua sistem organ. Dengan adanya perbedaan penetapandurasi pemberian kortikosteroid pada reaksi kusta, sementara penggunaan jangka panjangcenderung meningkatkan efek samping, maka diperlukan analisis perbedaan efektivitasterapi dan efek samping antara kortikosteroid 12 minggu dengan >12 minggu.Metode: Penelitian ini merupakan studi analitik observasional dengan desain kohortretrospektif yang membandingkan efektivitas terapi dan kejadian efek samping antarapenggunaan kortikosteroid 12 minggu dengan >12 minggu pada pasien kusta denganreaksi, melibatkan seluruh pasien baru kusta dengan reaksi tanpa batasan usia, yangberobat ke RSCM dan Puskesmas Cakung selama periode 1 Januari 2015 sampai 31Desember 2017. Data sekunder dikumpulkan dari rekam medik, dan pengamatandilakukan sampai Desember 2018. Efektivitas terapi dinilai dari perbaikan klinis hinggakortikosteroid dapat diturunkan bertahap dan dihentikan, tanpa ada rekurensi dalam 3bulan setelah siklus pertama selesai. Efek samping dinilai dari seluruh efek sampingterkait kortikosteroid yang tercatat pada rekam medik.Hasil: Dari 195 subjek, 57 (29.2%) menggunakan kortikosteroid selama 12 minggu, dan138 (70.8%) menggunakannya selama >12 minggu. Efektivitas terapi berupa perbaikanklinis tanpa rekurensi selama 3 bulan terjadi pada 38 (66.7%) pasien kelompok 12 minggudan 106 (76.8%) pasien kelompok >12 minggu (RR 0.604 dengan IK 95% 0.307 1.189,p 0.143). Dari 145 subjek, efek samping kortikosteroid terjadi pada 12 (31.6%) pasienkelompok 12 minggu dan 70 (65.4%) pasien kelompok >12 minggu (RR 0.244 denganIK 95% 0.111 0.538, p<0.001). Dari total 171 kejadian efek samping yang timbul,37.4% adalah efek samping ringan berupa dispepsia, kelainan kulit dan lipodistrofi,sementara 62.6% adalah efek samping berat berupa gangguan neuropsikiatrik, kelainanmata, penyakit kardiovaskular, perdarahan saluran cerna, kelainan metabolik-hormonal,serta reaktivasi infeksi.Kesimpulan: Tidak ada perbedaan efektivitas berupa perbaikan klinis tanpa rekurensiselama 3 bulan, antara penggunaan kortikosteroid 12 minggu dengan >12 minggu,sementara efek samping yang timbul berbeda signifikan, yakni durasi pemberian yanglebih panjang menimbulkan kejadian efek samping 4 kali lebih banyak.

---

ABSTRACTIntroduction: Leprosy is an infectious disease that has not been fully controlled, and hasbecome a public health problem because of the defects caused, one of which is a leprosyreactions. The main therapy for leprosy reactions is corticosteroids, in a standard 12weeks dose according to WHO recommendations and the Indonesian Ministry of Health.Through this standard, therapy healing can not be achieved and recurrence often occurs,while long duration of administration thought to provide better clinical improvement andlast longer. Evidence related to the efficacy of corticosteroids in the leprosy reactions isstill lacking, and the optimal dose and duration of therapy needed varies greatly. On theother hand, the need for long-term high-dose corticosteroids makes it difficult to avoidadverse effects, covering almost all organ systems. With the differences in the durationof corticosteroid administration in leprosy reactions, while long-term use tends to increaseadverse effects, an analysis of the differences in therapeutic effectiveness and adverseeffects between corticosteroid use for 12 weeks and >12 weeks is needed.Method: This study is an observational analytic study with a retrospective cohort designthat compares the effectiveness of therapy and the incidence of adverse effects betweencorticosteroid use for 12 weeks and >12 weeks in leprosy patients with reactions,involving all new leprosy patients without age restriction, who seek treatment at RSCMand Puskesmas Cakung during the period of January 1, 2015 to December 31, 2017.Secondary data was collected from medical records, and observations were carried outuntil December 2018. Effectiveness of therapy was assessed from clinical improvementto corticosteroids can be gradually reduced and stopped, without recurrence within 3months after the first cycle was completed. Adverse effects were assessed from allcorticosteroid-related side effects recorded in the medical record.Result: Of 195 subjects, 57 (29.2%) used corticosteroids for 12 weeks, and 138 (70.8%)used it for >12 weeks. The effectiveness of therapy in the form of clinical improvementwithout recurrence for 3 months occurred in 38 (66.7%) patients in the 12 weeks groupand 106 (76.8%) patients in the >12 weeks group (RR 0.604 with 95% CI 0.307 - 1.189,p 0.143). Of 145 subjects, corticosteroids adverse effects occurred in 12 (31.6%) patientsin the 12 weeks group and 70 (65.4%) patients in the >12 weeks group (RR 0.244 with95% CI 0.111-0.538, p <0.001). Of the total 171 occurrences of adverse effects, 37.4%were mild such as dyspepsia, skin disorders and lipodystrophy, while 62.6% were severein the form of neuropsychiatric disorders, eye disorders, cardiovascular disease,gastrointestinal bleeding, metabolic-hormonal disorders, and reactivation of infection.Conclusion: There is no difference in effectiveness in the form of clinical improvementwithout recurrence for 3 months, between corticosteroid use for 12 weeks compared with>12 weeks, while the adverse effects that arise differ significantly, namely the longerduration of administration causes 4 times more events."

"Twitter adalah platform media sosial microblogging yang memungkinkan komunikasi dua arah untuk mengutarakan opini dan komentar. Komentar-komentar yang beragam ini dapat memperlihatkan sentimen-sentimen masyarakat apabila dilakukan analisis sentimen. Analisis sentimen adalah studi yang menganalisis opini orang terhadap suatu produk, organisasi, individu, atau jasa tertentu. Machine learning merupakan metode yang dapat mempermudah proses klasifikasi sentimen. Penelitian ini dilakukan pada cuitan berbahasa Indonesia terkait Kampus Merdeka yang diambil dari Twitter menggunakan package tweepy sebanyak 1.651 cuitan terhitung dari tanggal 5 Maret 2022 hingga 13 Maret 2022. Model machine learning yang digunakan pada penelitian ini adalah Bidirectional Long Short-Term Memory (BiLSTM), dengan dua model hybrid LSTM-based, yaitu CNN-LSTM dan LSTM-CNN sebagai pembanding. Kinerja model diukur dengan metrik kinerja accuracy, precision, recall, dan F1-score. Implementasi dilakukan pada data yang telah dilakukan oversampling untuk mendapatkan hasil yang optimal. Penelitian menunjukkan bahwa model BiLSTM memiliki kinerja yang lebih unggul dibandingkan dengan dua model pembanding lainnya pada seluruh metrik dengan besar metrik, yaitu: accuracy dan recall sebesar 79,577%; precision sebesar 73,097%; dan F1-score sebesar 75,634%.

---

Twitter is a microblogging social media platform that allows two-way communication to express opinion and comments. These various comments can show us sentiment of the public when we perform a sentiment analysis. Sentiment analysis is a study that analyze the opinion of people towards a specific product, organization, individual, or service. Machine learning is a method that will help perform sentiment classification easier. This study performs analysis on 1.651 data tweets about Kampus Merdeka taken from Twitter using a package called tweepy since March 5th 2022 until March 13th 2022. The machine learning model used in this study is Bidirectional Long Short-Term Memory (BiLSTM), with two LSTM-based hybrid model, CNN-LSTM and LSTM-CNN as comparison models. Model performance is measured by performance metrics accuracy, precision, recall, and F1-score. Implementation was done on data that has been going through oversampling to achieve the best result. The study shows that BiLSTM performs better than the other two comparison models for all the metrics with the percentage of the each metric being: 79.577% for accuracy and recall; 73,097% for precision; and 75,634% for F1-score."

"The dynamic nature of meteorological data and the commercial availability of diverse photovoltaic systems, ranging from single-junction silicon-based PV panels to concentrated photovoltaic (CPV) systems utilizing multi-junction solar cells and a two-axis solar tracker, demand a simple but accurate methodology for energy planners and PV system designers to understand the economic feasibility of photovoltaic or renewable energy systems. In this paper, an electrical rating methodology is proposed that provides a common playing field for planners, consumers and PV manufacturers to evaluate the long-term performance of photovoltaic systems, as long-term electricity rating is deemed to be a quick and accurate method to evaluate economic viability and determine plant sizes and photovoltaic system power production. A long-term performance analysis based on monthly and electrical ratings (in kWh/m2/year) of two developed CPV prototypes, the Cassegrain mini dish and Fresnel lens CPVs with triple-junction solar cells operating under the meteorological conditions of Singapore, is presented in this paper. Performances are compared to other conventional photovoltaic systems."