The Completeness and Accuracy of Hepatoma Coding for Medical Procedure Based on ICD-9 CM at Public Hospital in Padang

Background: Hepatoma or hepatocellular carcinoma (KHS) is a primary malignant tumor of the liver originating from hepatocytes and the 3rd cause of death from cancer in the world. The history of a hepatoma patient can be seen based on the patient's medical record. The filling of medical record is done by doctors, nurses and medical record personel. However, in medical record filling, incompleteness is often found and cause inaccurate information. Accuracy coding important for financial of hospital.Methods: Type of research is quantitative descriptive, which is to determine the completeness and accuracy of the medical records for hepatoma cases and procedure code using criteria for document quantitative analysis in a public hospital, Padang. The study design used a retrospective analytical approach. The variables in the study were completeness of discharge summary and accuracy of hepatoma procedure based on ICD-9 CM. The population in this study were inpatient medical record documents for Hepatoma cases at a public hospital, Padang from June to August 2019, which were 45 medical record documents (discharge summary form) of hepatoma inpatients.Results: From 45 hepatoma patient medical record documents, filling of item name, medical record number, date of admission, indication of the patient being treated, history, physical examination, diagnostic examination, procedures, medications given, medicines used at home, PPBS doctor's signature, DPJP doctor's hand is complete 100% . Highest incompleteness of filling was found at code ICD (47%) and address item (43%). From 45 discharge summary , accuracy procedure code at hepatome case shows 100 % accurate in ultrasonoggrafi abdomen and ultrasonografi thorax. While that EKG 98% accurate and 95 % rontgen thorax.Conclusions: In general, item data of discahrege summary for hepatoma medical record are completenes; highest incompleteness of filling was found at code ICD (47%) and address item (43%); Accuracy of code procedure more than 90% in each code procedure.

EFEKTIVITAS KONSELING BEHAVIORAL TEKNIK ASERTIF DALAM MEMINIMALISIR PERILAKU AGRESIF

Penelitian ini bertujuan untuk mengetahui efektivitas konseling behavioral teknik asertif terhadap perilaku agresif siswa. Penelitian ini merupakan jenis penelitian Quasi Eksperimen dengan rancangan penelitian one group pretest-posttest design. Penelitian ini dilaksanakan di SMP Lab Undiksha Tahun Pelajaran 2016/2017. Sampel dari penelitian ini adalah 20 orang siswa kelas VIII 1 dan VIII 2 SMP Lab Undiksha. Teknik pengambilan sampel yaitu purpossive sampling dan metode pengumpulan data dengan kuisioner perilaku agresif yang berjumlah 34 item. Data penelitian dianalisis menggunakan analisis statistik t-Test berpasangan. Hasil penelitian menunjukkan bahwa terdapat penurunan perilaku agresif terhadap siswa yang diberikan konseling behavioral teknik asertif. Hal ini dapat dilihat dari perbedaan Mean Rank pada pretest sebesar 156,6 dan posttest sebesar 96,8. Kemudian berdasarkan nilai probabilitas didapatkan thitung ? ttabel dengan taraf signifikansi 0,025 maka 62,94 ? 2,093 sehingga dapat disimpulkan H0 ditolak.

Calibration of the science process skills among Malaysian elementary students: A Rasch model analysis

<p><span>This study aimed to calibrate the test items of science process skills used as a test at primary school students to provide information on the difficulty of each item. Data were collected from 128 standard five students in a primary school in Penang. The test was given in multiple-choice as many as 40 items consisting of 33 items partial credit test was developed to gather information from the students. The analysis included an assessment of the model’s assumptions and calibrations according to the individual items. Information on the Rasch calibration according to the topic were provided. Results revealed that the measurement made fulfilled both model-data fit and unidimensionality assumptions. Further analysis showed that observing and communicating were endorsed as the easiest to master while inferring and classifying were the most challenging. The study discussed the implication, particularly towards the teaching and learning of science process skills in the classroom. Teachers should seriously consider the science process skills when designing their teaching and learning strategies in the classroom.</span></p>

KELENGKAPAN REKAM MEDIS DI RUMAH SAKIT: LITERATURE REVIEW

Rekam medis yang dikatakan lengkap adalah rekam medis yang telah diisi lengkap oleh dokter dalam waktu < 24 jam setelah selesai pelayanan baik rawat inap maupun rawat jalan. Rekam medis dikatakana lengkap jika didalam nya minimal memuat tentang data biografi dan biografis. Rekam medis elektronik harus dibuat dengan seragam agar informasi yang diperoleh dari rekam medis elektronik menjadi lebih lengkap dan seragam. Dikarenakan rekam medis elektronik juga harus mencakup mengenai data personal, demografis, sosial, klinis dan berbagai eventklinis selama proses pelayanan dari berbagai sumber data (multimedia) dan memiliki fungsi secara aktif memberikan dukungan bagi pengambilan keputusan medis. Penelitian ini bertujuan untuk melakukan literature review guna mengetahui kelengkapan data rekam medis Hasil penelitian ini menunjukkan bahwa Kelengkapan data administratif rekam medis belum sepenuhnya lengkap 100% lengkap bahkan beberapa penelitian hanya sampai 90%. Kelengkapan data administratif dominan terdapat pada data identitas pasien tetapi di dalam identitas pasien tidak di jabarkan kelengkapan data yang di masuk meliputi item data apa saja Kelengkapan data klinis rekam medis juga belum sepenuhnya 100% lengkap bahkan beberapa penelitian hanya mencapai 90%. Kelengkapan data klinis dominan terdapat pada data anamneses, catatan keperawatan, dan catatan observasi..

Application Of Fuzzy C-Means Clustering for Mapping Agent

Strict business competition in the field of mountain equipment providers and selling the same product makes the mapping of onsight agents needed to determine the priority of agents prioritized. Fuzzy C-means is one of the data grouping techniques in which the existence of each data point in a cluster is determined by the level of membership. The purpose of this study is to design and make applications for grouping agents. The research method used is direct interview to obtain information in the form of ordered item data. The design model uses the System Development Life Cycle (SDLC). The system design method used is the Unified Modeling Language (UML). Agent mapping system with web-based fuzzy c-means clustering uses the PHP and MySQL programming languages as the database. The results of this study are in the form of three data clusters that can be used to support decisions for priority and from 30 data agents, the first cluster consists of 15 agents, the second cluster consists of 1 agent, and the third cluster consists of 14 agents

Matrix factorization completed multicontext data for tensor-enhanced recommendation

Tensors have been explored to share latent user-item relations and have been shown to be effective for recommendation. Tensors suffer from sparsity and cold start problems in real recommendation scenarios; therefore, researchers and engineers usually use matrix factorization to address these issues and improve the performance of recommender systems. In this paper, we propose matrix factorization completed multicontext data for tensor-enhanced algorithm a using matrix factorization combined with a multicontext data method for tensor-enhanced recommendation. To take advantage of existing user-item data, we add the context time and trust to enrich the interactive data via matrix factorization. In addition, Our approach is a high-dimensional tensor framework that further mines the latent relations from the user-item-trust-time tensor to improve recommendation performance. Through extensive experiments on real-world datasets, we demonstrated the superiority of our approach in predicting user preferences. This method is also shown to be able to maintain satisfactory performance even if user-item interactions are sparse.

Nomophobia Mahasiswa: Analisis Desktiptif dengan JASP

Tujuan penelitian ini adalah untuk melihat kondisi nomophobia mahasiswa ditinjau dari gender, tahun masuk universitas, akses internet perhari dan jumlah sosmed. Penelitian ini menggunakan pendekatan kuantitatif dengan metode deskriptif. Sampel penelitian ini adalah mahasiswa tahun masuk 2015 (0,29%) 2016 (0,34%), 2017 (0,37%), dengan usia 19-23 tahun dengan jumlah 205 mahasiswa (laki-laki = 17,6%; perempuan = 82,4%). Pengambilan sampel menggunakan teknik sampling insidental (non probability sampling). Instrumen yang digunakan adalah instrumen nomophobia yang berjumlah 33 item. Data dianalisis menggunakan analisis perangkat lunak JASP dengan teknik deskriptif. Temuan pada penelitian ini adalah adanya perbedaan nomophobia di kalangan mahasiswa, rata-rata laki-laki (M = 99.7) lebih tinggi daripada perempuan (M = 93.82). Selain itu, temuan lain pada penelitian ini adalah adanya peningkatan nomophobia mahasiswa setiap tahun masuk terlihat dari nilai rata-rata sebesar 91.98 untuk tahun masuk 2015, 93.69 untuk tahun masuk 2016, dan 98.21 untuk tahun masuk 2017. Dan ada kesamaan antara durasi internet per hari dengan jumlah akun sosmed dalam mempengaruhi peningkatan nomophobia mahasiswa.

Challenges and Opportunities for Telecommuting in the School System: Building a Sustainable Online Education in the Context of the SARS-Cov-2 Pandemic

The main idea of this investigation is to identify a series of challenges and opportunities presented by telecommuting within the school system as a result of the SARS-Cov-2 pandemic. The objective of the paper is to identify key elements which are able to provide concrete assistance in building a sustainable online education system, with particular reference to Romania, as a system that can be used beyond the timeframe of the current pandemic. The methodology used for our scientific investigation is quantitative, based on an eight-item data collection instrument/questionnaire with 459 respondents (bachelor, masters, doctoral, and postdoctoral students—which makes this research a study from the perspective of the students’ perceptions) with ages ranging from 18 to 53. In terms of results, the eight items were evaluated on a Likert Scale from 1 to 5, leading to the formulation of seven hypotheses (H1 to H6), of which six were accepted and one was rejected (H7) (the questionnaire has a margin error/confidence interval of ±4.5% and a confidence level of P = 95%). We concluded from the six validated hypotheses, coupled with the one which was invalidated, that telecommuting to online education was not only successful but also garnered a system characterized by sustainability. Despite the swiftness of telecommuting to online education and the perceptions of the student population, online learning can be efficient and sustainable, in which case further government policies can only improve a system that has already been proven to work.

Content validation of the Well-being of Older People measure (WOOP)

Background Valid measures of the well-being of older people are important for the evaluation of health and social care services. The nine-item Well-being of Older People measure (WOOP) was based on a novel framework derived from a recent Q-methodology study, and was developed to capture a comprehensive set of well-being domains relevant to older people, as identified by themselves. This study introduces the WOOP and describes the qualitative assessment of its feasibility and content validity. Methods Between December 2017 and January 2018, a sampling agency retrieved data from 269 adults aged 65 years and older in the Netherlands. Using an online survey, participants were asked to complete the WOOP and to indicate the importance of each item to their well-being. Open-ended questions were used to collect information about participants’ own definition of well-being, their interpretation of the items of the WOOP, and their assessment of the descriptions and response options provided with each item. Data were analysed using inductive content analysis with the software package ATLAS.ti. Results The WOOP closely resembled respondents’ own description of what well-being means to them. The majority of the respondents reported no important well-being aspects to be missing from the WOOP, and indicated all WOOP items to be at least ‘reasonably important’ to their well-being. Many linked the WOOP items to well-being aspects as intended, and only a few had suggestions for improving the items’ descriptions and response options. Conclusions Given these results, all nine items were retained, and no items were added to the measure. Based on respondents’ feedback, minor changes were made to the wording of some descriptions and response options of items. Concluding, the feasibility and content validity of the WOOP seem satisfactory. Further validation of this new measure is required, in different health and social care settings and among subgroups of older people with potentially different views on what constitutes well-being.

Aplikasi Web Analisis Sentimen Dengan Algoritma Multinomial Naïve Bayes

Teknologi adalah keseluruhan sarana untuk menyediakan sebuah pelayanan yang diperlukan bagi terciptanya dan kenyamanan hidup manusia adalah aplikasi. Pada jejaring media sosial Twitter banyak pengguna yang menulis tweet tentang aplikasi web. Tahap dilakukan penambangan opini pengguna terkait kata kunci Aplikasi Web mengacu pada penggunaan bahasa alami, analisis teks untuk mengidentifikasi, mengekstrak, mengukur, dan mempelajari keadaan efektif dan informasi subjektif secara sistematis pada data opini di twitter. Dengan menggunakan metode klasifikasi teks yang telah banyak digunakan adalah algoritma Multinomial Naive Bayes. Metode ini memanfaatkan teorema probabilitas yang mana teorema bayes dan fungsionalitas data mining yaitu klasifikasi naïve bayes. Penelitian ini berfokus pada opini pengguna jejaring sosial twitter dengan kata kunci aplikasi data web ini diambil dari API twitter dengan jumlah item data 1000 selanjutnya klasifikasi opini pengguna dan data preproses. Dari hasil jumlah pengujian dalam algoritma kinerja kita menggunakan Confusion Matrix dan merepresentasikan prediksi dan kondisi sebenarnya(aktual) dari data yang dihasilkan oleh kita bisa menentukan Accuracy 69% , Precision merupakan rasio yang benar diprediksi pada label kelas positif 0,67 , netral 0, negatif 1 dan recall merupakan rasio jumlah yang diprediksi benar terhadap data keseluruhan yang benar-benar yaitu kelas positif 1,netral 0, negatif 0,14 dan f1-score merupakan rata – rata dari precision dan recall yaitu kelas positif 0,81,netral 0 , negatif 0,25.